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

The Stream Compute team at Stripe builds and operates the infrastructure, tooling, and systems behind our Flink-powered stream processing systems. We're at the heart of several core asynchronous workflows, operating at significant scale and handling vast amounts of sensitive financial data. Our work powers intricate processes involving various critical financial operations and real-time analytics. We run globally distributed systems with high reliability and performance to meet Stripe's scaling, availability, and product needs, and we continually reduce operational toil by investing in automation and self-service tooling for upgrades, maintenance, and day-to-day operations. The team is distributed between Seattle, Toronto and remote locations.

What makes our team truly exciting is our commitment to our users: we ensure no event is dropped, state integrity is preserved, and support exactly-once processing as a first-class feature. Working at the intersection of real-time data processing and fintech innovation, we continuously push the boundaries of what's possible. Our focus on innovation, user experience, reliability, and compliance drives increased ROI and operational excellence, making us a crucial part of Stripe's success.

What you'll do

You'll help define and deliver the next generation of Stripe's Flink-first stream compute infrastructure—driving innovation to meet extremely high availability targets at global scale. Partnering with infrastructure engineers, adjacent platform teams, and the product orgs that depend on Flink every day, you'll set a long-term technical direction that scales with Stripe's growth while enabling reliable, efficient operations for years to come. You'll work on the hardest problems in operating Flink in production—state management, exactly-once processing, performance isolation, and automated recovery—so teams across Stripe can confidently build stateful stream processing applications on top of it.

Responsibilities

• Design, build, and operate stream compute infrastructure with Apache Flink at the center, alongside technologies like Kafka, Temporal, and AWS services
• Partner with product and platform teams across Stripe to understand requirements, unblock Flink adoption, and improve how stream processing infrastructure is used end-to-end
• Define and implement operational best practices (e.g., shuffle sharding, cellular architecture, load shedding, automated state recovery) to improve resilience and reliability at scale
• Drive fleet-level automation and standardization ("pets" to "cattle") through self-service workflows, safer rollouts, and self-healing systems that reduce manual operations
• Lead initiatives that raise the bar on Flink availability and state durability (e.g., multi-region strategies, disaster recovery readiness, operational readiness reviews, incident learning)
• Evaluate and productionize Flink ecosystem capabilities (e.g., SQL, connectors, state backends) to improve developer experience and scalability without compromising reliability
• Work closely with the open source community to identify opportunities for adopting new open source features as well as contribute back to OSS

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

• This is a Staff-level role - that typically means 10+ years of experience building, operating, and evolving large-scale production systems
• Experience as a technical lead for team(s) working on distributed systems, including scaling them in fast-moving environments
• Hands-on experience with big data technologies such as Flink, Spark, Kafka, Pulsar, or Pinot
• Experience developing, maintaining and debugging distributed systems built with open source tools
• Experience building and scaling infrastructure as a product
• Strong software engineering skills and a passion for Big Data Distributed Systems
• Ability to write high quality code (in programming languages like Go, Java, Scala, etc)
• Comfortable operating with high autonomy and ownership
• Growth mindset and a willingness to learn quickly, explore ambiguous problem spaces, and dive deep when needed
• Strong written and verbal communication skills, including the ability to produce clear technical documentation

Preferred qualifications

• Experience operating streaming infrastructure as a platform (e.g., Flink clusters, Kafka, Pulsar) for internal customers at scale
• Deep hands-on experience authoring, optimizing, and operating real-time processing frameworks such as Flink, Spark Streaming, Storm, or Kafka Streams in production
• Experience building or operating control planes for managing large-scale infrastructure
• Open source contributions to data processing or big data systems (Hadoop, Spark, Celeborn, Flink, etc)

About the team

The Product Security Data Platforms team is a newly established engineering team within Stripe Security. Our mission is to build the foundational infrastructure that provides our users with unprecedented visibility into the security posture of their Stripe integration. While Stripe is renowned for industry-leading payment protection, we are expanding our focus to provide a comprehensive security telemetry platform that helps businesses protect their entire digital ecosystem on Stripe.

As a founding member of this team, you will be architecting a large-scale customer-facing security data pipeline and presentation layer. Much like modern security observability platforms and data lakes that have transformed cloud infrastructure, we are building an API-first service that transforms massive streams of behavioral data into actionable security intelligence. This team operates at the intersection of high-throughput data engineering and cybersecurity, creating the systems that will allow the world’s most sophisticated companies to monitor, detect, and respond to threats in real-time.

What you’ll do

As a Senior Software Engineer on this founding team, you will lead the technical design and implementation of our core security data pipelines. You will be responsible for defining how security signals are captured, processed at scale, and delivered to our users through robust, developer-friendly interfaces. If you have security domain knowledge, there are significant opportunities for you to help shape product vision.

Responsibilities

• Architect Scalable Foundations: Design and implement a highly available, low-latency pipeline capable of processing and augmenting millions of events per second into structured security telemetry.
• Build API-First Products: Develop the core services and streaming APIs that enable enterprise customers to seamlessly ingest security signals into their own internal security operations centers and analytics tools.
• Engineering Security Signals: Partner with security researchers and threat detection experts to build the logic that identifies anomalous behavior and surfaces high-fidelity security insights.
• Define Technical Strategy: Lead the technical roadmap for the platform, making critical decisions on data modeling, storage strategies, and the abstraction layers that will support future security products.
• Drive Engineering Excellence: As a senior leader, you will set the bar for code quality, system resilience, and operational maturity for a product that requires 99.99%+ availability.
• Cross-functional Collaboration: Work closely with Stripe’s core platform and data teams to leverage global infrastructure while ensuring security data remains isolated and protected.

Who you are

We are looking for an experienced backend and systems engineer who thrives on building new products from scratch. You should have a deep background in distributed systems and a passion for building platforms that empower other developers and security professionals.

Minimum requirements

• 8+ years of professional software development experience, with a history of shipping and maintaining complex, large-scale systems.
• Expertise in Data Engineering & Distributed Systems: Deep experience building and operating high-throughput data pipelines (e.g., Kafka, Flink, Spark, or similar streaming technologies).
• Strong Programming Fundamentals: Significant experience in languages like Java, C++, or Rust.
• System Design Leadership: A proven track record of designing robust, scalable architectures and leading cross-team technical initiatives from conception to launch.
• Operational Mindset: Experience maintaining mission-critical services with high availability requirements, on-call rotation, and a strong focus on observability and debugging.
• Communication & Collaboration: Excellent technical writing skills for drafting design documents and the ability to mentor other engineers while collaborating with non-technical stakeholders.

Preferred qualifications

• Security Domain Knowledge: Prior experience building security analytics, threat detection systems, or observability platforms.
• Platform Engineering: Experience building "as-a-service" infrastructure where the primary users are other engineers or external developers.
• Cloud Native Infrastructure: Prior experience with AWS, Kubernetes, and infrastructure-as-code (Terraform).
• Product Intuition: A desire to work on "0-to-1" initiatives where you help define the product requirements and user experience alongside engineering.
• Front-end / Full Stack Experience: Prior React / TypeScript frontend experience is helpful

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.

The Team + The Role

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

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

This is a remote role supporting a West Coast territory. 

What this looks like day-to-day

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

Who You Are

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

You're a builder, not a maintainer.

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

You're AI-curious - genuinely.

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

Must-haves

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

Nice-to-haves

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

About Pendo

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

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

Location: Remote

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

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

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

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

About The Role

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

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

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

Key Responsibilities

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

Primary Qualifications

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

Nice to Have

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

Additional Information

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

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

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

#LI-HYBRID

#LI-ZZ1

We’re looking for a Staff Software Engineer to help us build a high-performance, efficient, and easy to use batch processing platform and infrastructure at Pinterest. You’ll be working on some of the most exciting big data open source technologies such as Spark, Presto/Trino, Iceberg, etc. at the scale of hundreds of petabytes of data to bring everyone the inspiration to create a life they love. 

What you’ll do:

• Design, implement, and optimize Pinterest’s batch processing infrastructure.
• Collaborate with cross-functional teams to understand data needs.
• Lead technical projects and initiatives, driving them to completion.
• Mentor and guide junior engineers on best practices and architecture.
• Ensure the reliability, scalability, and efficiency of data systems.

What we’re looking for:

• 6+ years of experience building and supporting large scalable big data infrastructure/platforms
• Extensive experience with big data query technologies such as Spark SQL or Presto/Trino.
• Proven skills in designing and maintaining scalable data infrastructure.
• Proficiency in programming languages like Java, Scala, or Python.
• Strong problem-solving abilities and a drive for innovation.
• Excellent communication skills and the ability to collaborate across teams.
• Bachelor's degree in a relevant field such as Computer Science or Engineering, or equivalent experience.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times/quarter, and therefore can be situated anywhere in the country. 

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  
  

#LI-REMOTE
#LI-AH2

Location Details: 

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.  

This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands.

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us...  GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us. 

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way. 

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com. 

Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

About the Role

The Ads Applied Data team builds and scales the foundational data infrastructure that powers Moloco’s advertising platform. As a Senior Software Engineer, you will design, develop, and optimize distributed data systems for real-time and batch processing, ensuring reliable and low-latency delivery of data across the ads ecosystem. You’ll work closely with Product, ML, and Data Science teams to enable feature engineering, identity resolution, and advanced user signal enrichment across online and offline pipelines.

Responsibilities

• Design and build large-scale distributed systems for data ingestion (Petabyte-scale), transformation, and serving.
• Partner with ML and Serving teams to support feature engineering workflows, connecting offline data to serving systems.
• Contribute to the evolution of Feature Infra / Feature Store, ensuring scalability, discoverability, and consistency of feature data.
• Collaborate on Identity Graph construction to unify user and device identifiers for more effective signal enrichment and targeting.
• Improve system observability, resilience, and performance in high-throughput, low-latency environments.
• Mentor engineers and help define best practices for data and backend engineering.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, or equivalent technical field.
• 5+ years of software engineering experience with one or more modern languages (Java, Kotlin, Go, C++, C#, or Python).
• Proven experience designing and building large-scale distributed systems and backend services.
• Hands-on experience with data processing frameworks such as Apache Beam, Dataflow, or Spark, and orchestration tools like Airflow.
• Strong understanding of cloud infrastructure (GCP, AWS, or Azure) and data storage technologies (BigQuery, Bigtable, Redis, GCS, Kafka, Pub/Sub).
• Demonstrated experience delivering impactful projects through collaboration with cross-functional teams (Product, ML, Data Science).

Preferred Qualifications

• Experience with Feature Infra / Feature Store architecture and operations.
• Experience in Identity Graph design and construction to enhance user signal quality.
• Deep familiarity with AdTech or Machine Learning infrastructure domains.
• Experience working with Petabyte-scale data and high-availability systems.

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems. 

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

• Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
• Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

• Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work: 

• Your ethos is ownership
• You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.
• You demonstrate strong judgment under uncertainty. 
• You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.
• You lead through clarity and active listening. 
• You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions. 
• You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope. 
• You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.
• You fall in love with the problem, not the solution
• You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem. 
• When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook. 
• You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

SLSQ227R297

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

The impact you will have:

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

What we look for:

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

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.

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 hybrid role

JR: 2026-7683

#LI-Hybrid

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

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

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

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

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

The Team + The Role

The Enterprise Sales team at Pendo partners with some of the world’s largest organizations to improve and transform their digital experiences. The team operates in a fast-paced, collaborative environment and works closely with Solutions Engineering, Customer Success, Legal, Product, and executive leadership to drive meaningful business outcomes. Enterprise Sales values clear execution, strong partnership, and disciplined sales practices to win complex enterprise opportunities.

As an Account Director, Enterprise Sales, you will lead complex enterprise deals and own multi-stakeholder sales cycles with organizations of 1,500+ employees. You will build executive relationships, develop multi-year account strategies, generate high-quality pipeline, and apply MEDDPICC and Force Management principles to drive forecast accuracy and long-term customer value.

This is a remote role based in the PacificNW.

What this looks like day-to-day

• Enterprise deal leadership: Act as the internal lead for complex enterprise opportunities, coordinating cross-functional partners across Solutions Engineering, Customer Success, Legal, Product, and executive leadership. You keep the team aligned, the deal strategy clear, and the process moving with urgency and discipline.
• Executive relationship building: Build and maintain strong relationships across the C-suite, IT, and business leadership within organizations of 1,500+ employees. You understand stakeholder priorities and connect Pendo’s value to meaningful business outcomes.
• Value-based selling: Lead sales cycles focused on solving meaningful business problems and supporting digital transformation initiatives. You shape the value narrative, guide customers through complex decisions, and position Pendo as a strategic partner.
• Sales methodology and forecasting: Apply MEDDPICC and Force Management principles to manage complex, multi-stakeholder sales cycles. You maintain strong deal hygiene, identify risk early, and support accurate forecasting.
• Account strategy and expansion: Develop and execute multi-year account strategies that expand Pendo’s presence within enterprise customers. You identify growth opportunities, prioritize high-impact activities, and build plans that deliver long-term customer value.
• Pipeline generation: Consistently generate and maintain a high-quality pipeline through proactive prospecting and account development. You take ownership of pipeline health and create opportunities through disciplined, strategic outreach.
• AI-enabled productivity: Use AI tools and insights to improve sales preparation, productivity, and customer engagement. You look for practical ways to work faster, communicate more effectively, and make better decisions in a fast-moving environment.

Who You Are

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

You're a builder, not a maintainer.

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

You're AI-curious - genuinely.

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

Must-haves

• Proven track record of success in enterprise software sales, including SaaS or application software, selling into organizations with 1,500+ employees.
• Experience using MEDDPICC and/or Force Management to manage complex, multi-stakeholder sales cycles.
• Demonstrated ability to generate pipeline independently through strategic prospecting and account development.
• Experience leading cross-functional deal teams across Solutions Engineering, Legal, Customer Success, and executive stakeholders to close enterprise agreements.
• Comfort using AI tools to improve sales efficiency, preparation, and customer engagement.

Nice-to-haves

• Experience working in a startup or high-growth environment where you navigated ambiguity and built new processes or approaches.
• Success selling emerging or innovative technologies that required educating the market and shaping the value narrative.
• A track record of perseverance and resilience in professional or personal pursuits.
• Demonstrated ability to mentor peers and contribute to the overall development of the sales organization.

About Pendo

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

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

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

Compensation: The expected On-Target Earnings (OTE) range for this role is $280K-$320K, with a 50/50 base-to-variable compensation split.

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

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

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

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

ABOUT BEZOS ACADEMY

At Bezos Academy, we believe all children deserve the great start that excellent early education provides, including in under-resourced communities. Our mission is to nurture the potential in every child to become a creative leader, original thinker, and lifelong learner by inventing the solutions needed to scale early childhood education. We are a unique organization that realizes our mission in two ways. First, we operate a multi-state network of schools in under-resourced communities, offering quality Montessori-inspired preschool at no cost to families. Second, we create tools, products, technology, and other solutions designed to reach young children and their caregivers well beyond the walls of our schools. We aspire to have a profound, large-scale impact on children ages zero to five. At Bezos Academy, we are committed to expanding access to play-focused preschool education in underserved communities, aiming to improve long-term educational, social, and developmental outcomes in ways that create meaningful and lasting impact.

ABOUT THE ROLE

As a Senior AI Applications Engineer at Bezos Academy, you will help build AI-powered software applications that support teachers’ abilities to deliver measurable results in early childhood education. As a hands-on, results-driven software developer, you will play a pivotal role in developing intelligent systems for teachers, staff and families with a small product development team. Your products will both thrill and delight their users and enable our national school network to nurture young children’s originality, foster self-agency, cultivate a love for learning, and spark joy.

You have a proven track record of combining machine-learning models, high-quality data, and human-centered workflows into production-ready tools; you consistently deliver solutions that solve human problems. Resourceful throughout the software-development lifecycle—from research and prototyping to deployment, monitoring, and evaluation—you work effectively despite constraints on time and resources. In past roles, you have successfully launched AI-powered applications in collaboration with product-development teams. As a software engineer with a customer mindset, you take pride in applying practical AI workflows and sound software-engineering principles to build high-impact AI products. Adept at working from scratch, you navigate ambiguity, iterate quickly, and shape solutions that earn customer love. Hands-on experience with evaluations, inference validation, and AI guardrails has helped you strengthen the safety, performance, and ethics of AI features. You recognize exceptional work when you see it and instill that same passion in others.

In this role, you will focus on building, measuring, and iterating for children. Motivated equally by great products and great impact, you are deeply inspired by our mission to expand access to quality early childhood education and experiences.

LOCATION

• Washington, Arizona, Florida, Kentucky, or Texas, within two hours’ drive to multiple Bezos Academy preschools (please see our website for-school locations); Seattle, WA preferred.
• Relocation support is available for those willing to relocate to Seattle, WA

COMPENSATION AND BENEFITS

• This is a full-time, benefits-eligible, salaried position.
• The full salary range for this position, across applicable United States geographies, is $157,000 - $298,000 per year. The upper portion of the salary range is typically reserved for employees who have been in the role for multiple years and have demonstrated strong performance over time. Starting salary will vary by location, qualifications, and prior experience.
• This role includes 15 paid days of vacation, 4 days of paid personal time off, 9 paid days of sick (care) time, 9 paid holidays, 5 paid days off for an organization-wide winter break, and additional time off if required by applicable law. Benefits for this role include medical, dental, and vision insurance, life insurance, disability insurance, a 401(k) plan with a 4% employer contribution match, paid parental leave, an employer-matched flexible spending account for dependent care, and more. Please see here for details.

MINIMUM QUALIFICATIONS

• Bachelor’s degree or equivalent experience
• Eight or more years of experience developing and deploying full-stack applications, including two or more years working on AI-powered applications in production environments
• Proficiency in Python for backend development and integrating AI capabilities
• Working knowledge of TypeScript and SQL for full-stack development and data handling
• Experience integrating pre-trained foundation models, including large language models (LLMs) and multi-modal models, into production applications
• Familiarity with model evaluation techniques, such as prompt testing, output validation, and performance monitoring
• Experience with AWS services, especially those relevant to AI applications (e.g., Bedrock, Lambda, EC2, S3, RDS, DynamoDB)
• Understanding of AI safety practices, including inference validation, implementing guardrails, and handling personally identifiable information (PII) and sensitive data responsibly
• Ability to speak, read, and write English fluently
  

PREFERRED QUALIFICATIONS

• Experience with LangChain or similar frameworks for orchestrating LLM workflows and agentic behavior (e.g., tool use, planning, memory)
• Familiarity with AWS AgentCore
• Exposure to vector databases and embedding techniques, especially in retrieval-augmented generation (RAG) workflows
• Experience implementing AWS Bedrock Guardrails or similar safety mechanisms
• Understanding of LLM evaluation strategies, including prompt engineering and human feedback loops
• Experience with DevOps practices, including CI/CD pipelines, test automation, and infrastructure-as-code tools (e.g., AWS CDK)

Please click here for a full job description. 

Bezos Academy participates in E-Verify and will provide the federal government with employee Form I-9 Information to confirm authorization to work in the U.S. Bezos Academy only uses E-Verify once a candidate has accepted a job offer and completed the Form I-9. If E-Verify cannot confirm that an employee is authorized to work, Bezos Academy will give the employee written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so the employee can begin to resolve the issue before any adverse employment action is taken. For more information about your right to work, please see the Notice of Right to Work.

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.

What you’ll do

About the internship

Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

As an intern, you'll tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.

Responsibilities

• Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
• Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
• Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
• Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
• Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.

Who you are

Minimum requirements

• A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
• Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
• Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
• A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
• Intent to return to the degree-program after the completion of the internship/co-op.

Preferred qualifications

You Might Also Have:

• Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
• Published and presented peer-reviewed articles in top-tier venues.
• Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
• Familiarity with navigating new codebases and managing work across different programming languages.
• Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.

Application requirements

Please submit the following with your application:

• A detailed resume or LinkedIn profile showcasing your work history.
• Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.

Join us for an unforgettable summer internship and help shape the future of global commerce. At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

RDQ226R497

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. 

You will be a Sr Product Manager for Unity Catalog (https://databricks.com/product/unity-catalog). Unity Catalog is the metadata and governance foundation for the Lakehouse, providing not only fine grained security and governance capabilities, but also performance and productivity capabilities such as lineage, search, discovery, auditing, and compliance, for our customers' data and AI assets. 

This role is requires coordinating all product activities from vision to implementation, including engaging large enterprise customers to understand their needs, developing long-term product strategy, defining product roadmaps, working with engineering to build those products, and coordinating with various internal stakeholders (both pre- and post-launch) to ensure product success.

The impact you will have:

• Design and launch new governance and security capabilities as part of Unity Catalog.
• Define and build new platform services that enable Databricks’ data & AI product teams (ML/AI, Data Science & Engineering, Data Warehousing, etc.) to easily add new workload-specific governance capabilities that enhance the value of Unity Catalog and the Lakehouse.
• Take new features you envision from ideation / exploration with customers to full launch and rollout, including a marketing plan, field enablement, and broad customer adoption across all our segments.
• Bring insights about the data governance persona, our customers, and the market at large to the engineering and leadership team by working closely with our customers and partners. 

What we look for:

• 5+ years of enterprise B2B Product Management experience
• Educational background in computer science or related engineering practice.
• Experience working with databases and/or data warehouses, security, and catalogs.
• Experience building user-facing products for Data Analysts, Scientists, and/or Engineers.
• Strong track record of delivering products with cross-functional teams common to the enterprise software industry (field engineering, sales, marketing, partnerships, etc.).
• Experience in working closely with enterprise customers and ISV partners in the data market.

SoFi is seeking an experienced and motivated Senior Staff Data Engineer to be the technical leader of our Data Engineering group within the SoFi Data Platform(SDP) division. The mission of the SDP division is to activate data throughout SoFi, enabling the creation of personalized and delightful experiences for our members. 

The Role:

In this role, you will have the opportunity to directly impact, influence and lead the direction and architecture of our next gen AI powered SoFi Data Platform(SDP), and elevate data reliability through AI enabled workflows, tooling and practices. You will get the chance to lead, define, and take on complex and interesting problems as part of a fast-paced, highly collaborative organization. The ideal candidate will be a mentor, technical leader and a team player who is hands-on and comfortable driving solutions from initial architecture to implementation and adoption with a strong sense of ownership and drive for delivery. 

What You’ll Do: 

• Technical Leadership & Strategy: As a technical leader, you will be at the heart of SoFi’s data platform providing primary technical authority and strategic guidance to the data engineering group. 
• Architectural Excellence: Lead the architecture and delivery of large-scale, high-performance data pipelines and processing frameworks. Design scalable data models that support analytics, AI/ML and real-time data needs.
• Platform Innovation: Drive the adoption of cloud-native technologies, automation frameworks and reusable components that improve development velocity and system reliability across SDP.
• System Optimization: Drive org-wide initiatives to improve data reliability, cost-efficiency, and latency. Design solutions that scale horizontally and vertically to handle ever-growing datasets.
• Cross-Functional Collaboration: Partner with business stakeholders, product and engineering leads to align the data roadmap with SoFi’s business objectives. 
• Governance & Security: Lead the implementation of sophisticated data privacy, security, and compliance frameworks. Enforce data governance policies and practices to maintain data integrity in a highly regulated environment.
• Mentorship: Provide deep technical coaching and mentorship to Staff and Senior data engineers, fostering a culture of continuous learning, rigorous testing, and engineering excellence.
• Workforce Development: Contribute to hiring and training efforts to build a skilled and motivated data engineering workforce. Lead the interview process for senior-level talent and design onboarding programs that accelerate engineering productivity.
• On-Call Support: Be part of an on-call support rotation to support the critical production systems.

What You'll Need: 

• Education: A bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
• Experience: Over 12 years of experience in data engineering and analytics, with at least 4 years in a staff-level or higher capacity. A proven track record of successfully leading enterprise-wide data modernization efforts.
• Tech Stack Mastery: Mastery of the modern data stack: Snowflake / Python / SQL / GitLab / AWS / Airflow/ AI tools like Claude code/Cursor. Understanding and implementation experience of AI agents is a plus.
• Cloud Architecture: Expert-level proficiency in relational and cloud database platforms (Snowflake, Redshift, or GCP) and distributed processing frameworks (Hadoop, Spark, or Kafka).
• Strategic Thinking: Thorough knowledge and passion for data modeling (Kimball/Data Vault), database design, and data architecture principles. Ability to simplify complex, ambiguous issues into actionable technical plans.
• Communication: Exceptional ability to communicate complex technical concepts and trade-offs to non-technical stakeholders and senior management.

Domain Knowledge: Deep experience in a highly regulated and governed sector; experience in the Fintech industry is highly advantageous.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Manager of Machine Learning Engineering within the Advanced Technologies Group to lead the technical vision and execution of our foundational systems that power our next generation of AI. You will oversee 4 critical pillars within the Machine Learning org:data engineering, annotation pipelines, ML Infrastructure and Deployment of Agentic AI solutions. You are a hands-on, senior technical leader with a broad dynamic range, capable of providing high-level strategic direction while remaining technically proficient enough to dive into the weeds with your team. Your mission is to transition state-of-art models into robust, autonomous production systems that automate complex enterprise workflows.You will partner closely with internal engineering teams and external vendors to build the scalable tools and data pipelines that define the future of recognition economy.

What you'll do

• Build and maintain scalable, compliant and auditable data infrastructure to serve computer vision and AI pricing use cases 
• Build scalable data engineering pipelines and automated annotation workflows (LLM-in-the-loop) to reduce reliance on manual labeling and accelerate model iteration
• Own the MLOps lifecycle, including distributed training infrastructure, model registries, and low-latency inference services. Ensure high availability and observability for all deployed models
• Define technical direction, lead and grow a high-performance team of data and ML infrastructure engineers to influence impactful business outcomes
• Develop foundational systems to productionize agentic AI, Large Language Models (LLMs) and Vision Language Models (VLMs) solutions for workflow automation to enhance our products
• Enable Metropolis’s move into personalization and targeted advertisement through innovative ML data pipelines and feature stores
• Collaborate with external vendors and annotation platform providers to ensure high-quality data for production models
• Partner with other ML leaders (Growth , Edge deployment) and cross-functional leaders in Hardware, Platform, and Product engineering to align development roadmaps

What we're looking for

• 10+ years of professional experience in data and machine learning engineering with proven expertise in building enterprise-scale, auditable ETL pipelines and data governance mechanisms
• 5+ years of experience in leadership and management, ideally having managed other managers
• MS or PhD in computer science and/or a quantitative discipline
• Strong experience in distributed data processing like Apache Spark, Kafka, Cloud native data storage and processing services
• 1+ years experience building data /eval pipelines and deploying agentic AI solutions (LLMs and/or VLMs)
• Experience managing technical programs, defining milestones, and communicating progress to diverse audiences
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch
• Strong proficiency with SQL and Python
• Engage effectively with external data providers and vendors
• Familiarity with computer vision systems and models (e.g. object detection, tracking, segmentation)

While not required, these are a plus:

• Manage large scale datasets and database tools for data processing
• Deploy ML services to the cloud with a focus on scalability and reliability
• Operate in innovative, high-growth environments

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $200,000.00 USD to $250,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-AR1 #LI-Onsite

About the Role

We’re looking for an Applied Scientist (ALL LEVELS) to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.

What You'll Need

• Strong software engineering and coding skills in Python, with experience contributing to production codebases
  
  
• Experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
  
  
• Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
  
  
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field
  
  
• Solid foundation in statistics and experimental design
  
  
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
  
  

Nice to Have

• Familiarity with Pyspark and distributed data processing
  
  
• Background in search, recommendation systems, or personalization
  
  
• Experience working with large language models (LLMs) or vision-language models (VLMs)
  
  
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
  
  

What You'll Do

• Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
  
  
• Build interpretable ML models that can help us explain pricing decisions to customers
  
  
• Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
  
  
• Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
  
  
• Improve the feature engineering and model training pipelines that power our production systems
  
  
• Rethink our risk and optimization models using real-world data and domain insight
  
  

We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack.

Compensation

The base pay range for this position is $156,800-$310,000 annually, plus RSUs. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

#LI-RO

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems 

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Degree in computer science, machine learning, statistics, or related field
• Nice to have:
  • M.S. or PhD in Machine Learning or related areas
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-SA1

#LI-REMOTE

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keep up with industry trends in recommendation systems 
• Leverage LLMs to enhance content understanding

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• Degree in computer science, statistics, or related field; or equivalent experience
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
• Nice to have:
  • M.S. or PhD in Machine Learning or related areas
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • Background in computational advertising

Relocation Statement: 

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-HYBRID

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems 

What we’re looking for:

• 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Degree in computer science, machine learning, statistics, or related field
• Nice to have:
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-SA1

#LI-REMOTE

With more than 600 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keep up with industry trends in recommendation systems 
• Leverage LLMs to enhance content understanding

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• Degree in computer science, machine learning, statistics, or related field
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
• Nice to have:
  
  • Publications at top ML conferences
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
  • Expertise in scalable realtime systems that process stream data
  • Passion for applied ML and the Pinterest product
  • Background in computational advertising

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-HYBRID

#LI-SM4

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Machine Learning Engineer to develop and expand our revenue forecasting and dynamic pricing systems. This position is part of the machine learning team within the Advanced Technology Group (ATG) and directly influences key business metrics, including revenue, utilization, and customer demand. In this role, you will design and implement models that predict demand, analyze price–demand relationships, and develop pricing strategies. This is a highly impactful role with significant ownership over data, modeling, and infrastructure systems.

What you'll do

• Design, develop, and productionize demand forecasting models optimized for different business goals (e.g., visits, revenue, availability)
• Innovate and improve Machine Learning models for price elasticity, time series, and probabilistic models for revenue optimization
• Design and build end-to-end data pipelines to support large-scale production usage
• Identify data issues (e.g., bias, leakage, labeling inconsistencies) and drive solutions
• Design and analyze experiments (A/B, switchback, causal inference) to validate pricing strategies
• Deploy and monitor models in production, ensuring reliability, scalability, and data quality
• Collaborate with product, engineering, and business teams to translate requirements into scalable ML solutions

What we're looking for

• PhD in Computer Science, Statistics, Economics, Applied Mathematics, or a related STEM field, with at least 1+ years of relevant experience, or MS with equivalent publications
• Proficient programming skills in Python and SQL
• Foundational experience in machine learning modeling and statistics, such as time series forecasting, probabilistic models, and deep learning models
• Strong knowledge with forecasting, optimization, and decision-making algorithms, including revenue maximization, constrained optimization, and demand/price curve optimization
• Solid understanding of causal inference and experimentation, with experience evaluating both short-term and long-term effects (A/B testing, DiD, uplift modeling)
• Hands-on experience with data pipeline development, including AWS data storage, data transformation, distributed processing (Spark), and workflow orchestration (Airflow)
• Strong communication skills, both written and verbal, with the ability to operate effectively at team and deep technical levels
• Comfortable reading academic papers and formulating concepts using mathematical notation

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $150,000.00 USD to $180,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-NM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
• Design and own data architecture for large-scale projects while managing operational trade-offs
• Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
• Define and manage Service Level Agreements (SLAs) for all owned data sets
• Implement data security models, ensure privacy compliance, and evolve data governance processes
• Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
• Maintain production processes by optimizing complex code using advanced algorithmic concepts
• Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
• Mentor team members through actionable feedback to foster collective skill growth
• Maintain flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field
• master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
• Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Deep understanding of the modern IaC ecosystem to drive automated infrastructure deployments
• Experience with cloud computing services, preferably AWS, including hands-on experience with services like Glue, Airflow (MWAA), DMS, EKS, and SNS

While not required, these are a plus:

• Experience with Spark and PySpark
• Master's degree in Computer Science, Computer Engineering, or a relevant technical field

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $160,000.00 USD to $220,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-CM1 #LI-Onsite

RDQ427R179

Are you a mission-driven leader with a passion for how data and AI can play a meaningful role in addressing global challenges? Do you enjoy shaping narratives, building programs, and translating complex work into stories that inspire action?

As the Lead for Databricks for Good, you will own Databricks’ social impact initiative end to end. You will work closely with Databricks teams and with nonprofits, universities, and public-interest organizations to design and scale programs that apply data and AI to real-world challenges.

You will set the vision for Databricks for Good and ensure it delivers real, lasting impact, while clearly articulating how that impact is created and why it matters.

About Databricks for Good

At Databricks, we believe data and AI can be a force for positive change. Databricks for Good exists to ensure our platform empowers organizations working on humanity’s most pressing challenges, including responding to crises, advancing education, improving health outcomes, and accelerating climate action.

This role is an opportunity to define and lead that mission and shape how Databricks shows up in the world through meaningful, real-world impact.

What you’ll do

Your responsibilities will span program design and management, storytelling, and owning execution across Databricks and its partners. 

• Build and lead Databricks for Good from the ground up, defining its mission, success metrics, execution strategy, and long-term vision.
• Design and run high-impact programs such as social impact partnerships, hackathons, student and university initiatives, and nonprofit enablement programs.
• Serve as a public-facing representative for Databricks for Good by hosting events, delivering talks, moderating panels, and representing Databricks in global social impact forums.
• Own the partnership funnel for Databricks for Good technical engagements, with the goal of helping nonprofits apply Databricks to real-world challenges.
• Create compelling content - case studies, talks, blogs, and learning resources - that highlight how data and AI can be used for social good.
• Work cross-functionally with Field Engineering, Developer Relations, Marketing, Legal, and Sales to ensure social impact initiatives are scalable, technically sound, and aligned with company priorities.
• Act as a trusted internal advisor on social impact use cases, helping teams understand the needs, constraints, and operating realities of mission-driven organizations.
• Gather feedback from both internal and external collaborators to continuously improve programs and inform program direction.

The impact you will have

• Establish Databricks for Good as a credible, respected, and scalable social impact initiative throughout the tech industry.
• Enable nonprofits, universities, and public-sector organizations to unlock insights and outcomes that are uniquely possible with data and AI.
• Build durable partnerships that align Databricks’ strengths with real-world societal needs.
• Inspire employees, customers, and students to contribute their skills toward meaningful causes.
• Influence how Databricks technologies are used, taught, and evolved for public good.
• Help define what “data and AI for good” looks like at enterprise scale.

What we look for

• 7+ years of experience in social impact programs, developer relations, partnerships, technical program management, or a related field.
• Proven ability to build and scale programs from zero to one, with ownership over strategy, execution, and outcomes.
• Experience working with nonprofits, universities, NGOs, public-sector institutions, or mission-driven organizations.
• High-level technical understanding of Databricks’ product-market fit, enabling robust direction of partnerships and engagement selection.
• Exceptional communication and storytelling skills, with comfort presenting to both technical and non-technical audiences.
• Demonstrated ability to convene communities and stakeholders across sectors and geographies.
• High empathy, strong judgment, and the ability to navigate ambiguity while driving clarity and momentum.
• A collaborative mindset and a track record of working cross-functionally to turn ideas into execution.

ABOUT THE ROLE:

As a multimodal engineer on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities, while also incorporating audio where it enhances visual content (e.g., synchronized audio for video). Responsibilities span data curation, modeling, training, inference serving, and product integration, covering both pretraining and post-training phases. You will collaborate closely with product teams to push model frontiers and deliver exceptional end-to-end user experiences.

RESPONSIBILITIES:

• Create and drive engineering agendas to advance multimodal capabilities, with emphasis on image and video generation, editing, understanding, controllable/long-horizon synthesis, agentic planning, RL training, and world simulation (including audio integration for richer video experiences).
• Improve data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, particularly for visual and audio data. 
• Design evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence.
• Implement efficient algorithms for state-of-the-art model performance, including real-time inference, distillation, and scalable serving for visual content.
• Develop scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.
• Collaborate cross-functionally to integrate AI solutions into production and rapidly iterate based on user feedback.

BASIC QUALIFICATIONS:

• Track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling.
• Experience in data-driven experiment designs, systematic analysis, and iterative model debugging.
• Experience developing or working with large-scale distributed machine learning systems.
• Ability to deliver optimal end-to-end user experiences.
• Hands-on contributor with initiative, excellence, strong work ethic, prioritization skills, and excellent communication.

PREFERRED SKILLS AND EXPERIENCE:

• Experience in SFT, RL, evals, human/synthetic data collection, or agentic systems.
• Proficiency in Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, and related large-scale frameworks.
• Domain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video).
• Experience with agentic RL training, controllable/long-horizon generation, or multimodal agents that reason and act across modalities (especially in visual domains).

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

Our Mission: 

To actively connect people to their next great opportunity. 

Who We Are: 

ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android.

Summary:

Our team has a unique opportunity to work on applications and data at scale, serving millions of jobseekers and tens of thousands of customers. We’re working on building an efficient marketplace of jobseekers and employers and need generalist software engineers to build fast, scalable, and effective applications, stream and batch data processing, ML infrastructure and a variety of other systems all to help connect people to their next job. We provide an essential service and have a thriving business as a result.

Our stack is complex and we’re looking for engineers who know how to write evolvable, properly instrumented, and efficient code as part of a growing distributed system. We’re working on data driven systems and applications and need people who can build fast services and processes to power all of the intelligence we use to help change people’s lives.

Responsibilities:

• Build data processing and exploration pipelines along with ML infrastructure to power our intelligence
• Deploy a range of cloud-based technologies for critical projects
• Write, test, instrument, and deploy code to our Kubernetes environment
• Help drive the innovation and evolution of ZipRecruiter

Minimum Qualifications:

• 5+ years of professional software development experience with a focus on big data technologies
• Experience with Hadoop, Spark, Hive, and/or other big data technologies
• Comprehensive computer science fundamentals in coding, object-oriented programming, data structures, and algorithms
• Experience with containerization technologies like Docker and/or Kubernetes

Preferred Qualifications:

• 8+ years of professional software development experience, with a focus on big data technologies
• BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field or equivalent practical experience
• Experience with data integration tools like Apache Kafka, Flume, and NiFi
• Familiarity with data storage technologies such as Delta Lake, HBase, Cassandra, and MongoDB
• Familiarity with Apache Hudi, Apache Beam, Apache Flink, Google Cloud Dataflow, Amazon Kinesis Data Analytics, and/or Azure Databricks

As part of our team you’ll enjoy:

• Competitive compensation
• Exceptional benefits package
• Flexible Vacation & Paid Time Off
• Employer-matched 401(k) plan 

The US base salary range for this full-time position is $140,000-$200,000. Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations.

Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits.

#LI-Remote

#LI-DA1

Staff Backend Engineer - Inventory and Promise Platform 

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar commerce industry from the ground up. We are one of the fastest-growing retail companies that established an unparalleled reputation for being a leading and reliable force in South Korean commerce.
 
We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurial, surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. 
 
Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Job Overview:

As our Staff Backend Engineer for the Inventory and Promise Platform team, you will empower Coupang Fulfillment & Transportation to operate faster, better, and cheaper through modern, reliable, and data-driven technologies. In this role, you will be a key contributor to an area of the business that is rapidly expanding and is recognized for its Rocket Delivery service. The team already builds services that process thousands of requests per second, generate trillions of won annually in business decisions, and manage business rules that move millions of products. We are responsible for improving order coordination with technology to deliver products to millions of online shoppers. The role will involve technical leadership on rearchitecting and building a brand new Inventory and Promise platform which powers customer’s shopping experience by giving inventory visibility to the customer to be able to order and gives out promised delivery dates for their order. Additionally, the platform also powers fulfillment orchestration once an order is placed.

Key Responsibilities:

• Serve as a technical lead on our most demanding, cross-functional projects involving Inventory and Promise.
• Independently come up with quality architecture and design of systems for new microservices and machine learning pipelines.
• Functionally decompose complex problems into simple, straightforward solutions.
• Possess expert knowledge in performance, scalability, enterprise distributed architecture, and engineering best practices.
• Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members.
• Exert technical influence over multiple teams, increasing their productivity and effectiveness by sharing your deep knowledge and experience.

Qualifications:

• Bachelor's degree and/or Master’s degree in Computer Science or equivalent.
• 6+ years of software engineering experience, including Java.
• 6+ years of experience leading large-scale projects.
• 6+ years of knowledge of emerging platforms, Java, C/C++, operating system principles, and programming best practices.
• Strong understanding of backend scalable software architecture, distributed systems, and message-oriented architecture.
• Experience with full-stack, high-scale production systems with fault-tolerance and monitoring.
• Experience with building stream-processing systems, using solutions such as Kafka and Spark-Streaming.
• Data caching and storage techniques and creating distributed software architectures with horizontal scale.
• Operationalizing software in a large-scale environment with high availability requirements.

Preferred:

• Experience with scalable distributed systems and understanding of machine learning algorithms.
• Experience in the eCommerce domain involved in supply chain systems around Inventory and Promise.
• Software development experience with Java, Scala, and Python.
• Experience with AWS; Java language would be a plus.

Requisition: R0068371

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

Staff Backend Engineer - Foundational Systems and Platforms (FSP)

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar commerce industry from the ground up. We are one of the fastest-growing retail companies that established an unparalleled reputation for being a leading and reliable force in South Korean commerce.
 
We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurial, surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. 
 
Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Job Overview:

This role is in Foundational Systems and Platforms (FSP) organization in Global Operations Technology. Our charter includes Inventory Platform that managed inventory for Coupang and Fulfillment Execution system that orchestrates the complete journey of delivering a customer's order to their doorstep.

We are looking for a Staff engineer to help us build our next generation systems in FSP organization. The candidate should have strong backend engineering experience that includes building highly scalable systems, using workflow based orchestration solutions, actor-based and CQRS frameworks. Experience in AWS eco system and platform solutions like temporal and Akka will be preferred.

Candidate should have proven track record in delivering mission critical systems that supports operations and customers. This requires maintaining a high bar in Operational Excellence (OE) and working closely with our operations and product stakeholders.

Key Responsibilities:

• Independently come up with quality architecture and design of systems for new microservices and machine learning pipelines.
• Functionally decompose complex problems into simple, straightforward solutions.
• Possess expert knowledge in performance, scalability, enterprise distributed architecture, and engineering best practices.
• Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members.
• Exert technical influence over multiple teams, increasing their productivity and effectiveness by sharing your deep knowledge and experience.

Qualifications:

• Bachelor's degree and/or Master’s degree in Computer Science or equivalent.
• 7+ years of software engineering experience, including Java.
• 7+ years of experience leading large-scale projects.
• 7+ years of knowledge of emerging platforms, Java, C/C++, operating system principles, and programming best practices.
• Strong understanding of backend scalable software architecture, distributed systems, and message-oriented architecture.
• Experience with full-stack, high-scale production systems with fault-tolerance and monitoring.

Req: R0068651

• Experience with building stream-processing systems, using solutions such as Kafka and Spark-Streaming.
• Data caching and storage techniques and creating distributed software architectures with horizontal scale.
• Operationalizing software in a large-scale environment with high availability requirements.

Preferred:

• Experience with scalable distributed systems and understanding of machine learning algorithms.
• Experience in the eCommerce domain involved in supply chain systems around Inventory and Promise.
• Software development experience with Java, Scala, Python, NoSQL and Distribute Compute
• Experience with AWS; Java language would be a plus.

Please complete the attached Internal Transfer Request Form and submit.  

Please make sure to apply with your Coupang e-mail address.  

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Medical, Dental, and Vision insurance
• Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled 
• Flexible spending accounts and 401(k)
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Seattle

What We Do

• The Omnichannel team at The Trade Desk is pioneering a new approach to digital advertising — one built around telling a coherent story through ads, using the media best suited for each chapter. We work across the full ad tech stack, from identity to measurement to bidding, to deliver unified campaign experiences that span screens, formats, and moments. Our Software Engineers are end-to-end owners who participate in designing, building, and delivering data-focused products for our stakeholders.

What You'll Do

• Design and build systems that orchestrate advertising across channels, ensuring a unified narrative from first impression to conversion.

• Work across team boundaries — partnering with identity, measurement, and bidding teams to integrate their capabilities into cohesive omnichannel solutions.

• Own projects end to end, from early design through production rollout and ongoing operation.

• Translate ambiguous business requirements into concrete technical designs and execution plans.

• Deliver high-quality changes with automated tests, metrics, and monitoring.

• Collaborate with product managers and business stakeholders to define what success looks like and drive toward it.

• Mentor other engineers and contribute to a culture of trust, ownership, and technical excellence.

Who You Are

• You're comfortable owning things end to end — from scoping a problem to shipping and operating the solution.

• You communicate clearly with both technical and non-technical audiences, and you're effective working across teams with competing priorities.

• You thrive in ambiguity. Vague requirements don't slow you down — you translate them into actionable plans and iterate toward the right answer.

• You have 7+ years of software development experience.

• You have strong experience with distributed systems and backend development in a language such as C#, Java, or Python.

• You have a solid understanding of computer science and engineering fundamentals.

• You're comfortable working on an agile, distributed team spanning multiple time zones.

Nice to Have

• Experience with large-scale data processing (Spark, Airflow, Kafka, Flink).

• Familiarity with cloud infrastructure and orchestration tools (Kubernetes, Terraform).

• Experience in ad tech or with real-time bidding systems.

• Exposure to cross-channel measurement or identity resolution.

P-1495

About Databricks

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

About the Role

Databricks is seeking a Senior Staff Product Operations Manager to serve as the chief architect of our internal operational ecosystem. This is a high-leverage leadership role embedded within Engineering, designed to orchestrate the complex intersection of technical innovation, product lifecycle maturity, and global Go-to-Market (GTM) acceleration.

In this capacity, you will move beyond the management of existing processes to lead the creation of a formal Operational Association. You will be responsible for designing the high-fidelity frameworks that allow our engineering organization to remain agile while ensuring that every product investment is data-driven, transparent, and rigorously aligned with our long-term commercial strategy. This role is purpose-built for a strategic thinker who excels at navigating the "gray space" between a deep technical roadmap and the sophisticated financial requirements of a global enterprise platform.

Impact

• Operational Orchestration: Define and govern the strategic engagement model between Engineering, Product, and GTM, ensuring that product lifecycle milestones are seamlessly integrated with field readiness and revenue velocity.

• Investment Intelligence: Act as a critical advisor to executive leadership, applying a consultant’s rigor to evaluate business investments. You will analyze resource allocation, unit economics, and the opportunity costs inherent in scaling a world-class Data and AI platform.

• Synthesis of Ambiguity: Transform disparate, multi-dimensional data signals from across the organization into coherent business insights. You will be the definitive voice in translating "engineering velocity" into "market impact," providing the clarity necessary for high-stakes decision-making.

• Systems Transformation: Lead the evolution of our product development lifecycle (PDLC). You will identify structural bottlenecks and design scalable solutions that enhance organizational throughput without sacrificing technical excellence.

• Strategic Connective Tissue: Serve as the authoritative bridge between the "How" of technical execution and the "Why" of business value, ensuring a unified language of success across our most senior stakeholders.

Key Responsibilities:

• Act as the connective tissue between Support, Product, Engineering, and Analytics to drive operational alignment, product readiness, and continuous improvement across support workflows.
• Lead and execute strategic initiatives to scale global Support operations, including coverage models, KPI frameworks, and support process enhancements.
• Translate operational pain points into product and tooling requirements—partnering with internal tools, engineering, and analytics teams to drive automation, triage efficiency, and AI assistant improvements.
• Build and maintain dashboards that measure support effectiveness, surface product-driven case trends, and track customer experience across support channels.
• Support quarterly and annual planning cycles, including headcount, capacity modeling, and budget alignment in partnership with Finance and Workforce Management.
• Influence senior stakeholders by turning support and operational insights into clear, data-driven narratives that inform product and business decisions.

What We Look For: 

• Professional Experience: Minimum of 9 years of professional experience in Management Consulting, Product Strategy, Technical Program Management, or Operations within the technology sector.

• Bachelor’s degree in a technical, mathematical, or analytical field (e.g., Computer Science, Engineering, Economics). An MBA is highly preferred.

• Demonstrated experience in designing and scaling operational frameworks or internal software systems within a high-growth SaaS or enterprise technology environment.

• Expert-level ability to navigate large, complex datasets using SQL-based tools and Business Intelligence (BI) platforms to drive strategic decision-making.

• Proven track record of leading high-stakes, multi-quarter initiatives involving diverse cross-functional teams such as Engineering, Product, and Sales.

• Exceptional ability to synthesize complex technical concepts into clear, actionable business strategies for non-technical executive audiences.

Nice to Have: 

• Familiarity with Databricks tools, especially for extract/transform/load functions
• Experience working on Support Operations for SaaS based companies.
• Familiarity with tools like Salesforce, Zendesk, Jira, Looker/Tableau, and operational workflows

About the Role:

Join us as a Data Analyst where you will step into a dynamic role that that makes a real impact for our clients. If you are passionate about uncovering hidden insights within complex data sets and transforming raw data into actionable knowledge, then we want to talk with you! In this role you will embark on an adventure that utilized your analytical prowess to decode data, identify trends, and help shape the future of Stackline. Apply today and help us on our quest to unlock the full potential of data while contributing to meaningful change! This is a hybrid role (4 days/week in office) and is based out of our Seattle, WA office.

What You Will Do:

• Conduct comprehensive dataset analyses across Stackline to extract insights, trends, and patterns utilizing mathematical, statistical, and probability methodologies.
• Build and maintain data pipelines and workflows to ensure data accuracy and consistency, while identifying and rectifying errors, inconsistencies, or missing information.
• Provide timely and precise responses to inquiries from both internal and external sources regarding datasets and models.
• Apply technical expertise to process complex datasets, establish quality control procedures, and derive actionable insights through analytics.
• Develop scalable processes for automating reports and visualizations to communicate findings effectively to stakeholders.
• Collaborate with cross-functional teams to understand data requirements and address specific product questions or challenges.
• Document data sources and processes for data analysis.

Who We Are Looking For:

• Bachelor’s degree in Mathematics, Physics, Computer Science, or other relevant technical field.
• 2+ years of direct industry work experience in one or more of the following areas: data science, data analytics, or data engineering.
• 2+ years of experience with statistics and probability, particularly their application in systems analysis and operations research.
• Demonstrated experience with Python and SQL.

Bonus Points If You Have:

• Prior experience using advanced statistical tools such as SciPy or sklearn.
• Prior experience with big data technologies such as Hadoop or Spark.
• Demonstrated experience designing and building innovative ideas, working closely with technical teams from concept generation through implementation.
• Experience working in a startup, retail, digital advertising, or e-commerce environment.

Benefits and Perks

It's important that each and every employee feels they are supported and can complete their life's best work today and in the future. As part of that, we are committed to doing our part in addressing pay gaps and discrepancies by providing pay transparency for all of our roles. Actual salaries are just one component of the compensation package and may vary above or below the range based on job-related knowledge, skills, experience, location, and performance. The pay range for this position in Seattle is $85,000 - $105,000 per year. Other rewards may include annual bonuses, short- and long-term incentives, and other team-specific awards. In addition we provide a robust benefits and perks package that includes:

• Comprehensive medical, dental, and vision coverage that actually supports you — including HSA with company match and FSA options
• Fertility benefits to support your path to parenthood
• 401(k) with company match to help you plan ahead
• Company-paid life insurance
• 20 days of PTO + 9 company holidays to truly unplug
• Paid parental leave for all parents — because family matters
• Summer Fridays (log off at 3pm and enjoy it)
• Regular in-office social events including happy hours and catered lunches
• A thoughtfully stocked kitchen with healthy snacks and fresh fruit