About the Role

Together AI is building high-performance inference compute and the software platform around it. We’re looking for an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You’ll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org — with mentorship and support from experienced engineers.

Requirements

• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.

Responsibilities

• Contribute to building and maintaining 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).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help 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.

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: $130,000 - $170,000 + 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 an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You’ll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org — with mentorship and support from experienced engineers.

Requirements

• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.

Responsibilities

• Contribute to building and maintaining 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).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help 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.

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: $130,000 - $170,000 + 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

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 contribute to backend services that create value from our company data, and help make our data platform more self-serve 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 work on LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products — with mentorship and support from experienced engineers.

Responsibilities

• Contribute to backend services that enhance the data platform’s capabilities (APIs, control planes, automation, governance).
• Help enable DIY workflows for teams across the company:

• • Define/publish events and schemas
  • Create/consume streams and subscriptions
  • Establish access models (authz, row/field-level controls where applicable)
  • Manage dataset/catalog metadata, lineage, versioning, and retention

• Contribute to end-to-end data products: ingestion → validation/quality → enrichment → serving (APIs/streams) → observability → adoption.
• Work on prompt categorization and enrichment services: taxonomy design, labeling workflows, classifier/rules integration, evaluation, drift/quality monitoring, and safe rollouts.
• Learn to own reliability: SLOs, alerting, performance/cost tuning, incident response, and postmortems.
• Partner cross-functionally with ML/LLM, infra, security, and product teams to define crisp contracts and deliver durable platform primitives.

Requirements

• 0–4 years building production or project-based backend systems (internships, coursework, and personal projects count).
• Solid fundamentals in at least one backend language (e.g., Go, Python, Java, Rust) and some exposure to API design (REST).
• Eagerness to own work end-to-end: design docs, implementation, testing, deployment, and iteration based on real usage.
• Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, and a desire to build systems that are easy to evolve.
• Basic data modeling and SQL skills, and some familiarity 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 curiosity:

• • You’re curious about how engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, retrieval/knowledge grounding), and you’re eager to apply this to your own work.
  • You understand that AI tools can fail or create issues, and you’re thoughtful about when and how to apply them.

Nice to have

• Any exposure to self-serve platforms, developer tooling, or multi-tenant services.
• Coursework or projects involving LLM/AI products: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
• Passion for good quality code, highly readable, SOLID principles, design patterns, Domain Driven Design.
• Awareness of security and governance basics: 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: $120,000 - $170,000 + 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  

The Role

Join us in revolutionizing the lending landscape. SoFi is seeking enthusiastic Senior Software Engineers who are ready to lead the development of key advancement to the next generation of our financial services platform. 

Data Foundations leads the path on building the central platform-level foundation and infrastructure that powers SoFi's entire data ecosystem. Their scope spans Infrastructure & Core Primitives and Platform Operations — essentially the backbone that enables all data capabilities across the organization. Key qualifications of this role include:

• Leading the technical evolution of one or more key platform subsystems.
• Resolving problems in the platform design and implementation that weren’t clearly anticipated, taking requirements with ambiguity and proposing durable technical solutions.
• Expertly leverage existing solution patterns and understand when to differentiate resulting in well-structured, maintainable code.
• Ability to understand data models, APIs, scaling concerns, and failure modes in order to make effective trade-offs between maintainability and performance.
• Creating stability by writing meaningful tests, considering observability, and leveraging your ability to debug complex issues across multiple system layers.
• The ability to create clear design and operational documentation.
• Contributes to code reviews, is a role model for more junior engineers, and contributes to team efficiency, beyond personal output.

What You’ll Do

As an emerging leader within our team, you will focus on building out the backend services for our next-generation Lending Platform. This role involves full product lifecycle engagement, from initial concept to deployment. Key responsibilities include implementing new capabilities, ensuring code quality, and delivering highly-available, scalable services. Success requires close technical collaboration with Product, Marketing, Operations, Business, Legal, and Compliance teams. You will be responsible for translating business requirements from these stakeholders into effective technical solutions that provide outstanding value to our members.

What You’ll Need

• Bachelor's or Master's degree in Computer Science, or Software Engineering
• 3+ years as a professional, full-time Software Engineer, or similar relevant work experience.
• Proficient coding in Java, Kotlin, or other similar object-oriented programming language.
• Proficient working with GIT and related CI/CD systems.
• Experience with public cloud compute, storage, and infrastructure.
• Experience with any data warehousing solution like Snowflake and IAC tools to provision platform infrastructure.
• Experience with Kafka, Docker, Kubernetes, and Spring Boot or similar frameworks.
• Deep understanding of relational and document database fundamentals.
• Deep understanding of fundamental distributed systems concepts.

Nice To Have

• Full-Stack experience in both back-end (Kafka, Redis, Docker) and front-end (JavaScript, TypeScript, React).
• Experience with microservices design principles and architecture.
• Experience with workflow orchestration technology (AWS step function, Airflow, Temporal).

We're driven to push boundaries and deliver exceptional products to help our members achieve financial stability. If you have the passion and a commitment to customer success, we want to hear from you.

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.

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do

As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. 

Where you’ll work

This role will be based in our Sao Paulo office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities:

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation. 
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications. 
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.
• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

Requirements:

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python. 
• Experience with agentic AI. 
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice to have:

• Familiarity with BI tools such as Looker, Tableau, or similar platforms. 
• Solid dbt in production: models, tests, docs, and collaboration in a shared repo. 
• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions. 
• Experience with Salesforce data integration. 

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do

As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. 

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities:

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation. 
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications. 
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.
• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

Requirements:

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python. 
• Experience with agentic AI. 
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice to have:

• Familiarity with BI tools such as Looker, Tableau, or similar platforms. 
• Solid dbt in production: models, tests, docs, and collaboration in a shared repo. 
• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions. 
• Experience with Salesforce data integration. 

Compensation:

The expected salary range for this role is $120,800 - $151,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About this role

We are looking for an experienced Senior Business Intelligence Analyst to scale a critically important function responsible for building and maintaining systems, processes and services that enable us to understand financial performance and unlock key business insights at Faire. The ideal candidate for this role will ensure key accounting procedures are automated in ways that are accurate, efficient, easy-to-understand, and scalable. This role will sit in the Finance department and collaborate with team members from a breadth of functional groups across Faire, including Accounting, Finance & Strategy, Engineering and Data Infrastructure. This role will have a tremendous impact on the ability for Faire employees to use data effectively in order to report numbers externally and make impactful decisions internally. As an early member of a burgeoning team, you will have the opportunity to write the roadmap for how we improve access to business critical data and unlock automation that amplifies the impact of a variety of functions. 

What you’ll do 

• Scope, design, create, and manage complex ETL flows that aggregate and synthesize key business performance metrics and financial reporting, ensuring efficient, accurate, and scalable data models using best practices 
• Act as a trusted analytical partner to the Accounting and Finance teams providing technical expertise, gathering requirements from product and operational teams, and enabling data-driven decision-making and accountability by ensuring core ledgers accurately reflect business changes 
• Collaborate closely with Engineering, Data Infrastructure, and other stakeholders as a key translator and process improver, gathering requirements and delivering impactful data solutions that ensure alignment and efficiency across the organization 
• Lead initiatives to drive data strategy, roadmap planning, and prioritization, ensuring alignment with business objectives 
• Act as a thought leader to expand the team’s influence and impact throughout the Finance team and the broader organization 
• Drive workflow automation and innovation across Finance, including identifying and implementing Gen-AI–enabled productivity solutions to modernize processes and increase team leverage

Qualifications

• 5+ years of work experience in Business Intelligence, Analytics Engineering, Data Analytics, or comparable function 
• Expert in SQL with focus on data modeling, large-scale data processing, and tool development for analytics or Financial use cases. 
• Experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms 
• Experience with analytics workflow tools (examples: Airflow, Docker, dbt), data warehousing and storage (examples: Snowflake, BigQuery, Redshift, S3), and data visualization tools (examples: Mode, Tableau, Looker) 

Nice to have: 

• Experience with Python, R or other programming languages 
• BA/BS degree, ideally in computer science, math or another quantitative field 
• Familiarity with version control using Git and proficiency in command-line tools for workflow automation and data manipulation

Salary Range

San Francisco and New York: The pay range for this role is $174,500 to $240,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

San Francisco: the pay range for this role is $246,500 to $339,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

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 enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.

We’re looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent PhD graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems.

You’ll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you’ll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient.

This role offers the opportunity to bridge research and production—translating advanced ideas into systems that operate at scale.

What you'll be doing

• Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
• Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
• Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
• Improve reproducibility and reliability through dataset validation, monitoring, and testing
• Partner with ML engineers to support experimentation and model iteration
• Help optimize performance and efficiency across data processing and training systems
• Contribute to the evolution of our offline ML platform architecture as it scales

What we're looking for

• PhD in Computer Science, Machine Learning, Systems, or a related field
• Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
• Experience with Python and working with data-intensive workloads
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
• Experience (academic or applied) with data pipelines, model training workflows, or large datasets
• Strong problem-solving skills and ability to translate research ideas into practical systems
• Interest in building scalable, reliable infrastructure for machine learning
• Nice to Have
• Experience with workflow orchestration systems (Airflow, Flyte, etc.)
• Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
• Publications or research in ML systems, distributed systems, or related areas

Additional information

• Relocation support is not available for this position
• Work visa/immigration sponsorship 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.

#MID #LI-ED1

As a Senior Analyst, Analytics engineering, you’ll enable our analytics community to get the most out of our data. You’ll support analysts of varying levels of scope and experience by building, maintaining, and governing a data warehouse of operational and financial data.

You’ll keep us on the cutting edge of AI-driven analytics by partnering with Data Ops to develop a semantic layer and various agents to facilitate faster, better, and more interpretable insights.

We're seeking someone based near one of the following cities: San Francisco, Salt Lake City, Chicago, or New York City.

RESPONSIBILITIES

• Develop and maintain data models in Snowflake with dbt
• Design and build a testing and alerting framework to improve data quality
• Create data governance/democratization policies to support the broader analyst community
• Design and build a self-service analytics AI framework, including both the semantic modeling and tooling architecture

Partner with Data Engineering to optimize data staging in Snowflake

QUALIFICATIONS 

• 4+ years of experience in data engineering, analytics, or data science
• A bachelor’s degree in Computer Science, Information Systems, Statistics, or another quantitative field
• Advanced SQL knowledge (experience with dbt is a plus)
• Moderate Python knowledge (JavaScript knowledge is a plus)
• Experience building complex data pipelines using engineering best practices in platforms like Airflow or Prefect

Strong organizational discipline and quality assurance skills

PERKS & BENEFITS 

• We offer Gongsters a variety of medical, dental, and vision plans, designed to fit you and your family’s needs.
• Wellbeing Fund - flexible wellness stipend to support a healthy lifestyle.
• Mental Health benefits with covered therapy and coaching.
• 401(k) program to help you invest in your future.
• Education & learning stipend for personal growth and development.
• Flexible vacation time to promote a healthy work-life blend.
• Paid parental leave to support you and your family.
• Company-wide recharge days each quarter.
• Work from home stipend to help you succeed in a remote environment.

The annual salary hiring range for this position is $120,000 - $145,000 USD. 

Compensation is based on factors unique to each candidate, including, but not limited to, job-related skills, qualification, education, experience, and location. At Gong, we have a location-based compensation structure, which means there may be a different range for candidates in other locations. The total compensation package for this position, in addition to base compensation, may include incentive compensation, bonus, equity, and benefits. Some of our sales compensation programs also offer the potential to achieve above targeted earnings for those who exceed their sales targets. 

We are always looking for outstanding Gongsters! So if this sounds like something that interests you regardless of compensation, please reach out. We may have more roles for you to consider and would love to connect.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Gong recruiting email communications will always come from the @gong.io domain. Any outreach claiming to be from Gong via other sources should be ignored.

Gong is an equal-opportunity employer. We believe that diversity is integral to our success, and do not discriminate based on race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, military status, genetic information, or any other basis protected by applicable law.

To review Gong's privacy policy, visit https://www.gong.io/gong-io-job-candidates-privacy-notice/ for more details.

#LI-NK1

At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment.

This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

What you’ll do

• Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria
• Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans
• Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems
• Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration
• Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations
• Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement
• Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline
• Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production
• Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

What we’re looking for

• 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role
• Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact
• Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans
• Strong foundation in statistics, experimentation, causal reasoning, and measurement
• Experience building tools or products, not just analyses — for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications
• Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work
• Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly
• Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives
• High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications

• Experience in a forward deployed, solutions, consulting, or other client-facing technical role
• Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products
• Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow
• Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery
• Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems
• Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling
• Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like

Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

About the Role

As an Analytics Engineer, you will be an early member of the Data Science & Analytics team building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Engineering, Product, GTM and other areas to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company’s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions. 

Responsibilities:

• Understand the data needs of stakeholder teams in terms of key data models and reporting, and translate that into technical requirements
• Define, build and manage key data pipelines in dbt that transform raw logs into canonical datasets
• Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data
• Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company
• Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company
• Influence the future roadmap of Product and GTM teams from a data systems perspective
• Become an expert in our organization’s data models and the company's data architecture

You might be a good fit if you have:

• 5+ years of experience as an Analytics Data Engineer or similar Data Science & Analytics roles, preferably partnering with GTM and Product leads to build and report on key company-wide metrics.
• A passion for the company's mission of building helpful, honest, and harmless AI.
• Expertise in building multi-step ETL jobs, building robust data models through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.
• Expertise in SQL and Python to transform data into accurate, clean data models.
• Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.
• A bias for action and urgency, not letting perfect be the enemy of the effective.
• A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
• Experience building an Analytics Data Engineering (or similar) function at start-ups. 
• A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.

Who We Are

EDO is the TV outcomes company. Our measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales, helping advertisers, agencies, networks, streamers, and studios understand what works across linear and streaming TV.

We combine immediate engagement signals with decision science, vertical AI, and investment-grade data to help the advertising industry maximize media impact, optimize creative performance, and value every impression. EDO is headquartered in New York City and Los Angeles with office space in San Francisco. For employees residing full-time in NYC, SF, or LA, we have a hybrid work policy of three days in the office and two remote work days.

The Role

EDO is looking for a Senior Platform Engineer to help accelerate our shift toward a platform model. This is a senior IC role on the Infrastructure team focused on paved paths, reusable infrastructure patterns, and self-service workflows that help software, data, and machine learning engineers ship safely and efficiently.

Our environment is AWS-heavy and data-intensive, with heavy use of EC2, RDS, S3, SageMaker, MWAA/Airflow, Snowflake, dbt, Chef, Terraform, Spacelift, and emerging ECS/container patterns. The right person has strong AWS and infrastructure-as-code fundamentals, prior exposure to platform engineering practices, and the pragmatism to modernize existing systems without assuming everything should be rebuilt from scratch.

We approach infrastructure as an internal product: understanding engineers’ needs, prioritizing high-leverage platform capabilities, and iterating on tools and workflows that make teams faster, safer, and more self-sufficient.

What You Will Do

• Build and evolve EDO's internal platform capabilities: paved paths, reusable infrastructure modules, deployment standards, documentation, and self-service workflows.
• Own and improve Terraform and Spacelift-based infrastructure workflows, including module design, reviews, approvals, drift detection, and guardrails.
• Modernize existing AWS infrastructure, including EC2- and Chef-based systems, while helping teams adopt more standardized and repeatable patterns over time.
• Support production data and ML platform infrastructure, including MWAA/Airflow, Snowflake, dbt, SageMaker, S3, RDS, and related AWS services.
• Partner with software, data, and ML engineers as internal customers, turning recurring infrastructure needs into scalable platform capabilities rather than one-off support work.
• Improve deployment, CI/CD, observability, alerting, and incident response practices so teams can operate production systems with greater confidence.
• Expand pragmatic ECS/container deployment patterns where they create value, without treating Kubernetes as the default answer.
• Participate in a lightweight on-call rotation and use operational learnings to reduce toil, improve reliability, and strengthen the platform.

What We Are Looking For

• 6+ years of experience in platform engineering, infrastructure engineering, SRE, DevOps, cloud infrastructure, or similar roles.
• Experience building, operating, or contributing to an internal developer platform, infrastructure platform, developer productivity team, or similar platform-oriented function.
• Strong production experience with AWS, especially EC2, RDS, S3, IAM, networking, load balancing, and related operational patterns.
• Strong hands-on experience with Terraform or similar infrastructure-as-code tooling, including reusable modules and multi-environment patterns.
• Comfort working in a data-heavy environment and supporting technologies such as Airflow/MWAA, Snowflake, dbt, SageMaker, S3, and RDS.
• Product-minded approach to infrastructure: able to understand engineer pain points, prioritize high-impact platform work, document paved paths, and iterate based on adoption and feedback.
• Strong operational judgment, including debugging production systems, improving observability, and building platform patterns that support reliability, security, and cost efficiency.

Bonus Points

• Hands-on experience with Spacelift or similar IaC orchestration platforms such as Terraform Cloud or Atlantis.
• Experience helping an organization adopt platform engineering practices, including paved paths, golden paths, service templates, and developer-facing documentation.
• Experience with Chef, AWS cost management, security/compliance-driven infrastructure, or production ML/data science infrastructure.

Compensation and Benefits

EDO offers a competitive compensation package. Components of compensation include:

• Mid-stage equity and competitive salary
• Flexible Time Off
• Medical, dental and vision coverage: EDO provides full coverage for individual medical plans and partial coverage for dependent or family plans.
• 401(k) plan, FSA, HSA
• Commuter Benefits
• When in an office, employee meals, snacks, and more

In compliance with New York and California Pay Transparency Law, the salary range for this position is $170,000 to $190,000 plus equity. We note the salary information as a general guideline only, as actual compensation may vary from posting. We will consider various factors to determine the offer for this role, including the scope and responsibilities of the position, relevant work experience, key skills, training, and business considerations.

EDO is an Equal Opportunity Employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status. All your information will be kept confidential according to EEO guidelines.

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

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

The Role

Join us in revolutionizing the financial landscape. SoFi is seeking enthusiastic Senior Software Engineers who are ready to lead the development of key advancement to the next generation of our financial services platform.

Data Trust org leads the path for building platform services, and governance initiatives — from integrating diverse data sources into governance tools to evolving the foundational architecture that supports SoFi’s long-term growth

Data Trust’s charter includes

• Development and management of the Unified Data Catalog and Discovery Tools
• Ownership and other metadata associated with the Catalog
• Lineage and retention policies
• Data Quality Strategy and Standardization (Tiered Ownership, SLOs)
• Enforce regulatory compliance and privacy across data
• Data Governance enforcement and tooling (Data Contracts, RBAC mechanisms).
• Building self-service tools for Data Owners and Data Engineers.

What You’ll Do

As an emerging leader within our team, you will focus on building out the backend services for our next-generation metadata architecture. This role involves full product lifecycle engagement, from initial concept to deployment.

Key responsibilities for this role include:

• Implementing new capabilities, ensuring code quality, and delivering highly-available, scalable services.
• Success requires close technical collaboration with Product, Marketing, Operations, Business, Legal, and Compliance teams. You will be responsible for translating business requirements from these stakeholders into effective technical solutions that provide outstanding value to our members.
• Leading the technical evolution of one or more key platform subsystems.
• Expertly leverage existing solution patterns and understand when to differentiate resulting in well-structured, maintainable code.
• Ability to understand data models, APIs, scaling concerns, and failure modes in order to make effective trade-offs between maintainability and performance.
• Creating stability by writing meaningful tests, considering observability, and leveraging your ability to debug complex issues across multiple system layers.
• The ability to create clear design and operational documentation.
• Contributes to code reviews, is a role model for more junior engineers, and contributes to team efficiency, beyond personal output.

What You’ll Need

• Bachelor's or Master's degree in Computer Science, or Software Engineering
• 3+ years as a professional, full-time Software Engineer, or similar relevant work experience.
• Proficient coding in Java, Kotlin, Python or other similar object-oriented programming language.
• Proficient working with GIT and related CI/CD systems.
• Experience with public cloud compute, storage, and infrastructure.
• Experience with any data warehousing solution like Snowflake and IAC tools to provision platform infrastructure.
• Experience with Kafka, Docker, Kubernetes, and Spring Boot or similar frameworks.
• Deep understanding of relational and document database fundamentals.
• Deep understanding of fundamental distributed systems concepts.

Nice To Have

• Full-Stack experience in both back-end (Kafka, Redis, Docker) and front-end (JavaScript, TypeScript, React).
• Experience with microservices design principles and architecture.
• Experience with workflow orchestration technology (AWS step function, Airflow, Temporal).
• Experience working with Data Platforms

We're driven to push boundaries and deliver exceptional products to help our members achieve financial stability. If you have the passion and a commitment to customer success, we want to hear from you.

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

Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure.

As a Senior Backend Engineer, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal StaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world.

Some of what you’ll work on:

• Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters.
• Build out a global management plane for managing our data center compute, networking, and storage.
• Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features.

Responsibilities

• Identify, design, and develop foundational backend services that power Together’s cloud platform
• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
• Partner with product teams to understand functional requirements and deliver solutions that meet business needs
• Write clear, well-tested, and maintainable software and IaC 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

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices
• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
• Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members
• Demonstrated experience with building and operating high-performance and/or globally distributed microservice architectures across one or more cloud providers (AWS, Azure, GCP)
• Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale
• Experience developing against and managing a relational database, such as PostgreSQL
• Expert-level programmer in one or more of programming language (Golang preferred)
• Proficiency in version control practices and integrating IaC with CI/CD pipelines.
• Experience with Kubernetes and containers preferred
• Experience building and operating data infrastructure (Kinesis, Airflow, Kafka, etc) a plus
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience

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 in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160,000 - $230,000 + 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

This is the first dedicated data hire on Together AI's Finance team. You will own the data layer that Finance runs on — building from scratch the models, pipelines, and reporting infrastructure that allow Strategic Finance, FP&A, and Accounting teams to get reliable answers quickly. The person in this role will have direct exposure to every part of the Finance organization and a real opportunity to shape how data-driven decision-making develops here as the company scales.

A significant portion of your work will touch the data behind the economics of Together's infrastructure, which sits behind nearly every financial question we ask. You will work closely with Together's Data and Commerce engineering team, which owns the underlying billing pipelines and data warehouse. Your job is to define and build the modeling and reporting layer that turns raw operational data into finance-grade datasets — aligning on data contracts, representing Finance's requirements in data design decisions, and ensuring the metrics Finance depends on are correct, documented, and trusted.

Responsibilities

• Own and evolve the dbt transformation layer for Finance: design, build, test, document, and maintain models covering billing, financial performance, compute unit economics, and operational metrics
• Author and maintain Airflow DAGs (Astronomer-managed) that orchestrate Finance dbt runs, data quality checks, and downstream dependencies reliably
• Deliver dashboards and reporting in Hex for the executive team covering financial performance, utilization, and key operating metrics
• Partner with Strategic Finance, FP&A, and Accounting teams on the data infrastructure behind forecasting, cost modeling, and other financial analyses
• Set data quality standards across Finance data products and own incident response when Finance-critical pipelines break
• Build the data foundation – clean, well-structured, documented, and reliably maintained – that enables Finance team to self-serve data analysis and supports AI automation and agentic workflows 

Requirements

• 5+ years in an analytics engineering or data engineering role, with meaningful time supporting Finance or business operations teams
• Expert SQL and production-grade dbt experience — models, tests, docs, snapshots, incremental strategies; you've designed a dbt project from scratch and maintained it
• Hands-on experience with Snowflake and Airflow in production; familiarity with Astronomer and the Cosmos dbt integration is a strong plus
• Solid dimensional modeling fundamentals: star schemas, slowly changing dimensions, fact table grain — you can apply Kimball principles without needing to look them up
• Strong dashboarding skills with a track record of executive-facing reporting that people actually use; experience with Hex or a comparable notebook/BI tool
• Clear communicator who can align stakeholders on metric definitions and translate between engineering tradeoffs and Finance requirements in both directions
• High comfort with ambiguity; this role will require scoping problems from scratch, not executing against pre-defined specs

Nice to Have

• Experience with financial data or billing data such as ARR, usage-based billing, invoice reconciliation, revenue recognition patterns, etc.. We operate a usage-based billing system and this context transfers directly.
• Experience with PII handling, data masking, access-tier modeling, or compliance work (SOC 2, ISO 27001, GDPR, CCPA).
• Familiarity with lakehouse patterns (Iceberg, Delta, Hudi) and hybrid warehouse/lake architectures.
• Python for data tooling: automation, data quality frameworks, custom dbt macros or operators.
• Experience with Hex, Metabase, or similar notebook/BI tooling that sits on top of your dbt models.
• Prior experience in a high-growth AI/ML infrastructure or platform company

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 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: $200k -$240k + 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.  

What we offer:

• Competitive compensation package including equity and annual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits)
• MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
• Flexible PTO, 10 paid holidays, and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

Title: Actuarial Data Scientist

Location: San Francisco Bay Area, CA / Austin, TX / Dallas, TX / Morristown, NJ (Flexible / Hybrid)

Reporting to: Director, Actuarial

Open to Relocation? We’ve Got You Covered: 

This role is open to candidates willing to relocate to one of our hub locations. Hippo offers relocation assistance to support your move, so you can focus on doing impactful work—not the logistics of getting here.

About Hippo:

Hippo exists to protect the joy of homeownership. We believe that insurance should protect the things you treasure through an intuitive, modern experience. We provide tailored insurance coverage and preventative maintenance plans that keep you protected throughout your homeowner journey. We’ll also help you find coverage for everything life brings—from auto to flood—reimagining how you care for your home.

About This Role:

We’re hiring an Actuarial Data Scientist to lead loss cost modeling for Hippo's Homeowners program. This role will own the design, development, and deployment of predictive models for frequency and severity, ensuring strong alignment with pricing strategy and business objectives. You'll build and scale Python-and SQL-based tooling that embeds expected loss ratio and segmentation analytics into reusable, production-ready workflows. In addition to leading loss cost modeling, you'll have the opportunity to expand the team's modeling capabilities across the demand and aggregation models to inform broader pricing and business mix decisions. 

About You:

You are a hands-on leader with a strong background in loss modeling. You bring structure to ambiguity, enjoy building scalable work, and take pride in developing people on your team. You think critically about model maintenance cost and you balance scientific rigor with practical business impact. You communicate clearly, document thoroughly, and operate with a strong sense of ownership.

What You’ll Do:

• Lead a homeowners insurance modeling, setting clear priorities, technical standards, and best practices while fostering a culture of ownership, rigor, and continuous improvement 
• Own the design and annual build of our by-peril loss models
• Expand modeling capabilities across conversion, retention, and aggregation to inform pricing strategy, business mix, and portfolio performance 
• Implement and scale models within our Airflow-based Python modeling pipeline, ensuring robust testing, validation, reproducibility, and long-term maintainability
• Develop reusable analytical tooling and workflows that improve efficiency, consistency, and scalability across the actuarial team
• Partner cross-functionally with Insurance Product, Underwriting, and Engineering to translate complex modeling insights into clear business recommendations and ensure successful production deployment

Must Haves:

• Bachelor’s degree in statistics, mathematics, data science, or another quantitative field
• 5+ years of experience in data science, analytics, or actuarial modeling within personal lines P&C insurance
• Strong experience with loss cost modeling; exposure to demand, underwriting, and/or claims modeling
• Knowledge of actuarial principles as they relate to insurance pricing
• Advanced proficiency in Python and SQL
• Excellent communication skills and ability to build trust with stakeholders at all levels

Nice to Haves:

• Actuarial credentials - ACAS/FCAS
• Master’s degree in a quantitative discipline
• Experience working in modern data platforms, including familiarity with cloud infrastructure (e.g., AWS) and workflow orchestration tools (e.g., Airflow)

The base pay range for this role is $145,000- $160,000 for our Texas (Austin and Dallas regions). The SF Bay Area (and New Jersey) base pay range for this role is $155,000- $180,000. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, location, business needs and market demands. 

Benefits and Perks:

Hippo treats its team members with the same level of dedication and care as we do our customers, which is why we’re fortunate to provide all of our Hippos with: 

• Relocation Assistance - Support available for qualified candidates relocating to one of our hub locations
• Healthy Hippos Benefits - Multiple medical plans to choose from and 100% employer covered dental & vision plans for our team members and their families. We also offer a 401(k)-retirement plan, short & long-term disability, employer-paid life insurance, Flexible Spending Accounts (FSA) for health and dependent care, and an Employee Assistance Program (EAP) 
• Equity - This position is eligible for equity compensation  
• Training and Career Growth - Training and internal career growth opportunities 
• Flexible Time Off - You know when and how you should recharge 
• Little Hippos Program - We offer 12 weeks of parental leave for primary and secondary caregivers 
• Hippo Habitat - Snacks and drinks available and catered lunches for onsite employees 

Hippo is an equal opportunity employer, and we are committed to building a team culture that celebrates diversity and inclusion.  

Hippo’s applicants are considered solely based on their qualifications, without regard to an applicant’s disability or need for accommodation. Any Hippo applicant who requires reasonable accommodations during the application process should contact the Hippo’s People Team to make the need for an accommodation known. 

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

About the role

Starburst is looking for an experienced Staff Software Engineer to sit at the intersection of software engineering and data engineering — building the internal platforms, pipelines, and data products that power how we understand our customers and our business. You'll work across Starburst Enterprise and Starburst Galaxy, using our own technology to solve real problems at scale, while also contributing software that other teams depend on.

Because data engineers are one of our primary target personas, you'll bring a uniquely valuable perspective: you'll use our products daily and feed that experience directly back into how we build and improve them. You'll work closely with a dynamic, talented, globally distributed team, writing production-quality software alongside building reliable data systems — with a consistent emphasis on quality, maintainability, and speed to insight.

As a Staff Software Engineer at Starburst you will:

• Design, build, and operate a high-quality data lake and the software systems that feed it, supporting product management, finance, customer support, and engineering
• Write production-grade software — services, APIs, tooling, and automation — that enables data workflows and integrations at scale
• Find innovative ways to use Trino and Starburst to solve complex data management and software architecture challenges
• Collaborate with technical leads, product managers, and data analysts to build robust data products and analytics
• Leverage AI to democratize access to datasets for users throughout Starburst, including building and maintaining the software infrastructure that makes this possible
• Enable dataset preparation and model evaluation for Starburst's AI projects
• Define and evolve engineering processes and best practices that span both software and data domains, with a focus on reliability and actionable results
• Work closely with leaders across teams to iterate on data architecture and the software systems that implement it, keeping quality high at every layer
• Identify emerging patterns in data management and software engineering, and work with Starburst's product teams to bring those innovations to market

Some of the things we look for

• A Trino enthusiast looking to push the bounds in an AI future
• At least 7 years of combined experience in software engineering and/or data engineering, with genuine depth in both
• Strong software engineering fundamentals: writing clean, testable, well-reviewed code in Java, Python, or Scala
• Experience building and optimizing data pipelines using Trino, Spark, dbt, and related frameworks
• Experience designing and building backend services, APIs, and data platform components
• Experience managing data and application infrastructure in public clouds, particularly AWS (EMR, EC2, S3, IAM); multi-cloud experience (GCP/Azure) is a plus
• Experience using and managing orchestration frameworks such as Apache Airflow or Dagster
• Knowledge of RAG and other design patterns for AI-powered applications
• Fluency in SQL and comfort moving between SQL and general-purpose programming as the task demands
• Experience building API integrations for extracting data from third-party sources
• Knowledge of data modeling techniques appropriate for modern data lakes
• Proficiency with Configuration-as-Code and Infrastructure-as-Code tools such as Pulumi, Terraform, and/or Ansible
• A track record of shipping reliable software and data systems on time, with disciplined practices around testing, code quality, and review
• Strong written and verbal communication skills, with the organizational ability to coordinate across teams

Where could this role be based?

• San Francisco, US

Location: San Francisco, CA (Hybrid) 

What is Verse? 

Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.

Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.

The Role

Verse is seeking a Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and energy risk management. You will shape the machine learning and data modeling foundations that Verse's software is built on. For example, you might spend a cycle deploying electricity market price forecasting pipelines for new regions, developing solar production anomaly detection models, or creating scalable tools for benchmarking energy project financial performance.

Key Responsibilities

• Lead End-to-End Data Science Projects: Own and drive projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions.
• Statistical & Machine Learning Modeling: Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models) to support decision-making and enhance product capabilities.
• Analytics Engineering & Data Modeling: Perform complex data transformations and develop well-structured data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets.
• Software Development & Productionization: Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems in a cloud-based environment while leveraging AI coding tools to accelerate development.
• MLOps: Contribute to Verse’s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production.
• Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows.

What We're Looking For (Minimum Qualifications)

• Master’s degree in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and 2+ years of professional experience in data science or machine learning; or
• Bachelor’s degree and 4+ years of professional experience in data science or machine learning
• Strong foundation in statistical modeling and machine learning, including time series forecasting and model evaluation
• Experience deploying and maintaining models in cloud-based environments (e.g., AWS, GCP, or Azure) using MLOps practices
• Strong Python expertise, including experience with scientific computing and ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
• Hands-on experience in orchestrating complex data transformations (e.g. Airflow, Dagster, dbt)
• Strong software engineering practices (version control, testing, code reviews, CI/CD)
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders

What Will Make You Standout (Preferred Qualifications)

• Experience in energy, climate tech, or related domains (not required)
• Familiarity with optimization methods or operations research
• Experience developing probabilistic forecasting models and quantifying uncertainty
• PhD in a quantitative field

What Makes Verse a Great Place to Work? 

• Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
• Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
• Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
• Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations

Base Pay Range

$146,000 - $172,000

This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.

Benefits and Employee Perks 

• Competitive compensation and equity grant at a high-growth start up 
• Comprehensive benefits package including medical, dental and vision insurance, and 401k 
• Flexible hours and unlimited PTO 
• Diverse and inclusive working environment 

Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.

About the Role

Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.

What You’ll Accomplish

• Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.
• Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.
• Implement and optimize systems that process and deliver billions of messages daily.
• Improve code quality through code reviews, testing, and advocating for best practices.
• Identify and address technical debt to ensure the long-term health of our codebase.
• Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.

Your Expertise

• 5+ years of professional experience in software development focusing on backend systems.
• Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.
• Experience building and maintaining scalable, high-performance applications.
• Proven ability to collaborate effectively with cross-functional teams.
• Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.

Nice to Haves

• Experience with service-oriented architecture and distributed systems.
• Familiarity with AWS services and cloud infrastructure.
• Knowledge of databases such as DynamoDB, Postgres, or Redis.
• Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).
• Familiarity with frontend development with React and TypeScript.
• Experience with DevOps practices and tools such as Docker and Kubernetes.

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
• Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $190,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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About the role

Are you passionate about using data to shape the future of Faire's product features for small and medium businesses (SMBs)? If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly.

Join us and be part of a team that values data-driven innovation and excellence.

What You Will Do

The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. 

• Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
• Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap.
• Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
• Optimize processes for operational excellence in project management and system reliability.
• Ensure security standards are met within data systems and workflows. 
• Ensure and promote data quality standards for accurate and reliable insights.
• Embrace emerging technologies with enthusiasm.

Minimum qualifications

• 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
• Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
• Production-level development experience in Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
• Experience with Airflow, Docker, DBT or similar analytics workflow tools.
• BA/BS degree in Computer Science, Math, Physics, or a related technical field.

Salary Range

Toronto: the pay range for this role is $171,000 to $235,500 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About the role

Are you passionate about using data to shape the future of Faire's product features for small and medium businesses (SMBs)? If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly.

Join us and be part of a team that values data-driven innovation and excellence.

What You Will Do

The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. 

• Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
• Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap.
• Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
• Optimize processes for operational excellence in project management and system reliability.
• Ensure security standards are met within data systems and workflows. 
• Ensure and promote data quality standards for accurate and reliable insights.
• Embrace emerging technologies with enthusiasm.

Minimum qualifications

• 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
• Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
• Production-level development experience in Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
• Experience with Airflow, Docker, DBT or similar analytics workflow tools.
• BA/BS degree in Computer Science, Math, Physics, or a related technical field.

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About ROLLER

ROLLER is not your average software-as-a-service company. With a global presence in over 30 countries, we're here to bring some excitement to the leisure and attractions industry and make a difference! Our mission is to help businesses operate smoothly and create fun and memorable guest experiences by providing seamless ticketing, point-of-sale, self-serve kiosks, memberships and digital waiver processes.

But here's the best part: our team. We're a group of 300+ highly passionate, enthusiastic, and down-to-earth professionals located all around the world who are all working together to build something truly remarkable. We're aiming high and believe that the possibilities are endless. As we continue to grow globally, we're excited to write our success story and have fun along the way.

We genuinely love what we do, and we're looking for like-minded people to join us on this amazing journey. If you're ready to be part of a dynamic team and make a real impact, come aboard, and let's create some unforgettable experiences together at ROLLER!

About the Role

We are seeking a highly technical, hands-on Senior Data Engineer to architect and scale our data infrastructure from the ground up. As a core member of the data function within our Business Technology team, you will be responsible for building the pipelines and models that power smarter decision-making and operational efficiency across the entire organization.

In this foundational role, you will build & architect the modern data stack, ensuring our infrastructure is robust, automated, and governed. You collaborate as a technical partner with GTM ,Product, Finance, P&C to build high-performance data models and pipelines that transform raw data into actionable cross-functional insights.

Joining ROLLER at this pivotal growth stage, you will have the opportunity to make an outsized impact on our technical landscape, directly influencing how we process data to deliver world-class experiences for our customers globally.

What You'll Do

• Scalable Architecture: Design and implement robust Data Modeling and Architecture strategies that support high-volume data processing and maintain long-term scalability.
• Cloud Ecosystem: Develop and manage end-to-end data pipelines using Google Cloud Platform services, specifically leveraging Cloud Run, Cloud Function for compute, BigQuery for storage, and Cloud Composer (Airflow) for orchestration.
• Transformation Excellence: Build, maintain, and document complex data transformation layers using DBT (Data Build Tool) to ensure high data quality and reliability.
• Infrastructure as Code: Automate the provisioning of cloud resources using Terraform and streamline deployment workflows via GitHub Actions CI/CD pipelines.
• Cloud Data Warehousing: Demonstrate expert-level proficiency in managing and optimizing Cloud Data Warehouses, such as Snowflake & BigQuery.
• Team Collaboration: Partner with cross-functional stakeholders to build and scale high-performing data infrastructure that supports engineering, analytics, and Data Program needs.
• Stack Management: Architect and maintain a modern data stack by implementing best-in-class tools including Snowflake, Bigquery, dbt, Fivetran, Looker, Tableau and Airflow.
• Pipeline Engineering: Develop scalable ETL/ELT workflows and robust data models to deliver real-time analytics and unified business reporting.
• Data Visualization: Create and maintain intuitive, high-performance Looker dashboards will be an added advantage.

About You

You are a technical builder who views data as a competitive advantage. You thrive in fast-paced environments and have a proven track record of engineering scalable data foundations from the ground up. Equal parts architect and analytical problem-solver, you excel at balancing long-term technical vision with the daily hands-on execution of complex pipelines.

You are energized by the full lifecycle of data—moving beyond just writing code to actively leading project discovery and analysis alongside cross-functional partners. You take pride in enabling GTM, Product, Finance & P&C teams through clear insights and high-performance systems. Most importantly, you are excited to act as a founding technical force for a high-growth SaaS company that is transforming the guest experience for attractions businesses globally.

• 5+ years of experience in Data & Analytics or Data Engineering with a focus on Scalable cloud driven data pipeline build

• Proven experience in dimensional modeling (Star/Snowflake schema) and designing architectures that support both historical reporting and real-time needs.
• Expert-level proficiency in Snowflake or BigQuery, including performance tuning, cost optimization, and access control (RBAC).
• Hands-on experience with Google Cloud Platform services, specifically Cloud Function, Cloud Run for containerized workloads and Cloud Composer for orchestration.

• Through hands-on experience of dbt (Data Build Tool) to manage transformations, including writing custom macros, implementing tests, and generating documentation.
• Solid experience using Terraform to provision cloud resources, ensuring that infrastructure is version-controlled and reproducible.
• Proficiency in GitHub Actions to automate testing and deployment pipelines for data models and infrastructure.
• Ability to design high-performance dashboards that prioritize user experience and fast load times.

• Experience collaborating with Finance, GTM, and Product to define key metrics (like CAC, LTV, or Churn) and codifying them into the data layer.
• Familiarity with data ingestion tools like Fivetran , Airbyte, Workato, Mulesoft to sync data from various SaaS platforms into the warehouse.

• Operates as a full-stack Data Engineer with the technical authority to architect and build entire data lifecycles, from raw source ingestion to high-impact data visualization.
• Familiarity with business-critical systems like Salesforce, Chargbee, Gainsight, and product analytics tools.
• Strong communicator with a track record of working across technical and non-technical teams to drive alignment.
• You have a high appetite for Technology and AI and a natural curiosity for how it can transform your work. You’re comfortable using AI tools to automate repetitive 'busy work,' freeing you up to focus on high-impact work.

We believe AI is a career-defining inflection point. ROLLER is a fast adopter of new technology like AI, and every team member is empowered to own their learning and use the latest tools to supercharge their impact. We’re looking for candidates with the proficiency and curiosity to embrace AI and technology — not just as a technical skill, but as a core competency to help us achieve big goals

Preferred Qualifications

• Experience partnering with IT or Business Technology teams to drive cross-functional outcomes.
• Exposure to customer success and revenue workflows, such as onboarding journeys, renewal metrics, or support analytics.
• Familiarity with AI/ML pipelines and experimentation frameworks that support data-driven innovation.

Perks!

• You'll get to work on a category-leading product that customers love in a fun, high-growth industry! Check our Capterra and G2 reviews.
• ROLLER Recharge days to celebrate and recharge once we've hit our goals
• Engage in our 'Vibe Tribe' - led by our team members; you can contribute to company-wide initiatives directly. Regular events and social activities, fundraising & cause-related campaigns...you name it. We're willing to make it happen!
• Team Member Assistance Program to proactively support our team's health and wellbeing - access to coaching, education modules, weekly webinars, and more.
• 16 weeks paid Parental Leave for primary carers and 4 weeks paid Parental Leave for secondary carers.
• Work with a driven, fun, and switched-on team that likes to raise the bar in all we do!
• Individual learning & development budget plus genuine career growth opportunities as we continue to expand!

What You Can Expect

1. Initial call with our Talent Acquisition Manager
   You'll have an initial call with our Talent Acquisition Manager to chat through some of your experience to date, salary expectations and you can check off any initial questions you might have.
2. Interview with the Hiring Manager
   You'll get to meet with the hiring manager to learn more about the role & ROLLER whilst also talking through your experience in more detail.
3. Loop Interviews
   This is where you will get to meet our wider ROLLER team to do a 'vibe check' on us to make sure our culture & vibe meet what you are looking for!
4. Offer
   If all lights are green and the fit feel right, we'll conduct reference checks and you'll receive an offer to join!

AI Engineer
Location: San Francisco, CA, in-office
Compensation: 150,000 – $210,000
Company: Cargomatic, Inc.

Disruptive, groundbreaking, transformative company is changing an industry

Join a rapidly growing company disrupting the trucking industry! Cargomatic is the #1 technology platform and digital marketplace for powering world-class, local trucking. Take a look around you. Literally everything humans build, grow, or sell has spent time on a truck. Local trucking is the lifeblood of every regional economy, and yet this $82 billion industry still relies heavily on phone calls and fax machines. Cargomatic is transforming the way goods move around every local node in the supply chain by connecting shippers and commercial truck drivers with mobile technology. We are solving complex, real-world problems every day, and giving full transparency to the shipping process. 

AI Engineer- Rapid Prototyping & Automation

Cargomatic is seeking a highly hands-on AI Engineer who thrives in fast-paced environments and is passionate about rapid prototyping and deploying standalone AI-driven applications. This role focuses on building agentic AI systems and automation tools that can operate independently, integrate with our ecosystem, and deliver immediate business value.

You will work at the intersection of AI, product development, and infrastructure- quickly turning ideas into working prototypes and scaling the most promising solutions into production.

Key Responsibilities:

• Rapidly design, prototype, and deploy standalone AI applications that solve real-world logistics and operational challenges
• Build and implement agentic AI systems capable of autonomous decision-making and task execution
• Develop AI-powered automation tools to streamline workflows across operations, customer experience, and internal processes
• Leverage modern LLM ecosystems, including Claude-based and code-first AI frameworks, to build intelligent agents and workflows
• Integrate LLMs, APIs, and data pipelines into production-ready services
• Collaborate with product, engineering, and operations teams to identify high-impact opportunities for AI solutions
• Iterate quickly based on feedback, performance metrics, and evolving business needs
• Ensure scalability, reliability, and security of AI systems in production environments
• Stay current with advancements in AI/ML, especially in agent frameworks, Claude/OpenAI ecosystems, and automation tooling (e.g., n8n)
• Implement guardrails, validation layers, monitoring, and evaluation frameworks to mitigate hallucination, prompt injection, and data security risks.
• Collaborate cross-functionally with Product, Engineering, and Operations to translate business needs into scalable AI-enabled solutions.
• Contribute to architectural standards, technical best practices, and innovation initiatives.

Preferences:

• Strong product builder mindset with an ability to prioritize high-impact solutions
• 3+ years of experience in software engineering, with a focus on AI/ML or automation
• Proven experience building and deploying AI-powered applications or prototypes end-to-end
• Strong understanding of agentic AI concepts, LLMs, and modern AI frameworks
• Hands-on experience with Claude (Anthropic), OpenAI, or similar LLM APIs, including prompt design and orchestration
• Experience with code-based AI frameworks (e.g., Claude tool use / function calling, LangChain, AutoGen, CrewAI, or similar)
• Experience building or orchestrating workflows using n8n (or similar tools like Zapier, Temporal, Airflow)
• Experience with event-driven architectures and real-time systems
• Familiarity with vector databases and retrieval-augmented generation (RAG)
• Proficiency in backend development using Node.js
• Experience with frontend frameworks such as React for building lightweight interfaces
• Hands-on experience with cloud infrastructure, particularly AWS (Lambda, ECS, S3, etc.)
• Familiarity with databases such as MongoDB and RDS (PostgreSQL/MySQL)
• Experience integrating third-party APIs and building microservices
• Ability to move quickly from concept → prototype → production
• Active GitHub contributions or demonstrated passion for emerging technologies in AI and data systems.

Benefits & Perks:

• Competitive compensation
• Medical, dental, and vision benefits
• 401K company match program
• Flexible paid time off (PTO) and paid holiday

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.

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 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.

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

About the Role:

We are looking for a Senior Software Engineer to architect, build, and maintain the data infrastructure at Gusto.  As part of the Data Platform team, you will collaborate closely with Data Science, Business Intelligence, and analysts across Gusto teams to help them achieve their goals. 

The Data Platform position is a software development role with knowledge of data architectures and data delivery. The ideal candidate is passionate about developing software, working with data, and

Here’s what you’ll do day-to-day:

• Architect, build, and refine our infrastructure and tools that enable other teams to work with data.
• Efficiently handle vast amounts of clickstream, database, and third party application data, processing in batch and real-time
• Take full ownership of the solutions you build, working with stakeholders to develop requirements, implement solutions, monitor production, and troubleshoot problems that arise.
• Work as part of a team. We value team players who share their knowledge and like collaborating with others.

Here’s what we're looking for:

• • At least 7 years of software engineering experience.
  • Experience building solutions in the cloud, AWS preferred (Redshift, MSK, EMR).
  • Experience with OLAP databases (Clickhouse)
  • Experience building data pipelines at scale, Airflow and Python preferred.
  • Experience with streaming systems desired (Kafka, Kinesis, or similar).
  • Ability to turn vague requirements into clear deliverables with minimal guidance.
  • Experience building and maintaining a modern data stack in production.

Our cash compensation amount for this role is targeted at $163,000-$204,000/year in Denver, $178,000-$223,000/year in Los Angeles, and $197,000-$247,000/year for San Francisco, New York, and Seattle. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

The Role

Analytics Engineering at Flex sits at the intersection of Data, Product, Engineering, and business objectives. As Director, Analytics Engineering you will run the team that enables stakeholders at Flex to easily find the data they need to make decisions. You’ll be responsible for developing a world-class analytics platform that powers all data consumption at Flex, as well as managing and developing a team of high-performing Analytics Engineers. You'll also be hands-on, leveraging your technical skills to develop data models and build better data products and solutions. You'll partner with analysts, engineers, PMs and others to define the requirements while being accountable for delivering the end data product.

You Will:

• Develop and lead strategy for data modeling platform and team roadmap
• Manage and mentor a team of Analytics Engineers
• Collaborate with leaders across product & engineering teams to define data requirements and inform architecture/schema design decisions
• Lead the development of data models to consume, transform, and expose data to stakeholders and systems across the company
• Collect business requirements, define successful analytics outcomes, and design data solutions
• Set company-wide standards for data regarding structure, quality, and expectations
• Contribute Flex’s data culture by influencing processes, systems, and tools that enable to make better decisions in a scalable way

You Have:

• 8+ years as an analytics engineer or equivalent, with a track record of shipping high quality products and features at scale
• Expert knowledge of SQL, data warehouses (we use Snowflake), and how to write efficient SQL queries
• Familiarity with common BI tools (preferably Sigma Computing, Tableau, Mode, etc.)
• Expert proficiency with dbt, dbt Cloud, and Airflow
• Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, and best practices for codebase development and CI/CD)
• Proficiency with Python preferred
• Experience within the fintech space preferred

Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area.  

Tier A (NYC/SF/Seattle): $240,000-290,000
Tier B (Austin, Washington D.C. Philadelphia, Los Angeles, San Diego, Chicago, Miami, Atlanta : $215,000-265,000
Tier C (SLC/All Other States): $200,000-250,000

Offices

Roles posted in New York, San Francisco, or Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program.

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.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

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 $162,800 - $203,500, 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.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

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 $149,780 - $187,220, 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.

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.

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.

We are looking for a Staff Security Software Engineer who is passionate about detecting and mitigating abuse in the Cloud. 

As a Staff Security Software Engineer at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. This role reports to the Senior Manager of Security Engineering within the Security organization. You should have experience developing and maintaining software systems in a complex, high-scale environment, analyzing outcomes and communicating insights to stakeholders, and rapidly devising solutions that are in alignment with overall business goals. Our team is focused on enabling DigitalOcean to scale safely by building systems that detect and prevent abuse on our platform. We highly value collaboration and growth, and work closely with other teams in the Security organization to deliver high quality solutions and also build tooling to boost their efficiency.

Our customers trust us with their data and operations, and we take that responsibility seriously. Security at DO means solving highly complex problems on a large scale that have real impact for our customers, our products, and for the larger internet community.

What You’ll Do:

• Design, develop, and deploy resilient services and tooling that provide security capabilities at scale, primarily in Go, with some work in Javascript and Python.
• Research and design automated approaches to detecting and actioning abuse and misuse of DigitalOcean products and services.
• Work with product and engineering teams to design and implement secure architectures.
• Design and build internal tools that enable our Security Operations Center to do more, faster.
• Measure the efficacy of our services and tools, using logs, metrics, and audit records, to drive reporting and decision-making, leading to iterative and transformative security improvements as DigitalOcean scales. All while being mindful that security should be an efficiency enabler for the business, not an obstacle.

What You’ll Add to DigitalOcean:

• 8+ years of hands-on experience in software engineering projects, ideally with a security focus, in a complex, high-scale SaaS or IaaS environment. You are an expert in writing robust code with good test coverage and demonstrated success in delivering projects.
• Understanding of cloud-native services and infrastructure provisioning (e.g. compute, storage, networking).
• Deep familiarity with cloud services & infrastructure—compute, storage, network, managed services—and related abuse tactics, including DDoS, spamming, phishing, cryptomining, and bot networks.
• Strong analytical and reporting skills, with proficiency in SQL and data warehouse querying (e.g., Snowflake, Redshift, BigQuery)
• A customer-first mindset—you aim to maximize abuse prevention while avoiding false-positives that could impact high-value customers.
• Excellent communication and documentation skills; you can clearly articulate patterns, mitigation strategies, and tradeoffs to both technical and non-technical stakeholders. You have a record of partnering with internal engineering teams and non-technical stakeholders to gather requirements and tackle security problems across an entire stack with empathy and creativity.
• High integrity, strong judgment, and a track record of working independently on high-impact investigations and policy decisions.

Bonus qualifications:

• Experience with microservice architectures, asynchronous and event-driven processing, and synchronous gRPC/HTTP-based requests.
• Experience in building secure by default services and applications.
• Familiarity with technologies such as gRPC, Docker, Elasticsearch, Prometheus/VictoriaMetrics, Kubernetes, and GitHub Actions.
• Experience with Looker, Snowflake, dbt, and Airflow

Compensation Range: 

• $199,680 - $249,600

*This is a remote role

#LI-Remote

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

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 Software Engineer (MLOps) to own the scaling, reliability, and deployment of our machine learning workloads. You will build the computational backbone to accelerate, scale, and productionize our ML research, serving as the critical bridge between frontier research and production-grade engineering.

If you are passionate about standardizing ML infrastructure, conquering complex distributed systems challenges, and being the core glue that wires up modern toolchains, this is the role for you.

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

Key Responsibilities:

You will work with a team of researchers and engineers on Calico’s key strategic cross-functional drug discovery and development initiatives through the following responsibilities:

• Architect the Computational Engine: Design, build, and deploy highly scalable distributed training environments and evaluate and establish the company-wide blueprint for orchestration systems and infrastructure for therapeutic discovery and development
• Build the Serving Infrastructure: Architect the high-throughput inference and serving pipelines necessary for our models to propose and evaluate synthesis recommendations
• Define the MLOps Standard: Architect and implement rigorous, automated systems for ML experiment tracking, model versioning, checkpointing, and artifact registries, ensuring our path to drug discovery is fully reproducible and data-driven
• Mentorship & Leadership: Serve as a subject matter expert and technical mentor, including partnering with our researchers and academic partners to integrate their research into our production pipelines

Position Requirements:

• A strong intellectual curiosity for life sciences
• 5+ years of relevant work experience in industry or academia
• Strong software engineering skills with deep expertise in Python and JAX or PyTorch
• Hands-on experience with MLOps practices (e.g., model registries, monitoring, CI/CD for ML pipelines) and modern open-source tools (e.g., Ray, Kubernetes, MLflow, Airflow, Flyte)
• Must be willing to work onsite at least four days a week

Nice to Have:

• Hands-on experience troubleshooting distributed training bottlenecks
• Prior experience productionizing ML models for biological or molecular data
• Contributions to open-source projects or academic publications in ML

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.

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role:

This role is ideal for engineers who thrive on complex distributed systems and have deep experience with backend APIs, relational databases, and event-driven architectures. You’ll build high-performance, reliable solutions across cloud-native platforms and global infrastructure for a fast-scaling, commerce-driven company.

Responsibilities

• Identify, design, and develop foundational backend services that power Fal's commerce platform

• Partner with product teams to understand functional requirements and deliver solutions that meet business needs

• Write clear, well-tested, and maintainable software and IaC for both new and existing systems

• Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure

• Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance

Requirements

• 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices

• Expert-level programmer in one or more of Python, Go, Or Rust

• Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources

• Proficiency in writing and maintaining Infrastructure as Code (IaC)

• Proficiency in version control practices and integrating IaC with CI/CD pipelines.

• Experience with payment processors (e.g. Stripe) and billing systems a plus

• Experience with Kubernetes, or containers a plus

• Experience building and operating data infrastructure (Kinesis, Airflow, Kafka, etc) a plus

What we offer at fal:

• Interesting and challenging work

• Competitive salary and equity

• A lot of learning and growth opportunities

• We offer relocation assistance to San Francisco.

• Health, dental, and vision insurance (US)

• Regular team events and offsite

Compensation:

• $180,000 - $250,000 + equity + comprehensive benefits package

Location:

• We are currently hiring in downtown San Francisco.

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role:

As a Senior Data Scientist for Product Intelligence, you will architect the analytical foundation for how fal builds and grows. Your domain spans the entirety of the developer journey—from initial acquisition to long-term expansion. You will turn raw behavioral and system signals into the metrics and insights that shape our product roadmap and go-to-market strategy.

This is a high-influence role where you will act as a strategic partner to Product, Engineering, and Marketing. Beyond domain-specific analysis, you will share ownership of the foundational data systems, standards, and experimentation frameworks that serve as the source of truth for the entire company.

What you’ll do

• Architect the metrics that define user success on fal and build the measurement systems to track activation, retention, and time-to-value across both our self-serve and B2B pipelines.
• Develop a deep, causal understanding of how customers discover, adopt, and grow on the platform to identify key expansion levers and acquisition opportunities.
• Own the instrumentation standards and data contracts that serve as the source of truth for product telemetry and core behavioral schemas.
• Surface insights through rigorous deep-dives and experimentation to influence product direction, pricing models, and go-to-market initiatives.
• Develop scalable data products including automated experimentation frameworks and canonical schemas that enable teams to self-serve and move faster.

What we are looking for

• 5+ years of experience in data science or analytics roles-ideally with API products, developer tools, or B2B SaaS platforms
• Advanced-level SQL and proficiency in Python for analytics, modeling, and experimentation
• Strong proficiency with dbt and orchestration tools like Dagster or Airflow for production pipeline
• Proven ability to work across teams to influence product roadmap and strategy
• Experience establishing data quality and governance practices, including lineage, testing, and documentation.
• Demonstrated bias for action and the ability to thrive in fast-moving, ambiguous environments.
• A track record of shipping data products or features, not just dashboards. You think like a Product Manager and build like an Engineer

Nice-to-haves

• Experience working on developer-facing products or platforms.
• Exposure to infrastructure, performance, or cost-related data (e.g., cloud usage, compute efficiency).
• Experience operating in early-stage or fast-scaling environments.
• Interest or experience in architecting data systems designed for agentic consumption and AI-driven product workflow

Compensation

• $190,000 - $230,000 + equity + comprehensive benefits package

What we offer at fal

• Interesting and challenging work
• A lot of learning and growth opportunities
• We offer visa sponsorship and will help you relocate to San Francisco.
• Health, dental, and vision insurance (US)
• Regular team events and offsites