Staff GenAI Research Scientist - Retrieval

P-1214

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description 

As a Staff Research Scientist on the Enterprise Agents team, you will be responsible for keeping up with the latest developments in Agent Context, Information Retrieval, Knowledge Assistants, RAG, Embeddings, and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Staff Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on Information Retrieval for reusable Agent components, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches.
• Drive research and technical strategy across enterprise retrieval and search, including workspace search, vector search.
• Drive algorithmic innovations for Retrieval within Large Language Models. 
• Experience with Agent Benchmarks for retrieval, text-embeddings and LLM Data Quality. 

What We Look for

• 5+ years of 
• PhD in Computer Science or related field with strong foundations in Natural Language Processing and Information Retrieval 
• Developing and implementing methods that extend and improve model capabilities, reliability, and safety. 
• Strong preference for candidates with first-author publications at top ML/systems conferences (EMNLP, ICLR, ACL, NeurIPs) focused on optimization or efficiency.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description 

As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Sr. Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
• Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.

What We Look for

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
• Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Opportunity

At Zeta Global, identity is at the core of our marketing cloud. The Identity team builds and operates backend services that power the Zeta Identity Graph - collecting, resolving, and maintaining billions of behavioral, demographic, and transactional signals. These services enable people-based marketing at scale, ensure trust and transparency in how identity data is managed, and provide critical APIs and event streams consumed across Zeta’s platform. Our systems support more than 235 million consumer profiles and process billions of events monthly, requiring services that are highly available, low-latency, and built to scale

We are looking for a Lead Software Engineer who brings strength in both backend distributed systems and data engineering. In this role, you’ll design APIs and event-driven services, scale our systems to handle rapidly growing data volumes, and modernize our platform for resilience, transparency, and performance.

You Will:

• Design and build backend services and APIs for identity resolution, graph transparency, and integrations.
• Develop and optimize event-driven pipelines and workflows processing billions of signals.
• Deploy and operate cloud-native services on EKS/Kubernetes, leveraging Helm for repeatable deployments.
• Ensure reliability, observability, and scalability across services and data pipelines.
• Collaborate across engineering, product, and data teams to deliver end-to-end identity solutions.
• Mentor engineers and influence architecture and roadmap

You Have:

• 5+ years of experience in backend and/or data engineering at scale.
• Strong skills in Python, Java, or Scala, with expertise in APIs, distributed systems, and event-driven design.
• Hands-on experience with Kafka (or similar), Spark/Hive/Flink, and workflow schedulers (Airflow/Luigi).
• Proficiency with Kubernetes (EKS preferred) and deployment practices (Helm, service meshes).
• Solid knowledge of SQL, data modelling, and cloud platforms (AWS).
• Familiarity with columnar / NoSQL databases (Aerospike, Snowflake, HBase, Scylla, Couchbase).
• Strong communication skills and a track record of driving technical direction and mentoring teams.

Bonus Skills:

• Experience with large-scale or multi-tenant distributed systems.
• Exposure to real-time streaming frameworks (Flink, Storm).
• Knowledge of open table formats (Iceberg, Hudi, Delta Lake).
• Background in security, compliance, or privacy related to identity systems.

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $150,000 - $200,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-DD1

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Opportunity

At Zeta Global, identity is at the core of our marketing cloud. The Identity team builds and operates backend services that power the Zeta Identity Graph - collecting, resolving, and maintaining billions of behavioral, demographic, and transactional signals. These services enable people-based marketing at scale, ensure trust and transparency in how identity data is managed, and provide critical APIs and event streams consumed across Zeta’s platform. Our systems support more than 235 million consumer profiles and process billions of events monthly, requiring services that are highly available, low-latency, and built to scale

We are looking for a Lead Software Engineer who brings strength in both backend distributed systems and data engineering. In this role, you’ll design APIs and event-driven services, scale our systems to handle rapidly growing data volumes, and modernize our platform for resilience, transparency, and performance.

You Will:

• Design and build backend services and APIs for identity resolution, graph transparency, and integrations.
• Develop and optimize event-driven pipelines and workflows processing billions of signals.
• Deploy and operate cloud-native services on EKS/Kubernetes, leveraging Helm for repeatable deployments.
• Ensure reliability, observability, and scalability across services and data pipelines.
• Collaborate across engineering, product, and data teams to deliver end-to-end identity solutions.
• Mentor engineers and influence architecture and roadmap

You Have:

• 5+ years of experience in backend and/or data engineering at scale.
• Strong skills in Python, Java, or Scala, with expertise in APIs, distributed systems, and event-driven design.
• Hands-on experience with Kafka (or similar), Spark/Hive/Flink, and workflow schedulers (Airflow/Luigi).
• Proficiency with Kubernetes (EKS preferred) and deployment practices (Helm, service meshes).
• Solid knowledge of SQL, data modelling, and cloud platforms (AWS).
• Familiarity with columnar / NoSQL databases (Aerospike, Snowflake, HBase, Scylla, Couchbase).
• Strong communication skills and a track record of driving technical direction and mentoring teams.

Bonus Skills:

• Experience with large-scale or multi-tenant distributed systems.
• Exposure to real-time streaming frameworks (Flink, Storm).
• Knowledge of open table formats (Iceberg, Hudi, Delta Lake).
• Background in security, compliance, or privacy related to identity systems.

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $150,000 - $200,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-DD1

About the Role

The Data engineering team has been created keeping in mind the importance and criticality of data for the overall success of Chime.  The mission of this group is to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making.. As a core member of the team, you will have the opportunity to build scalable data pipelines and frameworks.  Additionally, you will have the unique opportunity to architect and build workflows that could potentially become de facto standards for the fintech industry.

The base salary offered for this role and level of experience will begin at $164,000.00 and go up to $227,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.

In this role, you can expect to

• Be a hands-on data engineer, building, scaling and optimizing ETL pipelines
• Design data schemas and scale them data  for 10x data growth 
• Ownership of all aspects of data - data quality, data governance, schema design, data quality and security
• Develop scalable data architecture and standardized data models that enable self-serve data insights using AI.
• Own the ETL workflows and make sure the pipeline meets data quality and availability requirements
• Work closely with partner teams, like Data Science, Analytics and DevOps

To thrive in this role, you have

• 5+ years experience transforming data to governed and lucid datasets
• 5+ years of hands-on experience to build and deploy production-quality data pipelines
• 5+ years of experience working with stakeholders to provide business insights
• 5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python 
• 3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata
• Track record of successful partnerships with Analytics, Data Science and DevOps teams 
• Understanding of key metrics for data pipelines and has built solutions to provide visibility to partner teams
• Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.

#LI-Onsite #LI-GC1

About the Role

You’ll join the Data Platform team, responsible for building the backend services and “data products” that power how data moves through the company. We create the core platform primitives - high-quality event streams, reliable access layers, and developer-friendly APIs/tools - so teams across the org can self-serve what they need and ship faster. You’ll design, build, and run backend services that create value from our company data, and make our data platform more self-serve (DIY)- so product and engineering teams can easily create and operate event-driven architectures, publish/consume streams, define access models, and ship data products end-to-end. You’ll also build LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products.

Responsibilities

• Identify, design, and develop foundational data infrastructure components capable of handling millions or billions of events daily
• Analyze and improve the robustness and scalability of existing data processing infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable infra-as-code and software for both new and existing systems
• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
• Participate in an on-call rotation to address critical incidents when necessary

Requirements

• 6+ years building production backend systems (distributed systems, APIs, data services).
• Strong skills in at least one backend language (e.g., Go, Python, Java, Rust) and API design (REST/gRPC).
• Demonstrated ability to own services end-to-end: design docs, implementation, testing, deployment, on-call, and iteration based on real usage.
• Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, strong design patterns, and systems that are easy to evolve.
• Solid data modeling and query skills (SQL) and experience with at least one of:

• • Streaming/eventing (Kafka/PubSub/Kinesis, etc.)
  • Workflow/compute (Airflow/Spark/Flink/Trino, etc.)
  • OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech)

• AI augmentation mindset:
  • You understand the state-of-the-art ways engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, eval-driven iteration, retrieval/knowledge grounding), and you apply this thoughtfully to your own development and to the systems you build.
  • You have engineering judgment and you understand when AI Augmentation can fail or create team dynamics issues, putting mitigation mechanisms and guardrails in place.

Nice to have

• Experience building self-serve platforms (control planes, templates/golden paths, paved roads, multi-tenant services).
• LLM/AI product exposure: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
• Security and governance experience: least-privilege access, auditability, data retention, PII handling.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $240,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

Together AI is building high-performance inference compute and the software platform around it. We’re looking for a Staff Data Warehouse Engineer with strong fundamentals and high growth potential to evolve into a technical lead. You’ll design and operate the warehouse from bronze → silver → gold, own core data models and metrics, and raise the bar on data quality and governance across the org.

Responsibilities

• Architect and operate a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data.
• Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented).
• Design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Lead Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement and automate data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Establish data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Build and maintain a business semantic layer (consistent metric definitions, dimensions, and reusable logic) used by notebooks/BI.
• Partner with stakeholders (Product, Engineering, Finance, GTM, Ops) to translate questions into durable datasets and metrics.
• Use SQL, Python, and Spark where scale demands it; optimize for correctness, performance, and cost.
• Mentor engineers and contribute to standards (code review, design docs, runbooks), paving the path to tech lead.

Requirements

• Strong warehouse fundamentals and production experience delivering trusted datasets and metrics.
• Expert SQL (window functions, dimensional modeling, performance tuning).
• Hands-on with dbt (models, tests, docs, snapshots, macros) and Airflow (DAG design, backfills, reliability).
• Solid Python for data tooling and automation; experience with Spark (PySpark/SQL) is a plus.
• Practical experience with SCD2, star schemas, and handling slowly changing business entities.
• Strong stakeholder management: you can drive alignment on definitions, tradeoffs, and delivery timelines.
• High standards for data quality, reliability, and maintainability.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $240,000 - $275,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Overview

Zeta Global is seeking a Lead Software Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows.

This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability.

The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments.

What You’ll Build

• Full-stack applications supporting HCP and patient (DTC) audience discovery, segmentation, and activation
  • Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
  • Identity resolution and data linkage services across fragmented data sources
  • Reporting, attribution, and measurement systems connecting campaigns to outcomes
  • APIs and services enabling downstream activation, analytics, and partner integrations

Key Responsibilities

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
  • Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
  • Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
  • Implement identity resolution logic including matching, deduplication, and graph-based linkage
  • Ensure high data quality through validation, reconciliation, and monitoring frameworks
  • Design systems with strong security controls, including encryption, access control, and auditability
  • Apply privacy-by-design principles across all systems handling PHI/PII
  • Partner with Product and Data teams to translate healthcare requirements into scalable architectures
  • Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
  • Mentor engineers and act as a technical leader across the team

Engineering Expectations

• Strong experience designing distributed systems (microservices, event-driven architectures)
  • Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
  • Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
  • Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
  • Experience building modern front-end applications (React or similar)
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
  • Experience implementing observability (logging, metrics, tracing) and reliability patterns
  • Strong understanding of performance optimization and scalability tradeoffs

Healthcare & Domain Expectations

• Experience working with HCP data (provider identity, targeting, segmentation)
  • Experience with patient / DTC data workflows and privacy-aware systems
  • Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
  • Familiarity with identity graphs and data onboarding patterns
  • Experience building reporting or attribution systems tied to business outcomes
  • Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements

Qualifications

• 8–10 years of software engineering experience with increasing technical ownership
  • Proven track record of building and scaling data-intensive or distributed systems
  • Experience working in regulated environments (healthcare strongly preferred)
  • Strong system design and architecture skills
  • Ability to lead technically while remaining hands-on in implementation
  • Strong collaboration skills across engineering, product, and data teams

Preferred

• Experience with healthcare data providers or identity ecosystems
  • Background in AdTech, MarTech, or audience/data platforms
  • Experience with privacy-enhancing technologies (tokenization, clean rooms)
  • Exposure to ML/AI-driven data products or analytics systems

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $215,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-TS1

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Overview

Zeta Global is seeking a Lead Software Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows.

This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability.

The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments.

What You’ll Build

• Full-stack applications supporting HCP and patient (DTC) audience discovery, segmentation, and activation
  • Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
  • Identity resolution and data linkage services across fragmented data sources
  • Reporting, attribution, and measurement systems connecting campaigns to outcomes
  • APIs and services enabling downstream activation, analytics, and partner integrations

Key Responsibilities

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
  • Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
  • Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
  • Implement identity resolution logic including matching, deduplication, and graph-based linkage
  • Ensure high data quality through validation, reconciliation, and monitoring frameworks
  • Design systems with strong security controls, including encryption, access control, and auditability
  • Apply privacy-by-design principles across all systems handling PHI/PII
  • Partner with Product and Data teams to translate healthcare requirements into scalable architectures
  • Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
  • Mentor engineers and act as a technical leader across the team

Engineering Expectations

• Strong experience designing distributed systems (microservices, event-driven architectures)
  • Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
  • Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
  • Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
  • Experience building modern front-end applications (React or similar)
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
  • Experience implementing observability (logging, metrics, tracing) and reliability patterns
  • Strong understanding of performance optimization and scalability tradeoffs

Healthcare & Domain Expectations

• Experience working with HCP data (provider identity, targeting, segmentation)
  • Experience with patient / DTC data workflows and privacy-aware systems
  • Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
  • Familiarity with identity graphs and data onboarding patterns
  • Experience building reporting or attribution systems tied to business outcomes
  • Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements

Qualifications

• 8–10 years of software engineering experience with increasing technical ownership
  • Proven track record of building and scaling data-intensive or distributed systems
  • Experience working in regulated environments (healthcare strongly preferred)
  • Strong system design and architecture skills
  • Ability to lead technically while remaining hands-on in implementation
  • Strong collaboration skills across engineering, product, and data teams

Preferred

• Experience with healthcare data providers or identity ecosystems
  • Background in AdTech, MarTech, or audience/data platforms
  • Experience with privacy-enhancing technologies (tokenization, clean rooms)
  • Exposure to ML/AI-driven data products or analytics systems

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $215,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-TS1

P-1549

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

The Mission

Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter's revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds.

We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers. This is a zero-to-one role with two deeply connected charters:

1. Build the retrieval stack — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems.
2. Build the search subagents that sit on top of that stack and reason about what context is needed, how to retrieve it, and whether the right thing actually came back — closing the loop between an agent's intent and the substrate that serves it.

If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you.

What You Will Do

• Build the full retrieval stack from scratch. Own the end-to-end system: query understanding, content understanding and indexing, hybrid retrieval, ranking, and evaluation. Make the architectural calls that will define how Databricks agents access context for years to come.
• Retrieve across heterogeneous data — structured and unstructured. Index and rank across structured assets (tables, columns, SQL queries, dashboards, code, notebooks, jobs) and unstructured content (docs, wikis, tickets, chat, images, video, audio). Each modality has its own signals — design retrieval that exploits them rather than flattens them.
• Connect to the SaaS surface area customers actually use. Build connectors and retrieval adapters for the systems where enterprise knowledge lives. Treat each retrieval source with its own freshness, permissions, and ranking signals.
• Optimize for two consumers at once. Retrieval must serve both LLMs (grounded, token-efficient, hallucination-resistant context) and humans (intuitive, explainable discovery). These are different objectives and require different signals — own both.
• Crack query understanding for agents. Agent queries don't look like web queries. Build query rewriting, decomposition, intent classification, and entity resolution tuned for multi-turn agentic workflows.
• Crack content understanding at scale. Build the pipelines that extract structure, entities, embeddings, summaries, and metadata from every supported asset type — and keep them fresh as customer data evolves.
• Build search subagents that reason about retrieval. Design the agentic layer that decides what context is needed, which sources to query, how to decompose and route the search, and — critically — whether the retrieved content is actually sufficient to answer the question. These subagents will plan multi-hop searches, issue follow-up queries when results are weak, ground claims against retrieved evidence, and hand back high-confidence context (or signal failure) to upstream agents. This is where IR meets agentic reasoning.
• Build the evaluation flywheel for both retrieval and subagents. Stand up offline evals (nDCG, MRR, Recall@K, Precision@K), LLM-as-judge harnesses, human-in-the-loop labeling, and online experimentation. Extend evaluation beyond ranking metrics to measure subagent decision quality — did it ask the right follow-up?, did it correctly recognize when retrieval failed?, did it ground its answer in the right evidence?. Quality you can't measure is quality you can't ship.
• Set technical direction and grow the team. Set the multi-year roadmap, mentor senior engineers, partner with Research, Product, and Platform leaders, and raise the technical bar across the org.

What We're Looking For

• 10+ years of software engineering experience, with significant time spent building production retrieval, search, or RAG systems at scale.
• Deep Information Retrieval (IR) expertise: lexical retrieval (BM25, Lucene/Elasticsearch/OpenSearch), dense retrieval (embeddings, ANN indexes — FAISS, ScaNN, HNSW), hybrid retrieval, and learning-to-rank.
• Hands-on experience with modern LLM-era retrieval: RAG architectures, query rewriting, re-ranking with cross-encoders, long-context strategies, and grounding techniques that reduce hallucination.
• Experience designing agentic systems on top of retrieval — search planners, multi-hop / iterative retrieval, self-reflection and sufficiency checks, tool-using agents that decide what to fetch and verify what came back.
• Strong grasp of relevance evaluation: nDCG, MRR, Precision@K, Recall@K; offline/online experimentation; LLM-as-judge frameworks; building human labeling pipelines.
• Experience working across structured and unstructured data — you've indexed and ranked over tables, code, and documents in the same system, and have opinions about how to do it well.
• Track record of building 0→1: you've stood up a retrieval system from an empty repo, made the foundational architectural decisions, and grown it into something that customers depend on.
• Demonstrated ability to operate as a technical leader: setting direction across teams, mentoring senior engineers, and influencing roadmap with research, product, and platform partners.

Nice to Have

• Experience building retrieval over enterprise SaaS sources (permissions, freshness, multi-tenancy, ACL-aware indexing).
• Background in agentic systems, tool use, or multi-turn retrieval for LLM agents.
• Contributions to open-source IR/search projects, or publications at SIGIR, KDD, WWW, EMNLP, or similar venues.
• Experience training or fine-tuning embedding models, rerankers, or query understanding models.

Why This Role

• Foundational impact. Retrieval is the single biggest lever on agent quality. The stack you build will sit underneath every Databricks agent and every customer-built agent on our platform.
• Greenfield with scale. You get the rare combination of starting from a clean sheet and having immediate access to massive enterprise scale, real customer data, and a world-class research org.
• The right team. You'll work alongside engineers and researchers behind Lakehouse, Apache Spark™, Delta Lake, MLflow, MosaicML, and DBRX.

Location

This role is based in our Mountain View, CA or San Francisco, CA office. Hybrid in-office collaboration expected.

We are looking for a Senior Data Engineer to join our Data & ML Platform team, responsible for development, maintenance and support for Oura’s Datalake and adjacent systems, collaborating closely with data scientists, analysts and other departments utilizing the Datalake.

This is a hybrid role based in San Francisco, CA, working onsite 1-2 days per week.

We have offices in San Francisco, San Diego and Los Angeles for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.

What you will do: 

• Build, operate, and improve Oura’s Datalake consisting of systems to move, process, and store large amounts of data (Terabyte–Petabyte scale) leveraging tools such as AWS Kinesis, S3, Spark / Glue, Athena, dbt, Iceberg, Snowflake, Docker, workflow engines, and more.
• Design and implement data models and pipelines with a strong focus on data quality, reliability, and governance.
• Ensure that our data platform and processes meet privacy, compliance, and security requirements.
• Build components that support the handling of datasets, training, testing, and release of new on-device and cloud-based ML models.
• Independently collaborate with different stakeholders including Data Scientists, Testing, Firmware, and Hardware to define and implement improvements and new functionality and support internal Datalake consumers in their day-to-day work.
• Write code, mostly in Python and SQL  with occasional additions Typescript, Java or some other language.

We would love to have you on our team if you have:

• 5+ years of experience developing and operating production systems.
• Experience running, monitoring, and debugging production systems at scale on a public cloud. We rely on AWS but experience with other cloud platforms counts too.
• Good architectural understanding of event-driven architectures, workflow engines, database, and data warehouse systems.
• Ability to design robust data models and pipelines, with attention to data accuracy and integrity.
• Experience in building infrastructure and components following best practices such as CI/CD and infrastructure as code.
• Demonstrated skills in writing well-structured, testable, and high-performance code.
• Familiarity with some of the following: Workflow engines, Stream processing, MLops, Spark, Athena, SQL, dbt, Databricks.
• You are self-motivated, proactive, and able to lead and manage your own work effectively.
• A pragmatic and goal oriented approach to development.

What Makes You Stand Out

• Real-life experience with Databricks.
• Familiarity and experience with the Data Mesh approach
• Broad knowledge of software fundamentals, databases, warehouses, and system design with experience on various programming languages

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1 $172,550 - $203,000
• Region 2 $159,000 - $187,000
• Region 3 $148,000 - $174,000

A recruiter can determine your zones/tiers based on your US location.

About The Role

As .Monks continues to expand our Data & Digital Media capabilities, we are looking for a senior professional to support and grow our services in marketing analytics.

In this role, you will support both ongoing and new engagements by overseeing the delivery of actionable and impactful insights at the intersection of business, site, and paid media data. This position plays a key role in evolving our analytics capabilities while also working closely with client stakeholders to deliver high-quality, scalable solutions.

This is a highly hands-on, client-facing role, with a strong focus on building and maintaining data pipelines, enabling measurement frameworks, and supporting advanced analytics use cases.

Key Responsibilities

• Support analytics delivery across client engagements, ensuring high-quality outputs and actionable insights
• Design, build, and optimize data pipelines and workflows to support reporting, forecasting, and measurement initiatives
• Understand business needs and contribute to the development of cross-channel measurement frameworks
• Partner closely with client stakeholders to translate data into insights and recommendations
• Support test design and analysis to evaluate performance and identify opportunities for improvement
• Contribute to the development of new analytics approaches, tools, and processes
• Identify opportunities to improve efficiency, automation, and data operations
• Collaborate with cross-functional teams (media, strategy, analytics) to deliver integrated solutions

Primary Qualifications

• Bachelor’s or Master’s degree in a quantitative field (e.g., computer science, statistics, applied mathematics, economics, engineering) or equivalent experience
• Strong hands-on experience with SQL and data pipeline development (ETL/ELT)
• Experience working with large datasets in cloud environments (e.g., GCP, Databricks, or similar)
• Working knowledge of Python or similar languages for data processing or automation
• Familiarity with data visualization tools (e.g., Tableau, Datorama, or similar)
• Understanding of digital advertising measurement, reporting, and attribution methodologies
• Strong communication skills, with the ability to translate complex data into clear insights
• Ability to work independently and manage priorities in a fast-paced, ambiguous environment

Nice to Have

• Experience with Databricks, Spark, or distributed data processing frameworks
• Exposure to marketing mix modeling (MMM), forecasting, or advanced measurement techniques
• Experience working in consulting, agency, or embedded client environments
• Familiarity with AI/ML or emerging data applications

Additional Information

• This is an individual contributor role with significant ownership and client exposure
• Success in this role requires a proactive, self-starter mindset and strong stakeholder management skills
• This role supports a West Coast–based team, so candidates should be comfortable collaborating with PST stakeholders and flexing hours when needed (e.g., occasional late afternoon meetings)

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

This role is subject to our Return to Office (RTO) policy. If you reside within a commutable distance of one of our office locations, you will be expected to work from the office a set number of days per week. The specific details, including the number of required office days, will be in accordance with the company’s then-current RTO policy, which is subject to change from time to time.

#LI-HYBRID

#LI-ZZ1

GAQ127R112

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.

Databricks is looking for a Senior Financial Analyst to join our G&A FP&A Team in our mission to help data teams solve the world's toughest problems. You will report to the Sr. Finance Manager, and will be a key finance partner to the G&A organizations.

You will serve as a trusted advisor to provide the financial insights, analysis, and guidance to optimize investment decisions and accelerate business growth. You will improve forecast reliability, enhance corporate reporting, partner with IT, People and Legal across different levels, and help the business to be successful and achieve its goals, grounded in financial reality and modeling, and analysis.

The impact you will have:

• Be the key Finance partner to IT, People and Legal leaders and their teams, including:
• Partner with the business to drive forecast accuracy
• Prepare and own budget vs. actual variance analysis and other relevant reporting
• Build, maintain and improve detailed financial models that track and analyze functional costs and their impact cross-functionally and on the company’s overall performance, including but not limited to the Recruiting Capacity model and IT CAPEX forecast
• Collaborate with the Accounting on accruals and other elements of the close process
• Assist with and manage frequent ad hoc requests and strategic projects to support senior leaders in making informed business decisions
• Participate in the company’s long-range strategic planning
• Lead process and system improvement and scaling projects for your area to drive the company’s continued growth and scaling.  

What we look for:

• Bachelor's Degree in Business, Finance, Economics, Accounting, or a comparable quantitative field
• 4+ years of FP&A, Strategic Finance, or related experience (e.g., Investment Banking, Management Consulting), with a focus on technology; familiarity with the software industry, SaaS business, or consumption-based models
• Experience with supporting G&A functions is a plus
• Experience in building financial models independently and preparing recommendations
• Excellent analytical, organizational, and collaboration skills
• Knowledge of generally accepted accounting principles and experience with GAAP and non-GAAP financial metrics
• High competency with systems such as Anaplan or Pigment, Workday, Netsuite, Salesforce, Coupa, and Zip
• Prior experience using SQL or willingness to learn is a plus

Want to help us help others? We’re hiring! 

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

Join Us! GoFundMe is seeking a customer-obsessed, insights-driven and savvy Principal Consumer Product Marketing Manager to lead high-impact, consumer-facing initiatives across our platform. You’ll be instrumental in shaping compelling product narratives, crafting GTM strategies, and influencing cross-functional teams to drive measurable results across our consumer lifecycle.

From early strategy through activation and continuous optimization, you’ll help connect people to the causes and communities that matter most. You’ll be expected to operate with a high degree of independence, manage ambiguity with clarity, and lead initiatives that impact both team and company-wide goals. 

Candidates considered for this role will be located in the San Francisco, Bay Area. There will be an in-office requirement of 2-3x a week.

The Job

Strategic Product & Go-to-Market Leadership

• Lead end-to-end go-to-market strategies that bring our products to life—shaping the vision, rallying cross-functional partners, and turning ideas into impactful launches. 
• Obsess over understanding our ideal customers—grounded in data and human insight—to define clear segments and craft standout messaging and tactics that inspire people to help others.
• Flex your analytics muscle through defining, tracking and communicating key metrics that show the impact of product marketing efforts on product adoption, engagement, and growth.
• Translate business objectives and consumer needs into integrated marketing and channel strategies that drive meaningful adoption, engagement, and growth.
• Keep the momentum going after launches, leading energizing retros, uncovering what worked (and what didn’t), and turning those insights into smarter tests, sharper iterations and scaled impact.
• Bring a highly data-driven approach to decision-making, leveraging quantitative and qualitative insights, including a deep partnership with research to optimize strategy and performance.
• Bring a right-brained spark to GTM - using creative, unconventional thinking to solve tough challenges and help us stand out in a crowded, competitive space.
• Leverage journey mapping to better understand consumer experiences and inform full-funnel strategies.

Positioning & Messaging

• Craft clear, differentiated, and emotionally resonant messaging frameworks that map to business objectives, customer needs, behaviors, and motivations.
• Synthesize complex product information and research into clear, compelling product narratives aligned with user motivation, market opportunity, and business strategy.
• Build and maintain messaging frameworks, positioning guides, and audience strategies to be used across all GoFundMe business teams. 
• Maintain an understanding of the competitive set, ensuring messaging and positioning stand out in the market and reflect current trends and dynamics.

Strategic Influence

• Serve as the glue between Product, Marketing, Research, and Data, translating insights and data into action, particularly in fast-moving, high-complexity environments. 
• Partner closely with PMs, Engineers, Researchers, and Designers to inform product strategy and roadmap through consumer insights, competitive landscape, market dynamics, and a deep understanding of emerging cultural trends shaping user behavior.
• Identify and validate product hypotheses through testing frameworks and research driven feedback loops.
• Be deeply connected with research, using it as a foundational input for strategic decision-making across GTM and product marketing efforts.

Operational Excellence

• Ensure alignment across Marketing, Comms, Social, and Growth teams on execution timelines, assets, and performance goals.
• Proactively identify risks or misalignments and take initiative to realign plans or surface strategic pivots.
• Lead by example with rigor, clarity, and a bias toward action.

What Success Looks Like

• GTM strategies are clearly defined, well communicated, and executed with confidence, resulting in product adoption, engagement, and business growth.
• Stakeholders feel informed, empowered, and aligned across functions and priorities.
• Product marketing consistently fills the strategic and executional gaps across launches for both product and marketing functions.
• Messaging resonates with users and scales across surfaces, from lifecycle emails to landing pages to all other owned, earned and paid channels.
• You are seen as a strategic leader and reliable owner by Product, Marketing, and Executive teams alike.

You

• 6–10+ years of experience in Product Marketing, with proven impact on consumer-facing product launches and strategic initiatives.
• A strong track record of independently owning high-impact product launches, including testing frameworks and full-funnel marketing campaigns.
• Exceptional ability to synthesize ambiguity into actionable strategy, and to provide clarity where there is none.
• Mastery of product storytelling, messaging frameworks, and positioning across varied user segments and lifecycle stages, paired with prolific writing skills that translate complex ideas into clear, compelling narratives across channels.
• A consumer-obsessed mindset, consistently advocating for user-first thinking and grounding decisions in user behavior and research.
• Excellent project management, communication, and stakeholder engagement skills.
• Familiarity with tools such as Figma, ClickUp, Amplitude, and Slack to drive GTM planning and collaboration.

Why you’ll love it here

• Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year.
• Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.
• Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together.
• Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits.
• Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
• Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow.
• Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.
• Community Engagement: Make a difference through our volunteering program.

We live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!

GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences.  We do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.

The annual U.S. salary range for this full-time position is $171,000 - $257,000. The company also offers equity and other benefits to employees, including healthcare, dental, vision, life insurance and 401(k) saving program. In addition to this wage, there are geolocation differentials that will increase pay depending on the work location. Additionally pay may vary depending on other factors including skills, experience, education, or training. Your recruiter can share more about the specific total compensation package based on your location during the hiring process.

If you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com. 

Global Data Privacy Notice for Job Candidates and Applicants:

Depending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here. By submitting your application, you are agreeing to our use and processing of your data as required. 

Learn more about GoFundMe:

We’re proud to partner with GoFundMe.org, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their FY ‘25 annual report.

Our annual “Year in Help” report reflects our community’s impact in advancing our mission of helping people help each other.

For recent company news and announcements, visit our Newsroom.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

The Role 

We’re looking for a Senior Data Engineer to design, build, and operate the data pipelines and aggregates that power Zeta’s AdTech platform. This is a hands-on individual contributor role focused on high-scale batch + streaming data processing, reliable data products, and analytics-ready datasets that enable prediction, agentic workflows, BI reporting, and measurement. You will partner closely with backend, ML, and product teams to deliver trusted, well-modeled data with strong performance, quality, and observability. 

What You’ll Do 

• Build data pipelines: Develop robust batch and streaming pipelines (Kafka/Kinesis) to ingest, transform, and enrich large-scale event data (impressions, clicks, conversions, costs, identity signals). 

• Create data aggregates & marts: Design and maintain curated aggregates and dimensional models for multiple consumers—prediction models, agents, BI dashboards, and measurement workflows. 

• Data modeling & contracts: Define schemas, data contracts, and versioning strategies to keep downstream systems stable as sources evolve. 

• Data quality & reliability: Implement validation, anomaly detection, backfills, and reconciliation to ensure completeness, correctness, and timeliness (SLAs/SLOs). 

• Performance & cost optimization: Optimize compute/storage for scale (partitioning, file sizing, incremental processing, indexing), balancing latency, throughput, and cost. 

• Orchestration & automation: Build repeatable workflows with scheduling/orchestration (e.g., Airflow, Dagster, Step Functions) and CI/CD for data pipelines. 

• Observability for data systems: Instrument pipelines with metrics, logs, lineage, and alerting to accelerate detection and root-cause analysis of data issues.
• Security & governance: Apply least-privilege access, PII-aware handling, and governance controls aligned with enterprise standards.

Qualifications

• 5+ years building production data pipelines and data products (batch and/or streaming) in a high-scale environment.
• Strong experience with SQL and data modeling (dimensional modeling, star/snowflake schemas, event modeling). 

• Hands-on experience with streaming systems (Kafka preferred) and/or AWS Kinesis, including event-driven designs. 

• Proficiency in one or more languages used for data engineering (Python, Java, Scala, or Go). 

• Experience with distributed data processing (Spark, Flink, or equivalent) and performance tuning at scale. 

• Experience with AWS data services and cloud-native patterns (S3, Glue/EMR, Athena, Redshift, etc. as applicable). 

• Familiarity with lakehouse/table formats and large-scale storage patterns (e.g., Parquet; Iceberg/Hudi/Delta are a plus). 

• Experience with orchestration/workflow tooling (Airflow/Dagster/Step Functions) and CI/CD for data workloads. 

• Strong data quality/observability practices (tests, monitoring, lineage; understanding of SLAs/SLOs). 

• Experience with SQL + NoSQL data stores (e.g., Postgres/MySQL; DynamoDB/Cassandra/Redis) and choosing the right store per use case.
• Clear communicator and collaborator; able to work with mixed audiences and translate needs into reliable data interfaces. 

Preferred Experience

• AdTech / programmatic advertising domain knowledge: DSP/SSP/exchange/RTB concepts and data flows. 

• Experience building measurement pipelines (attribution, incrementality, lift, or experimentation analytics).
• Experience supporting ML feature stores, offline/online feature generation, or model training datasets. 

• Experience with real-time analytics stores (Druid/ClickHouse/Pinot) and high-cardinality aggregation strategies. 

• Deep knowledge of data governance/privacy, including PII handling and consent-aware data processing. 

• Open-source contributions, publications, or conference speaking. 

• BS/MS in CS/Engineering or equivalent practical experience. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $165,000 - $175,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases

#LI-YW1

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.

• Remote - San Francisco
• Remote - Texas 
• Remote - NYC
• Remote - Boston 
• Remote - Chicago 
• Remote - Seattle 
• Remote - Atlanta 

We are looking for a Sales Director to join our growing business. You will lead an existing team of Enterprise Account Executives and you will be measured by achieving your team’s overall quota, new logo acquisition, and growing Databricks usage. This is a team of account executives that are passionate about building a data ecosystem, technically knowledgeable, and have a desire to help customers and partners succeed. You will report to the Regional Vice President.

The impact you will have:

• Lead, grow and inspire the Enterprise Account Executives to help them overachieve on their goals and objectives.
• Instill a culture of teamwork focused on leading with measurable business value and achieving desired customer outcomes.
• Develop trust-based relationships with customers and partners to ensure long-term success.
• Drive ongoing learning of the continuous innovation being delivered to our customers via our data intelligence and GenAI solutions.
• Actively participate in the region’s growth plans, ensure forecast accuracy and build a customer-focused, durable, high-growth business.

What we look for:

• You live the Databricks’ core values and instill them in the team you are leading.
• You will have 5+ years of successfully building and leading high-growth new logo sales teams serving enterprise customers within the Big Data, Cloud (Azure, AWS, GCP), Analytics, AI spaces.
• History of exceeding quota and thriving in hyper-growth Enterprise technology companies.
• Understanding of value selling and sales methodologies such as MEDDPICC, Challenger, Command of Message.
• Knowledge of developing partner ecosystems to help grow strategic enterprise territories and ensure customer success.
• With this role, a proven track record of leading teams to success when focused on enterprise territories and driving consumption is critical. 

The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems.

To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound.

We are seeking a staff ML engineer to design and evolve the large-scale offline platform. This role focuses on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at scale. You will work closely with ML engineers and platform teams to ensure our pipelines can efficiently handle growing data volumes and increasingly complex training workloads.

You will play a key role in shaping how model datasets are prepared as well as model training, validated, and delivered to distributed training systems, while ensuring the reliability, scalability, and performance of our offline ML platform.

What you'll be doing

• Design and operate large-scale data pipelines that generate training datasets used for machine learning training and experimentation
• Develop infrastructure that supports distributed training workflows using technologies such as Pytorch, Ray Data, and Ray Train, etc.
• Integrate ML pipelines with workflow orchestration systems (e.g., Flyte, Airflow, or similar) to enable reliable multi-stage training workflows
• Improve reproducibility and observability of ML pipelines through dataset validation, monitoring, and automated testing
• Optimize performance and resource utilization across distributed compute systems used for data processing and model training
• Partner closely with ML engineers to enable efficient large-scale experimentation and model iteration
• Lead architectural improvements to ensure our offline ML pipelines remain scalable, reliable, and cost-efficient

What we're looking for

• Strong experience building large-scale ML pipelines
• Experience working with distributed computing frameworks such as Ray, Spark, Flink and familiarity in the Ray ecosystem (Ray Data, Ray Train) for distributed data processing and model training
• Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines
• Deep experience designing and operating production-grade data pipelines
• Strong programming skills in Python and experience working with large-scale distributed workloads
• Experience with modern data infrastructure (data lakes, warehouses, orchestration systems, streaming platforms)
• Strong systems thinking, with the ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems
• Proven ability to lead technical direction and influence architectural decisions across teams without formal authority

Additional information

• Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN #LI-ED1

The Trade Desk is a global technology company with a mission to create a better, more open internet for everyone through principled, intelligent advertising. Handling over 1 trillion queries per day, our platform operates at an unprecedented scale. We have also built something even stronger and more valuable: an award-winning culture based on trust, ownership, empathy, and collaboration. We value the unique experiences and perspectives that each person brings to The Trade Desk, and we are committed to fostering inclusive spaces where everyone can bring their authentic selves to work every day.

Do you have a passion for solving hard problems at scale? Are you eager to join a dynamic, globally- connected team where your contributions will make a meaningful difference in building a better media ecosystem? Come and see why Fortune magazine consistently ranks The Trade Desk among the best small- to medium-sized workplaces globally.

What we do  

Our Software Engineers are end-to-end owners who have the opportunity to participate in many aspects of designing, building, and delivering data-focused products for our stakeholders.  

At The Trade Desk, we believe in building the back-end infrastructure of our platform with a focus on quality at scale. This means whether we are building parts of our client-facing applications, internal custom solutions for our own team members, or model pipelines for bidding optimizations, we are making sure that we have infrastructure, development, and tools to do it right and efficiently.  

Our system performs all day, every day serving global traffic. We build a distributed system in a highly collaborative environment, utilizing a broad range of technologies. Our back-end developers work on finding solutions to algorithmic, optimization and scale challenges in everything we do.

About the role:

The Trade Desk Software Engineers are best described as end-to-end owners.

• You will participate actively in all aspects of product strategy – from designing, building, and delivering products for our clients.
• We have dozens of individual, mission-focused teams working across a wide spectrum of technological challenges.
• You will have the opportunity, depending on your interests and aptitude, to lead engineers that focus on building large-scale distributed systems coordinating thousands of servers in cloud and physical data centers around the world, petabyte-scale data challenges, machine learning, advanced visualizations, and interactive user interfaces – to name a few.
• Software Engineers contribute to more than our product – they help build up our team. Through a combination of mentoring and technical leadership of local teams, you will make others better and raise the bar for those around you.

We are a global team with different backgrounds, experiences and perspectives. To complement this team, you will welcome ideas that are different from your own and be well-versed in building from common ground to value, seek out, and foster invisible and visible dimensions of diversity. 

Who you are: 

Our culture is much deeper than just having fun together (though, we do that well too...). We take pride in our engineers being trust-builders, generous givers, scrappy problem solvers, and gritty pursuers of excellence. You do not have to meet all the requirements below, but we believe that people who meet most of them will have a higher likelihood of succeeding in this role: 

• The ideal candidate will have 2 to 5 years of impactful hands-on software engineering experience
• You are a strong communicator. You’re able to collaborate cross functionally with data scientists and root cause pain points in their workflow.
• You have a passion for improving the efficiency of others. The work you will do in Machine Learning Operations will have a big impact on both the data scientists and the data engineers in our organization.
• Experience building large scale data pipelines with spark is a plus.
• Experience building machine learning models is a plus.
• You have a Bachelor’s/Master’s level degree in a computer-science or relevant engineering related field or equivalent experience. Not everyone has the same level of access to opportunities. What is most important to us is what and how you can contribute, which is why our consideration is not limited by the level of education you have.
• You think beyond just the task at hand to deeply understand the 'why' behind what you & your team are doing.
• You are a driver. You will own technical milestones and projects in a ground-breaking and fast-paced environment, driving them from inception till completion. This includes task planning, individual code contribution, and code reviews.
• You understand engineering fundamentals. At our scale, many off-the-shelf techniques and existing technologies (open source and enterprise) simply don't work.
• You are able to work from first principles to evaluate solutions and adapt them to a unique environment.
• You are a broadly skilled engineer, accustomed to developing web services.
• You have experience building always-on systems, working across a variety of technologies and service layers.
• You have a product-focused mindset.
• You have the passion and ability to contribute to the process of discovering what will delight our clients and push forward one of the world’s largest and most influential industries toward a vision of openness, transparency, and evidence-based decision-making.
• You work with confidence and without ego. Our engineers have deep knowledge and exercise a high degree of leadership in their daily work.
• You have strongly-held, defensible ideas, and advocate for what you believe is right.
• You are also adept at identifying and evaluating trade-offs, willing to be proven wrong, and quick to walk through fire to support your fellow teammates.
• You value, seek out, and foster diversity.

Variety of technical opportunity is one of the best things about working at The Trade Desk as a software engineer which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We don't need engineers who know all the answers; we need engineers who can invent the answers no one has thought of yet, to the questions yet to be asked.  

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#LI-AD1

About The Role

The AI team is building cutting-edge solutions that bring the power of AI directly to edge devices while seamlessly integrating with cloud infrastructure. We are looking for a Software Engineer to design and develop high-performance, scalable services to support AI workloads across edge and cloud environments.

What You Might Do

• Contribute to design, build, and maintain services that power AI-driven applications, ensuring scalability and performance.
• Develop APIs and microservices that facilitate seamless integration between cloud-based AI models and edge devices.
• Optimize data pipelines and storage solutions for real-time AI inference and processing.
• Work closely with AI researchers, infrastructure engineers, and frontend developers to deliver end-to-end AI-driven solutions.
• Build and optimize an agent orchestration runtime that enables tool use, memory management, and multi-step reasoning across LLMs, APIs, and edge-connected systems.
• Support the implementation of security and privacy best practices for distributed AI systems.

Essential Qualifications

• Requires at least Masters in Computer Science, Engineering, Data Science, Artificial Intelligence or related fields.
• 1+ years of experience in backend software development, with strong proficiency in Python, Java, and C++. 
• Working knowledge in LLM integration into multi-agent systems with strong understanding of agent orchestration, tool use, and memory/context management.
• Comfortable tinkering with LLMs via prompting and experienced with tools use, task decomposition, and structured outputs.
• Familiarity with database management systems (SQL and NoSQL) and data streaming technologies.
• Strong problem-solving skills and ability to work in a fast-paced, agile environment.

Preferred Skills

• Experience with AI model deployment and integration into backend services.
• Exposure to cloud-edge hybrid architectures and distributed AI workloads.
• Familiarity with on-device AI frameworks such as PyTorch, TensorFlow Lite, ONNX Runtime, or CoreML.

Salary Range: $127,000 - $175,000

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Before Stripe, every growing internet platform had a payments team. Today, every growing internet platform has an Identity team. Identity verification has become core economic infrastructure for online businesses — enabling them to digitally verify their users' identities for fraud prevention, regulatory compliance, and trust and safety purposes.

At Stripe, we're building something more ambitious than a verification product. Our vision is to build the world's most trusted store of verified identities — a single, global, reusable, risk-scored representation of every individual who interacts with Stripe and beyond. This Identity Store becomes a platform with compounding network effects: more verifications enrich the store; a richer store produces better fraud signals; better signals mean lower friction for trusted users; lower friction drives more adoption.

Our product today serves millions of verifications per month for customers like OpenAI, Shopify, and WhatNot, and powers identity verification across multiple internal Stripe products including Fraud, Link, Connect, and Crypto. The problems ahead — adversarial AI and deepfake defense, networked identity infrastructure, progressive verification platforms, and low friction KYC APIs — sit at the frontier of what's possible in identity engineering.

What you’ll do

As a Staff Engineer on the Identity team, you will own the technical direction of one of Stripe's most strategically important product areas. This is not a role defined by task execution — it's a role defined by technical judgment, architectural influence, and the ability to turn an ambitious vision into a reliable, scalable system.

Responsibilities

• Own technical strategy — Define the architecture for Identity's core systems (Identity Store, headless verification platform, fraud detection infrastructure), make build-vs-buy-vs-partner decisions, and surface technical risks before they become customer-facing failures
• Lead 0-1 platform development — Architect net-new systems including the Identity Store, Networked Identity platform, and advanced fraud detection pipeline (behavioral biometrics, deepfake discriminators, adversarial training). Drive the evolution from a hosted-UI product to a headless-API and embedded-components platform
• Drive cross-functional alignment — Be the primary technical voice in roadmap and resourcing discussions. Partner with ML, product, legal, and engineering leads across Risk, Fraud, Link, Connect, and Crypto to ensure Identity's abstractions serve the full breadth of Stripe's product surface
• Raise the technical bar — Set engineering standards across ML, backend, mobile, and front-end; lead design reviews; and mentor senior engineers on the judgment needed to operate a high-stakes, externally-facing product
• Operate with ownership — Be accountable for reliability, scalability, and security of the systems you design — including the observability and alerting that catch model drift and fraud pattern shifts before customers do

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role.
• Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g. building internal or external developer products). 
• Proven track record of delivering pragmatic solutions that accelerate business growth 
• Ability to adjust conversations from high-level discussions to detailed coding 
• Thrives on a high level of autonomy and responsibility 
• Clear and persuasive writing and in-person communication 
• Strong problem-solving skills, critical thinking, determination, and a growth mindset 
• Ability to work effectively with a diverse group of people, genuinely caring for each other and contributing to high level of psychological safety for all team members and partner
• Has experience in a range of software languages and frameworks. Examples of what we work with include:
• Languages: primarily Ruby and Typescript, but also Python, Scala, Java, Go, and SQL (Spark and Trino dialects)
• Frameworks: React, GraphQL Kafka, Protobuf, Airflow, Bazel, Temporal, 
• Others: Mongo, Splunk, Prometheus

Preferred qualifications

• Experience with identity verification, fraud detection, or trust and safety systems — especially systems with adversarial inputs at scale
• Familiarity with ML systems in production: model serving, training pipelines, observability, drift detection, and the feedback loops that keep models accurate under adversarial conditions
• Experience building platform products with multiple consumer types — internal platform teams and external developers — where API backward compatibility and abstraction quality are first-class concerns
• Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly
• Exposure to the technical stack we work with: primarily Ruby and TypeScript on the backend and web, Python for ML and data pipelines, with infrastructure spanning Kafka, Temporal, Protobuf, React, and distributed data stores
• Experience navigating ambiguity in a fast-moving organization — you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge

Why Stripe Identity

• The market is at an inflection point. The global identity verification market is growing at ~15% CAGR, from $12.5B in 2024 to $21.8B by 2028. Competitors have more features today — but none of them have Stripe's moat: payments signals, fraud network, consumer graph, and KYC data spanning the full financial ecosystem. We're building to win the next decade, not the last one.
• The problems are genuinely hard. Adversarial ML against deepfakes and face swaps. Distributed identity graph architecture with real-time freshness requirements. Progressive verification APIs that minimize friction without sacrificing fraud detection accuracy. These are unsolved problems — not just at Stripe, but in the industry.
• You'll work on systems that matter immediately. The verifications we run protect real users from real fraud. When our recall improves by 10 points, that's millions of dollars in prevented fraud losses for customers who rely on us. When our mobile SDK completion rate rises, thousands more legitimate users successfully onboard each month.
• The team is small enough that your judgment shapes the architecture. This isn't a role where you inherit decisions made five years ago. It's a role where the decisions you make in 2026 are the ones the team will build on through 2029.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Mosaic AI does so by producing novel science and putting it into production. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description

As a research engineer on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a research engineer on the Scaling Team at Databricks, you will: 

• Drive performance improvements through advanced optimization techniques including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization for training-specific patterns
• Design, implement, and optimize high-performance GPU kernels for training workloads (e.g., attention mechanisms, custom layers, gradient computation, activation functions) targeting NVIDIA architectures
• Design and implement distributed training frameworks for large language models, including parallelism strategies (data, tensor, pipeline, ZeRO-based) and optimized communication patterns for gradient synchronization and collective operations
• Profile, debug, and optimize end-to-end training workflows to identify and resolve performance bottlenecks, applying memory optimization techniques like activation checkpointing, gradient sharding, and mixed precision training.

What We Look for

• BS/MS/PhD in Computer Science or related field with hands-on experience writing and tuning CUDA kernels for ML training applications, or hands-on experience in distributed training frameworks (PyTorch DDP, DeepSpeed, Megatron-LM, FSDP) 
• Strong understanding of NVIDIA GPU architecture (memory hierarchy, tensor cores, warp scheduling, SM occupancy) and proficiency with CUDA debugging/profiling tools (Nsight, NVProf)
• Deep understanding of parallelism techniques and memory optimization strategies for large-scale model training, with proven ability to debug and optimize distributed workloads
• Strong software engineering skills in Python and PyTorch, with experience supporting production training workflows and knowledge of LLM training dynamics including hyperparameter tuning and optimization strategies.

Candidates in the listed location(s) are encouraged for this role:

• Remote - San Francisco

As a Strategic Hunter Digital Native Account Executive at Databricks, you are passionate about selling to high-growth, venture-backed companies. You will sell to the most technologically advanced companies in the world. You know how to compress decision cycles by penetrating accounts fast and demonstrating the value to the customer. You love understanding a product in-depth and are passionate about communicating its value to Customers. You will be over strategic accounts, and will be responsible for closing new customers and growing consumption. Along with the chance to close exciting deals, we also offer accelerators above 100% quota accomplishment. 

The impact you will have:

• You will have a direct influence on the data strategy of the most disruptive companies today
• You will communicate account strategy to Databricks Senior Leadership on a regular basis
• You will allocate Databricks resources to break into new accounts and grow existing accounts
• Meet with C-Level Executives to Practitioner level to understand how Databricks can make an impact on business outcomes
• Exceed activity, pipeline, and revenue targets
• You will use a creative, fail-fast approach to selling and creating value for customers
• You will build a plan for success internally at Databricks and externally with your accounts

What we look for:

• Passion for selling a highly technical product in the cloud
• 6+ years of experience with Open Source Technologies and build vs buy decision-making
• 6 -8 years of experience with Value Selling Methodologies
• A creative salesperson with a well-defined prospecting motion
• Sales experience within big data, Cloud, or SaaS sales
• Proven years of experience exceeding sales quotas
• Success closing new accounts 

The Global Data & Insights Team

Okta's Enterprise Data & Insights team powers the data infrastructure that drives decision-making across the company by building reliable pipelines, scalable data platforms, and production-grade data products. We partner closely with internal Data and Insights Analysts as well as external Okta Product teams to unlock business value through robust data architecture, efficient data movement, and the engineering foundations that make data trustworthy at scale.    

The Senior Analytics Engineer, Marketing Opportunity

We are seeking a Senior Analytics Engineer to serve as the technical architect of our marketing data engine. You will own our marketing attribution logic and end-to-end funnel performance data, evolving our current processes into an enterprise-grade ecosystem. Your mission is to uncover the high-fidelity signals that drive new customer acquisition and maximize expansion within our existing base. You’ll tackle a sophisticated roadmap of advanced analytics, transforming raw touchpoints into a trusted, scalable framework for growth.

This role sits at the intersection of business context and technical execution. You will design scalable data models, define consistent business logic, and help establish a strong semantic foundation that enables both human analytics and machine-driven intelligence.

You will partner closely with Marketing stakeholders, Data Analysts, Data Scientists, and Data Engineers to ensure data is accurate, consistent, and easy to consume; whether through dashboards, self-service exploration, or AI-powered workflows.

What you’ll be doing

Data Modeling & Semantics

• Design, build, and maintain scalable data models using dbt and Snowflake
• Define and standardize core Marketing metrics (e.g., pipeline, campaign performance, attribution, conversion rates)
• Establish consistent modeling patterns, naming conventions, and semantic clarity across datasets
• Contribute to a shared semantic layer that enables consistent reporting across channels and tools

AI-Ready Data & Snowflake Ecosystem

• Prepare high-quality, well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
• Enable data foundations that support LLM-powered use cases such as campaign insights, segmentation, and performance optimization
• Ensure data is context-rich, well-documented, and aligned with business meaning to improve AI accuracy and usability

Data Quality, Governance & Trust

• Implement robust testing, validation, and documentation practices in dbt
• Ensure consistency across dashboards and marketing tools through shared definitions and reusable models
• Apply data governance best practices, including access controls, lineage, and auditability
• Partner across teams to establish clear ownership of marketing data assets and definitions

Collaboration & Delivery

• Partner with Marketing, Customer First, and Analytics teams to translate business needs into scalable data solutions
• Support self-service analytics by building intuitive, reusable datasets across channels (e.g., digital, lifecycle, events)
• Contribute to scalable data workflows that balance immediate campaign needs with long-term maintainability
• Work within an agile environment, contributing to planning, prioritization, and continuous improvement

AI and Data Mindset

• Demonstrate an AI-first mindset, thinking beyond data models and dashboards to how data can power intelligent systems and decision-making
• Understand the importance of well-modeled, well-documented, and semantically clear data for AI and LLM-based use cases
• A level of comfort leveraging AI-assisted workflows to improve productivity, code quality, and consistency
• Curiosity for emerging capabilities in platforms like Snowflake Cortex and Snowflake Intelligence, and how they can be applied to Marketing analytics

What you’ll bring to the role

• 5–8+ years of experience in Analytics Engineering, Data Engineering, or similar roles
• Strong SQL skills and experience building analytics-ready data models
• Mentorship & Engineering Excellence: Mentorship, raising the technical bar, establishing organization-wide standards for dbt/SQL quality and CI/CD
• Hands-on experience with dbt and Snowflake or other ETL, Modeling and database platforms
• Solid understanding of data modeling principles, including dimensional modeling and semantic design
• Experience working with Marketing data (e.g., campaign data, web analytics, CRM, attribution models)
• Familiarity with tools such as Salesforce, Marketo, Google Analytics, or similar platforms
• Experience with data quality, testing, and documentation best practices
• Exposure to Python, R, or data processing frameworks (e.g., PySpark) is a plus
• Experience with BI tools such as Tableau or Looker
• Strong communication skills and ability to work across technical and business teams

What you can look forward to as an Okta employee!

• Amazing Benefits
• Making Social Impact
• Fostering Diversity, Equity, Inclusion and Belonging at Okta 
• Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/. 

Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.

#LI-HM2

#LI-Hybrid

P24712_3413650

P24715_3413656

We are seeking an accomplished and experienced Senior Software Engineer to join our dynamic team. In this role, you will be responsible for designing, developing, and maintaining our data infrastructure and services. You will collaborate with cross-functional teams, including data engineers, data scientists, software engineers, and product managers, to deliver modern and bleeding-edge solutions that drive business insights and innovation. This role reports to our Director of Engineering, Data Platform.

To learn more about Discord’s Data Platform, read our engineering blog — including how we built our modern data stack leveraging open-source tools!

This position is based in our San Francisco office.

What You'll Be Doing

• Define and execute the technical vision for Discord's data platform, enabling scalable, reliable, and performant data systems.
• Design, implement, and optimize data infrastructure to process and analyze petabytes of data across millions of users.
• Develop innovative data architectures to support analytics, machine learning, and operational insights.
• Build monitoring, logging, and alerting systems to ensure the health and performance of data services.
• Partner with data scientists, data engineers, product managers, and leadership to align technical solutions with business goals.
• Promote and drive best practices in data governance, security, and compliance across the organization.
• Provide technical leadership, mentor junior engineers, and foster a culture of excellence and continuous improvement.
• Stay up-to-date with industry trends and emerging technologies in data platform.

What You Should Have

• 5+ years of experience in software engineering with a focus on large-scale distributed systems or data infrastructure.
• Expertise in building and maintaining scalable data platforms, including data ingestion pipelines, stream processing, and batch processing systems.
• Proficiency in programming languages such as Python, Java, Rust, or similar.
• Proficiency with open source data projects and experience working with open source communities.
• Hands-on experience with modern data technologies such as Kafka, Spark, Flink, Airflow/Dagster, or similar.
• Deep understanding of database systems (e.g., SQL, NoSQL, columnar storage) and data modeling principles.
• Strong knowledge of cloud infrastructure (AWS, GCP, or Azure), containerization tools (Docker, Kubernetes), and microservices architecture.
• Excellent communication skills with a demonstrated ability to collaborate and influence across teams and levels.
• Proven ability to thrive in a fast-paced environment.

Bonus Points

• A strong passion for Discord and gaming.
• Open source contributions to data-related projects.

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $196,000 to $245,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Every day, hundreds of millions of gamers gather on Discord to hang out, strategize their next raid, celebrate tournament victories, and build communities around the games they love. Behind every voice channel, every streamer Go Live, every Quest completed, there's data, petabytes of it, telling the story of how people connect through gaming.

We're looking for someone who gets excited about building data infrastructure at massive scale and cares deeply about the gaming communities we serve. Someone with passion for building lovable products for Discord users and Discord engineers. We’re building the next generation Data Platform that powers decisions for one of the most vibrant platforms in the world.

If you're the kind of Software Engineer who lights up when talking about distributed systems, cares deeply about user privacy, grounding decisions in data, and wants your work to directly impact millions of gamers worldwide, we want to talk to you.

To learn more about Discord’s Data Platform, read our engineering blog, including how we built our modern data stack leveraging open-source tools!

What You'll Be Doing

• Build and maintain data infrastructure processing petabytes of data across millions of users
• Write clean, well-tested code for data ingestion, transformation, and serving systems
• Own projects end-to-end with guidance from senior engineers. From design through deployment and production support
• Collaborate with data scientists, engineers, and product teams to deliver solutions that power Discord's insights

What You Should Have

• 3+ years of software engineering experience with strong programming skills in Python, Java, Rust, Go, or similar
• Solid CS fundamentals and demonstrated ability to quickly learn new technologies and ramp up on unfamiliar systems
• Proven debugging skills and growth mindset. You seek feedback and continuously improve
• Strong collaboration skills and ability to clearly explain technical concepts to different audiences

Bonus Points

• Passion for Discord and gaming
• Experience with the data ecosystem: pipelines, ETL, modeling, or warehousing (Kafka, Spark, Flink, Airflow, Dagster, SQL, etc.)
• Cloud infrastructure knowledge (AWS, GCP, Azure) or containerization (Docker, Kubernetes)

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $160,000 to $180,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Every day, hundreds of millions of gamers gather on Discord to hang out, strategize their next raid, celebrate tournament victories, and build communities around the games they love. Behind every voice channel, every streamer Go Live, every Quest completed, there's data, petabytes of it, telling the story of how people connect through gaming.

We're looking for an Engineering Manager who gets excited about building world-class teams and data infrastructure at massive scale. Someone who cares deeply about the communities we serve and is passionate about developing engineers who build lovable products for Discord users and Discord engineers alike. You'll lead a team building the next generation Data Platform that powers decisions for one of the most vibrant platforms in the world.

If you're the kind of leader who lights up when coaching engineers, making tough technical decisions, and wants your team's work to directly impact millions worldwide, we want to talk to you.

To learn more about Discord's Data Platform, read our engineering blog, including how we built our modern data stack leveraging open-source tools!

This position is based in our San Francisco office.

What You'll Be Doing

• Lead and grow one or more teams of engineers building data infrastructure that processes petabytes of data across millions of users
• Partner with People and Technical leaders to set technical direction and define the roadmap for your team(s)
• Drive a culture of 80/20 thinking, quality-centered execution, and timely decision-making to ensure your team consistently ships high-impact results
• Build strong relationships with cross-functional partners to align technical solutions with business goals
• Help your team navigate ambiguity while maintaining momentum toward business outcomes

What you should have

• 2+ years of engineering leadership and 7+ years of software engineering experience with expertise in large-scale distributed systems or data infrastructure
• Strong people management skills including hiring, performance management, coaching, and conflict resolution
• Demonstrated ability to set the pace for a team, remove blockers, and drive projects to completion
• Excellent communication skills with ability to foster clear, effective dialogue across all levels and audiences
• Proven track record independently making sound technical decisions through ambiguity in partnership with cross-functional stakeholders
• Experience with the data ecosystem: pipelines, ETL, modeling, and/or warehousing (Kafka, Spark, Flink, Airflow, Dagster, SQL, etc.)
• Cloud infrastructure knowledge (AWS, GCP, Azure) or containerization (Docker, Kubernetes)

Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available.

The US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

SLSQ227R297

As a Startup Account Executive at Databricks, you get to work with some of the most exciting, disruptive companies using data to change the world. You are creative and self-motivated with experience running both transactional and strategic sales processes. You know how to sell innovation and change through customer vision expansion and can guide deals forward to compress decision cycles. You love understanding a product in-depth and are passionate about communicating its value to customers and partners. Along with the chance to close exciting deals, we also offer accelerators above 100% quota accomplishment. You will report to a regional sales manager.

The impact you will have:

• Build a territory plan within 30 days with a clear account prioritization strategy.
• Align existing customers with the Lakehouse vision and ecosystem.
• Be able to range from faster transactions to large strategic deals.
• Maintain clear Salesforce and Clari hygiene, including use case, MEDDPICC, revenue forecasts, and account notes.
• Lead with a customer-first mindset and focus on business value

What we look for:

• 2+ years of closing sales experience
• Prior experience in big data, Cloud, or SaaS sales
• Be able to quickly learn new technologies and value propositions
• Experience exceeding sales KPIs and quotas

Position Overview

The day-to-day responsibilities will include:

• Owning the financial systems and data strategy, defining and then executing on a 12–24 month roadmap in partnership with Finance and Executive leadership

• Owning end-to-end data architecture, including data lake and data warehouse infrastructure (Azure/Fabric), API and ETL/ELT integrations across source systems (ERP, EPM, HRIS), and BI reporting layers (Power BI)
• Developing and maintaining scalable BI and analytics frameworks that translate complex financial data into clear, actionable business insights
• Establishing and enforcing data governance standards, including master data management (MDM), metadata governance, and data quality frameworks across Finance
• Identifying and implementing AI-driven automation opportunities to transform Finance operations, reporting, and insight generation
• Leading large-scale system initiatives from requirements gathering through delivery, managing timelines, stakeholders, and cross-functional dependencies, including managing external technical consultant relationships
• Flexing between strategic leadership and hands-on contributor work — directing a small group of internal and external resources while personally contributing to writing code, building pipelines, designing data models and system oversight
• Driving technology adoption and change management across our Holding Company and support industry vertical teams in system implementation and adoption
• Translating business requirements into scalable technical solutions, acting as the bridge between Finance leadership and technical teams
• Partnering closely with Finance, IT resources and cross-functional stakeholders to align systems strategy with business priorities

Qualifications

• 10+ years of progressive experience in Data Architecture, Finance/Business Systems, or Business Intelligence, ideally within high-growth and/or high-M&A environments
• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, Business, or a related field
• Experience owning end-to-end data architecture including data lake or warehouse infrastructure, ETL/ELT integrations, and BI reporting layers; proficiency in SQL required, Microsoft stack a strong plus
• Experience with financial systems at scale including ERP, EPM, and Business Intelligence platforms; familiarity with OneStream and Business Central a plus
• Deep understanding of data engineering best practices, warehousing/lakehouse architecture, MDM, and metadata governance
• Demonstrated success delivering large-scale system initiatives, preferably within Finance
• Strong project management and cross-functional collaboration skills

Personal Attributes

• Strategic thinker and hands-on builder — equally comfortable driving vision and rolling up your sleeves to execute
• Excellent communicator with the ability to translate complex technical concepts for Finance stakeholders and vice versa
• Highly collaborative with strong cross-functional relationship and project management skills
• Self-motivated and comfortable operating with autonomy in a lean team environment
• Excited about applying emerging AI and automation tools to modernize how Finance operates
• Interested in a long-term career at a company building something to last for decades
• High integrity, low ego — Evergreen hires on potential and trajectory as much as technical credentials

Compensation

A competitive compensation package including a base salary range of $185,000–$210,000, annual performance-based bonus, Profit Interest Units (equity-based comp) and an excellent benefits package is available.

Location

San Francisco, CA preferred. Hybrid or remote candidates with significant relevant experience will be considered.

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale Generative AI experiences — including Pinterest Assistant and Canvas — ensuring these products are safe, fair, and trustworthy is paramount. We are looking for a Senior Data Scientist to help lead Pinterest's responsible AI mandate within the Advanced Technology Group (ATG). In this role, you will design and build the data science foundations for automated adversarial testing of our GenAI products — developing attack strategies, evaluation frameworks, and harm-detection methodologies that operate at scale. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Trust & Safety specialists, Policy teams, and Product Managers. You are expected to develop a deep understanding of generative AI vulnerabilities, and generate insights and robust methodologies to proactively surface and mitigate risks. The results of your work will directly influence product safety, policy compliance, and user trust across Pinterest.

What you'll do

• Design and develop automated adversarial testing methodologies — including single-turn, multi-turn, and multimodal attack strategies — to proactively identify vulnerabilities in Pinterest's Generative AI products.
• Build and calibrate hybrid evaluation pipelines combining LLM-based judges, classifiers, and rule-based systems to accurately detect safety violations, policy breaches, bias, and representational harms.
• Develop and operationalize harm taxonomies grounded in industry standards and Pinterest's Responsible AI and Trust & Safety threat models.
• Design adaptive refinement loops that learn from attack outcomes (near-misses, partial failures) to iteratively surface deeper and previously unknown vulnerabilities.
• Bring scientific rigor and statistical methods to the evaluation of AI safety — including benchmark dataset construction, evaluation calibration, and success-metric definition (vulnerability severity, coverage breadth, pre-launch risk reduction).
• Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML engineers, Trust & Safety specialists, policy teams, product managers, and legal partners to ensure safe product launches.
• Relentlessly focus on impact, whether through influencing product safety strategy, advancing responsible AI metrics, or improving critical evaluation processes.
• Mentor and up-level junior data scientists and cross-functional partners on adversarial evaluation, responsible AI methodologies, and safety-aware data science practices.

What we're looking for

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Strong interest and hands-on experience in one or more of: AI safety, adversarial machine learning, red teaming, responsible AI, or trust & safety.
• Deep familiarity with large language models (LLMs), generative AI systems, and their failure modes — including prompt injection, jailbreaks, bias, and safety violations.
• Experience designing and calibrating evaluation frameworks for AI systems — including LLM-as-judge, classifier-based evaluation, and benchmark dataset construction.
• Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines and large-scale experimentation.
• Familiarity with AI safety taxonomies and frameworks (e.g., OWASP LLM Top 10, MITRE ATLAS) is strongly preferred.
• Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership.
• Excellent written and verbal communication skills, with the ability to explain complex technical findings to both technical and non-technical partners.
• A team player eager to partner across Responsible AI, Trust & Safety, Product, Engineering, Policy, and Legal to turn safety insights into action.

This position is not eligible for relocation assistance.

#LI-NM4 

Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale and unify our foundational AI models across every recommendation surface, rigorously measuring the system-level impact of these advances is essential to our ability to ship with confidence and compound gains over time.

We are looking for a Senior Data Scientist to serve as the measurement backbone for Pinterest's foundational model initiatives within the Advanced Technology Group (ATG). In this role, you will design the evaluation frameworks, experimentation strategies, and system-level metrics that quantify how improvements to our largest and most complex models translate into real user and business outcomes. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Applied Scientists, Product Managers, and ML Platform engineers. 

You are expected to develop a deep understanding of Pinterest's recommendation ecosystem, from representation learning to retrieval, ranking, reinforcement learning, and beyond, and bring the analytical rigor necessary to decompose, attribute, and communicate the impact of foundational model changes across this interconnected system. The results of your work will directly influence model investment decisions, launch criteria, and the pace of innovation across ATG and Pinterest.

What You'll Do

• Design and execute system-level measurement frameworks for foundational model improvements spanning offline evaluation benchmarks, online A/B experiments, and longitudinal impact tracking across surfaces.
• Define, and own the success metrics that quantify foundational model value.
• Build causal inference methodologies to isolate the incremental impact of individual model components within a complex, multi-model production system where changes co-occur and interact.
• Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML Engineers, Applied Scientists, Homefeed and Surface teams to ensure measurement rigor is embedded in every model launch.
• Relentlessly focus on impact, whether through sharpening investment decisions with data, raising the bar for launch criteria, accelerating experimentation velocity, or surfacing hidden inefficiencies in the model ecosystem.

What We're Looking For

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Strong interest and hands-on experience in one or more of: ML system evaluation, recommender system measurement, A/B experimentation at scale, causal inference
• Deep familiarity with large-scale recommendation or ranking systems and their evaluation including an understanding of how representation learning, retrieval, ranking, and re-ranking stages interact and compound in production.
• Experience designing and executing A/B experiments for complex ML systems,  including multi-surface holdouts, metric decomposition, long-run effect estimation, and interference/spillover mitigation.
• Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines, feature stores, and large-scale experimentation platforms.
• Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership in a fast-moving research-to-production environment.
• Excellent written and verbal communication skills, with the ability to translate complex system-level findings into clear narratives for technical and non-technical partners including leadership-level investment recommendations.
• A team player eager to partner across teams to turn measurement insights into better models and faster launches.

This position is not eligible for relocation assistance.

#LI-NM4

As a Sr. Solutions Architect at Databricks within the Field Engineering org, you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge, and can drive complex technology discussions that express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams, with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customers' needs, build valuable customer engagements, and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in and promote Databricks-inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 8+ years in a customer-facing pre-sales or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides.

Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities.

This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.

This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately.

We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions.

Responsibilities:

• Define and drive the long-term technical roadmap for claims management systems, aligning priorities with Product, Claim Operations, Data Science, and other stakeholders.
• Provide architectural leadership, make informed design tradeoffs, and guide strategic decisions across multiple engineering teams.
• Understand claim handling workflows, identify bottlenecks and multiply their productivity by driving platform innovations and resolving pain points with AI automation solutions
• Deliver scalable, reliable, high quality and well-tested solutions and code.
• Collaborate closely with Lyft internal teams and external insurance partners to ensure technical alignment and scalable integrations.
• Lead code reviews, design reviews, production on-call support and incident triaging process.
• Invest in the engineering community through knowledge sharing via brown bags, tech talks, and suggesting improvements to team processes and engineering practices.

Experience:

• B.S., M.S. in Computer Science or related technical field or relevant work experience.
• 6+ years of professional experience building scalable distributed systems with high availability, observability and reliability requirements.
• Proven ability to build end-to-end products and platforms, collaborating effectively with various stakeholders e.g. Backend, Frontend, Data Engineering, Data Science, Claim Operations, and Product teams.
• Strong ability to reason about tradeoffs in system design, architecture, domain modeling, and operational cost.
• Experience driving AI adoption or automation initiatives to improve operational efficiency.
• Proficiency in Python. Knowledge of React/Next.js and data analysis is a plus.
• Experience with data processing frameworks and tools like Spark, Kafka, Airflow and cloud provisioning environments etc.
• Strong oral and written interpersonal skills.
• Prior experience in insurance, claims management, workflow orchestration or external vendors is a strong plus.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Seattle area is $136,160 - $170,200 , not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides.

Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities.

This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.

This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately.

We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions.

Responsibilities:

• Define and drive the long-term technical roadmap for claims management systems, aligning priorities with Product, Claim Operations, Data Science, and other stakeholders.
• Provide architectural leadership, make informed design tradeoffs, and guide strategic decisions across multiple engineering teams.
• Understand claim handling workflows, identify bottlenecks and multiply their productivity by driving platform innovations and resolving pain points with AI automation solutions
• Deliver scalable, reliable, high quality and well-tested solutions and code.
• Collaborate closely with Lyft internal teams and external insurance partners to ensure technical alignment and scalable integrations.
• Lead code reviews, design reviews, production on-call support and incident triaging process.
• Invest in the engineering community through knowledge sharing via brown bags, tech talks, and suggesting improvements to team processes and engineering practices.

Experience:

• B.S., M.S. in Computer Science or related technical field or relevant work experience.
• 6+ years of professional experience building scalable distributed systems with high availability, observability and reliability requirements.
• Proven ability to build end-to-end products and platforms, collaborating effectively with various stakeholders e.g. Backend, Frontend, Data Engineering, Data Science, Claim Operations, and Product teams.
• Strong ability to reason about tradeoffs in system design, architecture, domain modeling, and operational cost.
• Experience driving AI adoption or automation initiatives to improve operational efficiency.
• Proficiency in Python. Knowledge of React/Next.js and data analysis is a plus.
• Experience with data processing frameworks and tools like Spark, Kafka, Airflow and cloud provisioning environments etc.
• Strong oral and written interpersonal skills.
• Prior experience in insurance, claims management, workflow orchestration or external vendors is a strong plus.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $148,000 - $185,000 , not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. 

Lyft Ads is one of Lyft’s newest and fastest-growing businesses, focused on building the world’s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey—before, during, and after a ride—by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.

We are seeking an Algorithms Scientist  to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You’ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.

This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders—pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.

Responsibilities:

• Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
• Own the end-to-end lifecycle of modeling projects — including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
• Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
• Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
• Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
• Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
• Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
• Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
• Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement — and proactively identifying opportunities to apply them.
• Contribute to Lyft Ads’ modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.

Experience:

• Master’s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
• 3–5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains.
  Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
• Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
• Practical experience building and evaluating:
• Ranking and relevance models
• Optimization or pacing algorithms
• Predictive models for CTR, CVR, or user response
• Causal or experimentation-based measurement methods
• Understanding of online/offline evaluation techniques, including:
• Offline metrics (AUC, NDCG, MRR, calibration)
• A/B testing methodologies
• Bias correction and counterfactual estimation
• Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
• Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
• Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
• Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process. 

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Our transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, with public transportation, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes. We achieve this by processing millions of rides, taking into account the latest traffic information and analyzing the preferences of drivers.

To strengthen our efforts, we are hiring a Data Science Manager who will lead data scientists and data analysts helping us to make data driven decisions. Data Science & Analytics is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, measuring the impact of new features and monitoring our solutions in close collaboration with many engineering teams. You will help us solve some of the most impactful problems in mapping, including:

• How do we provide the best routes and most accurate ETAs?
• How is the routing experience for our drivers? Are we providing the fastest, most economic and most comfortable routes to our customers?
• How do we benchmark and measure the success of map services?

Our technology stack is based on the latest technologies such as AWS, Kubernetes and Apache Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers.

Responsibilities

• Lead and grow a high-performing team of data scientists with diverse backgrounds, including optimization, experimentation, machine learning and causal inference  
• Define and drive the data science vision, strategy, and roadmap, aligning with overall business and product objectives to improve market competitiveness and user experience 
• Provide strong technical guidance and coaching to the team on complex data science problems related to real-time decision-making and resource allocation
• Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate data insights into decisions and action
• Lead deep-dive analyses into large-scale datasets to identify opportunities for improving navigation efficiency, mapping accuracy, and overall product health
• Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies
• Mentor and guide the professional and technical development of your team members. Help develop their careers, and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals
• Maintain a balance between building sustainable, high-impact projects and shipping things quickly
• Work closely with the Lyft recruiting team to hire high potential candidates from diverse backgrounds

Experiences

• Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience
• 5+ years of hands-on technical experience in experimentation, causal inference, or data science, preferably with applications in real-time systems or marketplace dynamics
• 2+ years of management experience building, leading, and mentoring data science teams
• Strong expertise in statistics, experimental design, and causal inference, including A/B testing, multivariate testing, and incremental lift measurement
• Strong data storytelling and influence skills, with experience presenting insights and recommendations to senior leaders
• Experience launching and monitoring consumer facing products and iterating through data-driven experimentation and metrics analysis
• Experience guiding teams through ambiguous and complex technical challenges to deliver impactful solutions
• Hands-on experience building or operationalizing machine learning models (e.g., propensity, segmentation, churn, personalization) in partnership with engineering or platform teams (nice to have)
• Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences
• Hands-on experience with large-scale data processing (e.g., Spark, SQL) and machine learning frameworks is highly desirable
• Prior experience in mapping domain will be a plus

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $176,000 - $220,000 not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

We're hiring a RevOps Manager to own variable pay and quota-setting across our GTM organization, automate the majority of this cycle, and support/automate other RevOps functions - from analytics and forecasting to process improvement and tooling. 

Who You Are

Required:

• 3+ years in revenue operations, sales operations, sales compensation,  finance, or a closely adjacent function, with hands-on ownership of sales comp work
• Daily working fluency with AI tools (Claude, Cursor, ChatGPT, n8n, Replit, or similar)
• At least one shipped agentic workflow, internal tool, or skill that took real work off your plate or someone else's, with specifics on what it does and what it saves
• Comfort directing AI to write SQL and validate outputs against source data. Independent SQL fluency is a plus
• Cross-functional working style with Finance, Legal, and Sales leadership
• Judgment under pressure during compressed close windows

Nice to Have:

• Experience designing or improving quota-setting methodologies
• Audit support experience, with a habit of flagging issues in comp data, plan mechanics, or payouts before they escalate
• Familiarity with usage-based comp plans and the attribution challenges they create
• Experience with commission management platforms 
• Exposure to Salesforce data model, dbt, and BI tooling (Mode, Looker)
• Experience leading or co-leading an annual comp plan redesign

What You'll Do

AI & Agentic Automation

• Translate the existing SQL-and-spreadsheets comp process into agents, skills, and workflows so each cycle takes less manual work than the last.
• Examples we'd want to see from you in your first year: a payout-audit agent that pre-flags discrepancies against source data, a methodology skill that drafts and pressure-tests plan changes, an n8n workflow that routes rep escalations to the right reviewer, a Replit app that lets sales managers self-serve crediting questions, an agent that builds rep statements and explains the math.
• Tools we use today: Claude, Cursor, ChatGPT, n8n, Replit. You don't need a software engineering background. You do need a track record of shipping automations that took real work off someone's plate.

Comp Operations

• Run monthly and quarterly comp cycles for all GTM teams. Resolve discrepancies, reconcile with Finance and Payroll, run close QA. On-time cycles, errors caught before they escalate.
• Own the quarterly target-setting pipeline. Collect inputs, generate targets, drive approvals with the VP of Sales and CFO, finalize and distribute target packages. Partner with analytics on dashboards that make targets transparent to managers and reps.
• Handle new-hire guarantees, crediting exceptions, split credit decisions, LOA and territory moves, SPIFF design and payout, and manager-level comp questions. Sales and Finance judge the function on these calls.

Forecasting & Pipeline Analytics

• Own weekly and monthly forecast roll-ups across our GTM segments. Pressure-test rep and manager calls against pipeline data. Surface gaps to the VP of Sales and CFO before they show up in QBRs.
• Build and maintain pipeline dashboards covering coverage, stage conversion, velocity, and aging. Tie metrics back to compensation so managers see the full picture.
• Partner with FP&A on bookings forecasts, attainment modeling, and capacity planning for the next fiscal year.

Plan Design & Methodology

• Lead the annual comp planning cycle. Frame the plan, construct it across teams, run review and approval cycles with the CFO, CEO, VP of Sales, and other leadership. Manage Legal review and acknowledgment. Run the rollout. Own the retrospective.
• Bring a point of view on how plans are designed, how targets are set, and how the process runs. Identify changes that improve fairness or speed, then ship them in the next cycle.

What Success Looks Like

• First 90 days: Complete monthly comp cycles, partner on a quarterly cycle and one target-setting cycle. Know every plan and the people who own them. Ship your first agent or workflow that takes a piece of the cycle off the team's plate.
• First 6 months: Own a quarter-close from source data through payout. Propose specific changes to the operating process, backed by hours saved from the automations you've shipped. Take on forecasting & pipeline analytics work and partner on your first forecasting cycles
• First 12 months: Lead the annual plan design & capacity planning process. Show a portfolio of automations that save time in every subsequent cycle. GTM and Finance leaders bring comp questions to you first.

For CA-based applicants:

The base salary for this position is $130,000 - $170,000.

This position is eligible for equity in the form of stock options.

This position is eligible for Instawork benefits, including:

• Medical, dental, and vision plans with coverage beginning on the date of hire
• Flexible paid time off
• At least 8 paid company holidays annually
• Phone stipend
• Commuter stipend
• Supplemental pay on qualified leaves
• Employee health savings accounts (HSA) contribution
• Flexible spending plans
• 401K plan
• Perkspot - discount program through Lumity

A variety of factors are considered when determining someone's compensation, including a candidate's professional background, experience, and location. Final offer amounts may vary from the amounts listed above.

We are building an AI-native Data Cloud and need a VP of Engineering who owns architecture, execution, and business outcomes end-to-end. The buck stops with this role for platform reliability, developer experience, and Data Cloud adoption.

DigitalOcean’s Data Cloud will power AI applications end-to-end—from data ingestion to real-time inference—enabling developers to build production-grade RAG systems, AI agents, and analytics workflows on a single, integrated platform. This role is responsible for delivering that platform by leveraging and extending DigitalOcean’s existing infrastructure, PaaS, and AI capabilities.

This is not a traditional data platform role. You will define and execute the strategy to move DigitalOcean up the stack—from infrastructure provider to a differentiated AI application and inference platform. Success will be measured through roadmap velocity, system reliability, developer adoption, and measurable business impact.

We are looking for a leader who translates strategy into shipped systems, with clear accountability for outcomes.

What You’ll Do:

Data Cloud Platform

Architecture and delivery of a unified platform spanning:

• Ingestion (connectors, CDC, streaming)
• Storage (object, OLAP, vector, graph)
• Processing (ELT pipelines, real-time and batch)
• Query & analytics (SQL, hybrid search, RAG)
• Governance (catalog, lineage, versioning, access control)

AI-Native Capabilities

• Knowledgebase-as-a-Service (RAG pipelines)
• Vector and hybrid retrieval systems
• Feature and embedding pipelines
• Real-time inference data paths

Product & Execution

• Deliver GA-grade services with strong SLAs, cost efficiency, and simplicity
• Drive roadmap aligned to Digital Native Enterprise (DNE) customers
• Establish and manage clear metrics: adoption, retention, ARPU, performance, reliability

Organizational Leadership

• Build and scale a high-performing global organization (US and India)
• Implement single-threaded ownership (STO) across services
• Partner deeply with Product, GTM, and Platform Engineering

What Success Looks Like (12 months)

• Launch a cohesive Data Cloud platform—not a collection of fragmented services
• Achieve meaningful adoption across AI-native workloads (RAG, inference, analytics)
• Reduce developer time-to-value from weeks to hours
• Establish clear differentiation versus hyperscalers on simplicity and cost

What You’ll Bring:

• Proven track record of building and operating cloud-scale data platforms (OLAP, lakehouse, streaming, or ML systems), with strong architectural judgment across storage, processing, and query layers
• Experience integrating open-source ecosystems (e.g., Spark, Airflow, dbt) into managed cloud services at scale
• Experience with AI/ML data pipelines (feature stores, embeddings, RAG)
• Demonstrated ability to operate in ambiguity, make high-quality decisions with incomplete data, and drive multi-quarter execution with measurable outcomes
• Proven experience scaling engineering organizations and delivering under real-world constraints

Critical requirement:
You have personally driven complex distributed systems from concept to production—not just managed teams that did.

Why This Role Matters

The Data Cloud is the control plane for AI applications. If DigitalOcean gets this right, it becomes the platform where developers build and scale intelligent applications—not just where infrastructure runs. If not, it remains an interchangeable infrastructure.

Compensation Range: 

• $279,200.00 - $349,000

*This is a remote role

JR: 2026-7683

#LI-Remote

Instawork is a leading tech company building the most trusted labor marketplace for businesses and professionals. We're looking for a self-motivated, intellectually curious, and pragmatic Litigation & Employment Counsel to join our lean, high-impact Legal team. You should be comfortable using AI tools to drive efficiency in your legal work and eager to help build scalable processes as the company grows.

Who You Are:

• JD and California bar admission in good standing (or barred in NY or IL and qualified for and willing to maintain Registered In-House Counsel status with California State Bar)
• 5+ years of legal experience in a law firm and/or in-house
• Experience in the technology, gig economy, or marketplace industry strongly preferred
• Mature judgment and decision-making skills
• Ability to distill complex legal risks and competing priorities into clear, actionable guidance for business partners
• Comfort navigating ambiguity and reprioritizing quickly in a fast-paced environment
• Team mentality and recognition that no task is too small
• Proven ability to manage a high volume of matters with overlapping deadlines while maintaining quality and composure
• Excellent verbal and written communication skills
• Sense of perspective…..and humor

What You'll Do:

• Handle a wide variety of litigation and pre-litigation matters in state and federal courts and administrative forums, especially matters involving worker classification and employment-related claims
• Work closely with Instawork's Trust and Safety team, insurance brokers, and insurance carriers; conduct and supervise investigations related to employment matters, on-platform incidents, or policy violations
• Create and implement scalable processes for the legal team, including identifying opportunities for automation and process innovation
• Leverage AI and other technology tools to increase efficiency, improve work product, and support the team's continuous improvement goals
• Manage all aspects of the relationship with relevant outside counsel, including staffing, strategy, budgets, discovery, and work product
• Partner with Human Resources and business partners to evaluate legal risks and provide subject matter expertise on a broad range of employment issues, including wage and hour, recruiting and hiring, training, employee performance management, leaves of absence, disability accommodations, and HR best practices
• Develop and deliver training for HR and business teams on employment law topics, company policies, and risk mitigation.
• Help prepare for and mitigate exposure that may create litigation risk in the future
• Other projects based on the needs of a quickly growing company

Nice to Have:

• Prior in-house counsel experience
• Experience with workers' compensation and insurance coverage matters
• Proficiency with AI-assisted legal research, drafting, or workflow tools
• Continuous learning mindset: you bring strong skills and experience to the table and are open to new approaches, tools, and ways of working

For CA-based applicants:

• The base salary for this position is $175,000 - $225,000
• This position is eligible for equity in the form of stock options
• This position is eligible for Instawork benefits, including:
• A variety of medical, dental, and vision plans with coverage beginning on the date of hire
• Flexible paid time off
• At least 8 paid company holidays annually
• Phone stipend
• Commuter stipend
• Supplemental pay on qualified leaves
• Employee health savings accounts (HSA) contribution
• Flexible spending plans
• 401K plan
• Perkspot - discount program through Lumity

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico's highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

Calico seeks a Senior Machine Learning Research Engineer to join the team building the computational engine that closes the design-test-learn cycle in molecular design and scales the ML infrastructure across the company.

Working closely with a biology-fluent group of researchers and engineers, you will build ML platforms to accelerate their research, translate advanced ML methods into scalable code, and iteratively refine these tools as they apply them to real-world drug discovery problems.

If you are passionate about building high-impact ML systems, thrive in ambiguity, and are excited to move fluidly between optimizing data pipelines and deploying generative models, this is the role for you.

Please note: No biology or life sciences background is required for this role.

Key Responsibilities:

You will own the end-to-end flow from data ingestion to model deployment. Because of the flexible nature of this role, your responsibilities will adapt to the team's most pressing needs, shifting between two core areas:

ML Platform

• Build and scale core components of our ML Data, Eval, and Serving platforms, including APIs, libraries, and datastores
• Optimize the training and serving stack to maximize accelerator utilization at scale
• Automate end-to-end ML workflows between computational models and the wet lab, ensuring full reproducibility and lineage tracking

Generative Modeling & Search

• Optimize and scale our molecular search methods
• Identify opportunities to accelerate model research workflows and ship tools quickly
• Prototype new modeling ideas with researchers and deploy them into the drug discovery pipeline

Position Requirements:

• A strong intellectual curiosity for life sciences
• 5+ years of relevant ML software engineering experience in industry or academia
• Strong software engineering skills, particularly building model training, serving, or evaluation platforms
• Deep expertise in Python and JAX or PyTorch
• Must be willing to work onsite at least four days a week

Nice to Have:

• Large-scale data processing experience (e.g., Ray, Spark, BigQuery) and high-throughput data loading
• Familiarity with common biological datasets and formats (e.g., BAM, TIFF, Zarr, AnnData)
• Hands-on experience with advanced ML architectures (e.g., transformers, diffusion networks), search and optimization methods (e.g., active learning, Bayesian optimization, RL), or large-scale biomolecular models (e.g., AlphaFold)
• Advanced degree in computer science or a relevant field
• Contributions to open-source ML projects or relevant academic publications

The estimated base salary range for this role is $209,000 - $233,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Instawork is seeking a General Manager, Data Centers, to accelerate and scale our rapidly growing presence in the booming data center industry. Working closely with Instawork’s leadership team, this is a high-octane opportunity to drive strategy, capture market share, and optimize execution in one of the world's fastest-growing sectors.

You will be tasked with scaling the connection between our 10M+ flexible workers ("Pros") and the massive, continuous labor demands of data center builders, general contractors, operators, and hyperscalers. Your goal: parachute into high-impact expansion initiatives, optimize our go-to-market strategy, supercharge our supply and demand engines, and do absolutely whatever it takes to accelerate the marketplace flywheel in critical data center hubs.

What You’ll Do

• Scale the Playbook: Take our data center vertical from 1 to 10. You will drive operational excellence—whether that means streamlining complex site-access and safety protocols, standardizing onboarding for massive construction build-outs and hardware deployments, or expanding our footprint in key markets—until the vertical is a massive, self-sustaining engine.
• Strategic Execution & Partnership Expansion: Refine and implement Instawork’s growth strategy for the data center space. Cultivate, grow, and own relationships with top-tier general contractors, data center operators, colocation providers, and infrastructure tech giants, turning initial pilots into enterprise-wide deployments.
• Market & Data Needs Analysis: Deeply understand the unique labor, compliance, and safety requirements of both active construction sites and live data center environments. Leverage data to anticipate partner pain points and ensure Instawork’s tech and operations can seamlessly support their massive, fluctuating workforce needs throughout the entire facility lifecycle.
• Cross-Functional Leadership: Collaborate closely with Sales, Marketing, Product, and Operations to move aggressively and iterate on the fly. You will turn operational friction into scalable, automated processes and act as an internal driver of cross-functional alignment to unblock growth.
• Thought Leadership & Evangelism: Represent Instawork externally as a thought leader in the data center workforce space. Regularly present progress, growth metrics, and strategic recommendations to Instawork's executive leadership, shaping the company’s long-term vision for infrastructure support.
• Own the Road: Expect extensive travel to major data center markets. Your office is wherever the next massive launch, key partner expansion, or operational optimization takes you.

Who You Are

• Domain Expert & Relationship Builder: 4+ years of experience in commercial construction (specifically mission-critical or data center builds), data center operations, infrastructure scaling, or management consulting within the tech/infrastructure space. You understand the full lifecycle of a data center, from ground-breaking and construction to commissioning and ongoing facilities management.
• Scaling Mindset & Extreme Bias for Action: You don't wait for permission or perfect data; you deliver results. You thrive in a high-pressure environment where the pace is fast, expectations are massive, and you know how to build systems that sustain hyper-growth.
• Strategic & Curious: You think big-picture while staying fiercely grounded in data and execution. You are deeply comfortable with fast iteration, navigating complex enterprise requirements, and solving unstructured problems in a rapidly evolving industry.
• Multi-disciplinary Executor: You have a proven track record of managing high-growth expansion, optimizing complex operations, and turning early momentum into sustainable, long-term market dominance. You are highly skilled at working across multiple functions to deliver results.

For CA-based applicants:

• The base salary for this position is $160,000 - $200,000
• This position is eligible for equity in the form of stock options
• This position is eligible for Instawork benefits, including:
• A variety of medical, dental, and vision plans with coverage beginning on the date of hire
• Flexible paid time off
• At least 8 paid company holidays annually
• Phone stipend
• Commuter stipend
• Supplemental pay on qualified leaves
• Employee health savings accounts (HSA) contribution
• Flexible spending plans
• 401K plan
• Perkspot - discount program through Lumity

A variety of factors are considered when determining someone’s compensation, including a candidate’s professional background, experience, and location.  Final offer amounts may vary from the amounts listed above.

Senior Customer Engineer

The Team + The Role

Pendo’s Customer Engineering team is the technical backbone of the pre- and post-sales customer motion. The team brings together work that has historically sat across Customer Success, Technical Account Management, and Solutions Engineering into one full-lifecycle technical owner. Customer Engineering helps customers connect technical execution to business outcomes and realize the value of their investment in Pendo.

As a Senior Customer Engineer, you own strategic and complex Enterprise accounts across acquisition, implementation, adoption, expansion, and escalation. You lead technical strategy for complex deployments, resolve ambiguous customer challenges, and partner closely with account teams to drive retention, expansion, and customer value. Your impact extends beyond your own accounts through playbooks, coaching, repeatable fixes, and workflow improvements that raise the capability of the broader Customer Engineering team.

This is a remote role supporting a West Coast territory. 

What this looks like day-to-day

• New customer acquisition and selling: Partner with Account Directors on pre-sales motions for new customer acquisition, product expansion, and expansion across lines of business. You identify customer pain, craft and deliver tailored demos, and lead technical evaluations through requirements gathering, success criteria, installation guidance, and hands-on workshops.
• Complex implementations and value realization: Lead onboarding for strategic customers, including planning, implementation, integrations, and training. You build customer-specific implementation playbooks, guide complex deployments with executive visibility, and ensure customers realize value during onboarding and over time.
• Adoption, expansion, and growth: Identify opportunities to expand adoption across underutilized features, untapped products, and new lines of business. When adoption stalls, you diagnose root causes, design a path forward, and connect technical work to measurable business outcomes.
• Technical escalation: Serve as an escalation point for complex technical challenges raised by other Customer Engineers. You resolve ambiguous problems with multiple variables and tradeoffs, involving Product or Engineering only when truly needed.
• Team capability building: Build playbooks, document repeatable fixes, coach peers, and improve how Customer Engineering work gets done across the team. You use AI tools to accelerate content creation, surface patterns across accounts, and share practical workflow findings with the broader team.
• Early account impact: Assess account health, risks, stakeholder relationships, and the highest-priority problems to solve within your portfolio. You establish trust with Account Directors and customer stakeholders, then independently lead complex customer interactions that move accounts forward.
• Quarterly business outcomes: Drive measurable improvement in customer health, retention, expansion, and technical resolution across strategic accounts. You contribute reusable frameworks, playbooks, or processes that other Customer Engineers use and become a trusted advisor to Account Directors on account health and technical strategy.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Senior Customer Engineers don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• 5 to 8 years of experience in a customer-facing technical role such as Solutions Engineering, Technical Account Management, Customer Engineering, implementation, professional services, or solutions architecture.
• Deep hands-on experience with web technologies including HTML, CSS, JavaScript, and REST APIs, with the ability to architect and troubleshoot complex front-end implementations.
• Proven experience managing strategic Enterprise accounts with executive-level stakeholders, competing priorities, and complex technical or business requirements.
• Demonstrated ability to solve ambiguous problems involving multiple variables, constraints, and tradeoffs.
• Experience connecting technical execution to business outcomes such as retention, expansion, ROI, and value realization.
• Hands-on use of AI tools for account research, content creation, or workflow automation, with demonstrated integration into day-to-day work rather than light experimentation.
• Experience mentoring or coaching more junior technical team members.

Nice-to-haves

• Experience with Pendo, digital adoption platforms, product analytics, or in-app experience tooling in an enterprise environment.
• Hands-on experience with mobile app development, including Swift, Android, or React Native.
• Familiarity with data architecture, AI or machine learning concepts, or advanced analytics instrumentation.
• Track record of building reusable frameworks, playbooks, or processes that were adopted by a broader team.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Remote

Compensation: The expected On-Target Earnings (OTE) range for this role is $193,393 - $241,742, with a 70/30 base-to-variable compensation split.

Benefits: Pendo offers highly competitive United States benefits, including employer-heavy coverage with $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Senior Manager, Data Science

Portfolio Management and Loss Mitigation

The Role: 

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.

The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do: 

• Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
• Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
• Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
• Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
• Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
• Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.

What You'll Need:

• Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
• Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
• Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
• Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
• Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
• 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
• Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

The Team + The Role

The Enterprise Sales team at Pendo is focused on penetrating Pendo’s most significant untapped accounts, onboarding them onto the Pendo platform, and expanding relationships within the existing customer base. The team is responsible for driving enterprise account growth through disciplined execution, strong customer partnership, and close collaboration across Marketing, Product, and Customer Success.

As RVP, Enterprise Sales, you will report to the AVP of Enterprise Sales and build, manage, and scale a team of high-performing Enterprise Account Directors. You will set the strategy for net-new sales growth, enterprise account expansion, new logo acquisition, forecasting, and sales execution across diverse verticals and geographies.

This is a remote role based in the United States.

What this looks like day-to-day

• Team leadership: Select, onboard, develop, motivate, promote, and manage a team of Enterprise Account Directors. You build a high-performing sales culture grounded in accountability, collaboration, execution, and servant leadership.
• Enterprise growth strategy: Define and execute strategies to grow net-new sales within existing Enterprise accounts and expand Pendo’s footprint through new logo acquisition. You identify where the team should focus and translate growth priorities into clear operating plans.
• Pipeline development: Enable the team to aggressively prospect, identify, qualify, and develop enterprise pipeline. You coach account strategy, inspect pipeline quality, and ensure the team is creating enough opportunity to support sustainable growth.
• Cross-functional alignment: Partner closely with Marketing, Product, Customer Success, and other internal teams to drive customer satisfaction and enterprise account outcomes. You create alignment across teams so customers receive a coordinated, high-quality experience.
• Performance analysis: Analyze industry trends, sales performance, and team metrics to guide execution and accelerate results. You use data to identify risks, prioritize action, and improve sales productivity.
• Sales execution: Drive excellence in sales execution by leveraging the Pendo Value Framework. You reinforce strong value-based selling, coach complex enterprise deal strategy, and help the team execute consistently across opportunities.
• Forecast management: Develop, monitor, and maintain accurate Enterprise sales forecasts. You bring rigor to inspection, methodology, and forecast discipline so the business has clear visibility into performance.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great RVPs don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• 4+ years of experience building and managing a high-performing SaaS sales team selling to Enterprise accounts.
• 7+ years of experience selling enterprise technology in a fast-paced environment.
• Experience building Enterprise businesses from the ground up.
• Track record of overachievement in enterprise sales leadership or enterprise technology sales.
• Strong command of value-based sales methodology and the ability to collaborate effectively in a decentralized environment.
• Demonstrated ability to adapt and lead in a fast-changing environment.
• Experience implementing MEDDICC and Force Management.

Nice-to-haves

• MEDDICC certification.
• Force Management certification.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected On-Target Earnings (OTE) range for this role is $326K-$410K, with a 50/50 base-to-variable compensation split.

Benefits: Highly competitive, employer-heavy coverage including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Staff Software Engineer - AI Research Infrastructure

P-1215

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description

As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security.

You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support.

The Impact you will have

As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: 

• Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems)
• Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring.
• Create tooling that improves research developer productivity, such as experiment management systems, CI/testing infrastructure for research code, and workflows that reduce iteration time.
• Influence the long‑term roadmap for research computation, shaping how Databricks AI Research train, evaluate, and ship models to customers.
• Serve as a technical mentor and force multiplier for other engineers working on compute, infra, and AI systems.

What We Look for

• BS/MS or PhD in Computer Science or related field
• 5+ years of software engineering experience, including substantial time working on large‑scale distributed systems or infrastructure.
• Have deep experience with building and operating distributed systems, data pipelines, or large‑scale backend services, ideally involving GPUs, clusters, or major cloud providers.
• Are proficient in one or more systems programming languages (e.g., C++, Rust, Go, Java, Scala) and can design, implement, and debug complex services.
• Have built or significantly contributed to cluster schedulers, resource managers, or large‑scale job orchestration systems (e.g., Kubernetes, Slurm, Ray, custom internal systems).
• Understand modern ML training and inference workflows (e.g., distributed training, model parallelism, fine‑tuning, evaluation), even if you’re not primarily a research scientist.
• Can move fast and be pragmatic in getting things done, while caring about operational excellence. Have driven complex systems from prototype to stable, well‑owned services.
• Communicate clearly with both researchers and engineers, and enjoy translating between research needs and infra realities.

The Team + The Role

Novus is Pendo’s answer to a new challenge in software: teams are shipping faster than ever, but still need a reliable way to understand what is happening in their software after it reaches users. The product is aimed at product engineers and application owners building AI-native software, creating a new audience and category opportunity for Pendo.

The Product Marketing Director, Novus will be the marketing lead and GTM owner for this new product and category. This role owns narrative, positioning, audience targeting, channel strategy, demand generation, community activation, PLG motion, launch execution, enablement, and the metrics that connect marketing activity to early commercial outcomes.

This role is based in-office in San Francisco or New York.

What this looks like day-to-day

• Messaging and positioning: Develop and maintain messaging, positioning, and talk tracks as Novus evolves. Keep product, sales, marketing, and leadership aligned on how to describe the product, audience, category, and customer value.
• End-to-end GTM ownership: Own the full GTM plan for Novus, including audience targeting, channel strategy, campaign execution, launch moments, and success metrics. Build the plan, run it, and own the outcomes.
• Top-of-funnel growth: Own top-of-funnel acquisition for Novus by defining the channel mix, running campaigns, and driving early access signups. Connect acquisition activity to activation, free-to-paid conversion, and early revenue outcomes.
• Community activation: Build the community presence for Novus from the ground up across developer forums, social channels, influencer relationships, and event-driven activation. Create authentic engagement with builders who are skeptical of traditional marketing.
• PLG motion: Own the product-led growth motion in close collaboration with product and growth. Help design self-serve onboarding, activation flows, and freemium-to-paid conversion strategy.
• Pendo and Novus positioning: Help define how Novus and Pendo work together for customers. Position the relationship clearly for teams scaling from fast-moving startups into more complex product organizations.
• Sales and partner enablement: Build enablement materials that help sales and partner teams have credible conversations with product engineers. Translate technical depth into plain language without oversimplifying the product or audience.
• Measurement and commercial impact: Define and own the metrics that connect Novus marketing activity to pipeline and early commercial outcomes. Track measures such as free-to-paid conversion, activation rates, and marketing-sourced ARR contribution.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Product Marketing Directors don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• 7+ years of marketing experience, including at least 2-3 years owning GTM for a technical product or developer-facing platform at the individual contributor level.
• Experience building software or working closely enough with engineers to understand codebases, pull requests, and deploy cycles.
• AI-native working style, with regular use of tools such as Claude, ChatGPT, or similar tools to move faster, generate ideas, and pressure-test thinking.
• Strong content and storytelling instincts, with the ability to write a crisp narrative, build a compelling launch moment, and translate technical depth into plain language without oversimplifying.
• Hands-on experience building community and developer awareness, including an understanding of how builders discover tools, what earns trust in communities such as Hacker News or GitHub, and what feels authentic versus tone-deaf.

Nice-to-haves

• Hands-on experience with PLG go-to-market motions, including self-serve acquisition, freemium conversion, and community-led distribution.
• Familiarity with product analytics, instrumentation, or observability tools.
• Experience marketing to or within developer communities, including open source, dev tools, AI coding tools, or similar spaces.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected salary range for this role to be performed in New York, NY is $196,300 - $249,000. The expected salary range for this role to be performed in San Francisco, CA is $196,300 - $249,000.

Benefits: Highly competitive, employer-heavy coverage including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

The Team + The Role

Pendo’s marketing and communications teams shape how customers, media, employees, and the broader market understand Pendo’s brand and mission. The team connects Pendo’s products, insights, and leadership perspective to timely industry conversations across earned, owned, and shared channels.

The Director, Communications & Editorial Content will lead Pendo’s global communications, social media, and content strategy. This role will oversee teams and agency partners, advise executives, develop corporate and executive narratives, and drive storytelling that builds awareness with media, influencers, customers, and key markets.

This role is based in-office in Raleigh or San Francisco.

What this looks like day-to-day

• Global communications strategy: Lead and evolve Pendo’s global communications strategy across media and influencer relations, social media, and content creation. Ensure programs are aligned to Pendo’s brand, business priorities, and market opportunities.
• Corporate storytelling: Develop compelling corporate and executive narratives that connect Pendo’s mission, products, and market insights to broader industry and cultural conversations. Shape stories that resonate across audiences, channels, and markets.
• Executive communications: Serve as a trusted advisor to the executive team and senior leaders. Partner on speeches, presentations, thought leadership, and messaging that elevate Pendo’s brand and leaders’ public presence.
• Media and influencer engagement: Drive strategic campaigns and proactive pitching that earn coverage in top-tier business and technology outlets. Support speaking opportunities and executive visibility at high-impact events.
• Editorial and content leadership: Oversee Pendo’s content strategy and ensure a consistent voice and high-quality storytelling across owned channels and events. Guide teams toward content that is timely, relevant, and aligned to business goals.
• AI-enabled scale: Leverage AI and emerging technologies to improve content creation, team efficiency, and performance analysis. Use these tools to scale creativity, output, and communications impact.
• Agency and cross-functional partnership: Manage agency relationships and ensure alignment across earned, owned, and shared media programs. Collaborate with marketing, product, and people teams to support campaigns, product launches, event promotion, employer brand, and community initiatives.
• Measurement and optimization: Establish KPIs and report on communications and content impact. Use performance insights to identify opportunities, improve programs, and drive continuous improvement.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Communications and Editorial Content Directors don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• BA/BS degree, with preference for communications, journalism, marketing, or a related field.
• At least 10 years of communications, PR, or editorial experience.
• At least 5 years of experience leading integrated teams in high-growth B2B technology or SaaS environments.
• Proven success developing global media strategies and securing top-tier coverage.
• Demonstrated ability to craft narratives and content that resonate across audiences, channels, and platforms.
• Experience supporting and coaching executives on messaging, thought leadership, and public speaking.
• Strong writing, editing, and storytelling skills, with mastery of journalistic and AP style.
• Must be authorized to work in the United States without current or future sponsorship.

Nice-to-haves

• Deep understanding of the business, technology, and SaaS media landscape.
• Experience building and scaling executive communications programs.
• Comfort navigating and experimenting with AI tools to accelerate content and communications work.
• A mix of creative and analytical thinking, with the ability to connect big ideas to operational execution.
• Collaborative leadership style with experience managing agencies and high-performing teams.
• Exceptional organization and prioritization skills in a fast-paced, high-growth environment.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected salary range for this role to be performed in Raleigh, NC is $155,000 - $210,000 plus eligibility for 20% corporate bonus. The expected salary range for this role to be performed in San Francisco, CA is $178,300 - $240,000 plus eligibility for 20% corporate bonus.

Benefits: Highly competitive, employer-heavy coverage including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

The opportunity
At Unity, we are building a world-class ad-tech ecosystem that connects billions of users with the creators and experiences they love. The Advertiser Growth team is the engine of this mission, ensuring that as our marketplace expands, advertisers have the intelligent tools, robust infrastructure, and rigorous experimentation frameworks needed to scale their impact.

In 2026, our roadmap is defined by three transformative pillars: Foundation, Smart, and Intelligence. This role is unique in its technical breadth, sitting at the intersection of financial execution, creative innovation, and marketplace science. You will architect the GenAI systems that build high-performing creatives, design the pacing algorithms that manage multi-million dollar budgets, ensure our billing pipelines handle massive scale with zero-fault tolerance, and build the experimentation infrastructure that allows us to scientifically evolve the marketplace. This is a high-stakes role where your technical leadership directly governs Unity’s financial integrity and the long-term growth of our ecosystem.

What you'll be doing

• Next-Gen budget pacing: Design and optimize sophisticated pacing controllers (PID, probabilistic forecasting) to smooth advertiser spend across diverse time zones and traffic spikes, ensuring optimal delivery and marketplace stability.
• Creative GenAI infrastructure: Lead the backend integration of Generative AI models (Diffusion, LLMs) to automate the creation of high-performing image and video assets tailored to specific campaign goals and formats.
• Marketplace experimentation engine: Build and scale the infrastructure for high-velocity experimentation, including A/B testing, switchback tests, and long-term holdouts to measure the impact of marketplace changes on advertiser ROI and platform health.
• High-Scale billing reliability: Architect and maintain high-throughput billing pipelines that process billions of events with 100% accuracy, bridging the gap between real-time ad delivery and mission-critical financial reconciliation.
• Scientific optimization: Analyze complex financial and marketplace datasets to refine the trade-off between spend velocity and advertiser performance, using experimentation results to tune pacing and billing logic.

What we're looking for

• Advanced degree in computer science or relevant engineering-related field or equivalent experience.
• 6+ years of software engineering experience, including 3+ years working on ads delivery systems.
• Extensive experience building and operating large-scale, low-latency backend systems using languages like Java, Go, or Scala.
• Deep familiarity with building or maintaining budget control systems, feedback loops, or spend-prediction algorithms.
• Proven experience building or scaling experimentation platforms, with a deep understanding of variance reduction, interference/network effects, and metric design in a marketplace context.
• A track record of working on "mission-critical" pipelines (like billing, payments, or clearinghouses) where data precision, idempotency, and fault tolerance are paramount.
• Experience or strong technical interest in building the backend workflows required to serve, scale, and store Generative AI models for creative asset generation.
• Proficiency with real-time stream processing (Kafka, Flink, or Spark) specifically applied to event-based charging and real-time performance feedback.
• A proven ability to lead complex, multi-quarter technical roadmaps and mentor senior engineers in a high-growth environment.

Additional information

• Relocation support is not available for this position

Life at Unity

Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. Therefore, we provide employment opportunities without regard to age, race, color, ancestry, national origin, disability, gender, or any other protected status in accordance with applicable law. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

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