We are looking for a Senior Staff Software Engineer for Application Engineering. As a Sr Software Engineer on the Applications Engineer team, you’ll be part of a cross-functional team whose mission is to deliver real-world applications and value from the leap forward in computing enabled by quantum technology. 

We don't just build the world's best quantum computers - we apply cutting edge quantum computing tools to real world problems. Until now, our team of Applications Scientists have been building prototypes, working closely with our customers. Our new department, Applications Engineering, will ultimately help transform proven quantum computing use-cases pioneered by our scientists into production applications, making those innovations available to more people and businesses by packaging and deploying these tools as SaaS applications.

But first, we must mature existing proof-of-concept quantum code into production grade applications. As a hands-on team lead for a new engineering team, you will work on enhancing developer experience (DevEx) by applying best practices to research-grade code. You will also set up CI / CD pipelines, software packing tools, and pre/post flight tests for new algorithms as they go into deployment. Where possible you will also be in charge of optimizing and parallelizing traditional algorithms, to reduce pre-processing and post-processing workloads. You will spearhead a new team taking newly invented quantum applications, and turning them into well defined modules of reliable SaaS applications. Think of it as being a forward-deployed engineer for quantum computing applications; the strongest candidates will be generalists with wide-ranging interests. 

This team will work closely with Developer Tools, Infrastructure, and Product teams to solve problems by choosing the right technologies, and standardizing and automating those solutions. The right engineer will be comfortable working on refining chemistry simplification via Quantum Computing tool one quarter, and turning a novel quantum topology solver into a service the next - and love pair programming with scientists. They’ll bring the quantum expertise; you bring the deep and broad experience in classical programming.

Responsibilities:

• Partner with Application scientists to help deliver cutting-edge solutions for customers
• Elevate Applications code quality generally through architectural review, code review, standards, and best practices
• Improve Applications pace of delivery by creating CI / CD pipelines and other packaging automation, as well as test infrastructure and coverage
• Help productize computing code, especially improving data processing in pre-quantum and post-quantum processing steps
• Work closely with peers in Applications, Developer Tools, and Product teams to share best practices and feedback on internal tools
• Reporting to the Director of Application Engineering, help hire and mentor developers on the team

You’d be a good fit with:

• 12+ years of experience as a backend or full-stack developer, preferably in Python or Golang
• 5+ years of experience in setting up and maintaining CI / CD pipelines, in Github Actions, Jenkins, or similar tools
• 5+ years of experience in C/C++ or Rust
• 3+ years of experience in Docker, k8s, or similar containerization technologies
• A track record of shipping containerized applications that solve real business problems
• Previous work in scientific computing, quantum computing, or a related field
• Daily usage of augmented coding tools like Claude or Gemini 

You’d be a great fit with:

• 5+ years of experience in scientific computing, especially with data analysis using numpy, pandas, or similar
• Experience in HPC or performance optimization
• Experience in converting traditional algorithms into CUDA, OpenMP workflows, or similar parallelization experience
• Experience with workflow orchestration engines like Airflow, Dagster, or Temporal

Location: This position can work onsite or hybrid from our office in Bothell, WA; College Park, MD; or Boulder, CO
Travel: 5% for quarterly travel for collaboration 
Job ID:  1312

The approximate base salary range for this position is $192,979 - $252,659. The total compensation package includes base, bonus, and equity.

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Senior Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Evaluating ads integrity: understanding changes and drivers of our complex systems, diagnosing fraud claims and mitigating fraud escalations through a set of input/output metrics of each component.
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Economics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Staff Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

• This leader will own the multi-year strategy, roadmap, and execution across the ads supply ecosystem:
  • Supply Exchange & Inventory Integrations: Drive Moloco’s OpenRTB integrations with top-tier third-party supply partners and exchanges, expanding Moloco’s access to high-quality, global, multi-format inventory across gaming and non-gaming verticals.
  • Lead Moloco’s end-to-end General Supply strategy, including Exchange integrations, OpenRTB supply diversification, publisher onboarding, and supply ecosystem expansion.
  • Define, evangelize, and deliver a multi-year supply vision that improves supply quality, scalability, integration reliability, and long-term differentiation
• Conducting deep-dive analysis and experiments to influence product decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Preferred Qualifications:

• Advanced degree. PhD is highly desirable. 
• Deep expertise in the programmatic supply ecosystem, including ad exchanges, SSPs, OpenRTB protocols, auction mechanics, and cross-platform integration
• Demonstrated ability to drive cross-org alignment, influence senior stakeholders (Directors/VPs), and execute through large engineering teams
• Familiarity with publisher ad servers, targeting logic, and impression delivery workflows
• Deep knowledge of supply-side performance metrics such as fill rate, eCPM, latency, bid density, impression opportunities, and unique users—and how to optimize for them
• Hands-on experience with integrations and partner-facing APIs, including defining requirements for interoperability with DSPs, exchanges, ad networks, DMPs, and other adtech partners

ABOUT THE TEAM
Anduril Labs is a multidisciplinary team of technologists, solution architects, engineers, and military subject matter experts. Its mission is to drive innovation across all Anduril business units and product lines by developing novel concepts and next-generation technologies that enhance Anduril’s competitive edge and give its customers a decisive technological advantage over its adversaries.

ABOUT THE JOB
We are looking for a talented mid-level Software Engineer with a strong background in optimization to join our growing team at Anduril Labs. In this role, you will be instrumental in developing advanced algorithms and software solutions to tackle complex, multi-domain optimization problems critical to national defense and Anduril’s autonomous systems.

The ideal candidate possesses deep expertise in classical optimization algorithms, robust Python programming skills, and a solid foundation in data modeling. Experience with developing hybrid quantum optimization solutions is a plus. You will leverage state-of-the-art, GenAI-powered development tools such as Claude Code to accelerate solution development and enhance our optimization software. This role demands creative problem-solving, a self-starter mentality, and the ability to rapidly apply algorithmic theory and mathematic modeling to practical, real-world optimization challenges. You will be designing, implementing, and deploying optimization algorithms and services that integrate seamlessly into larger defense systems, working across various platforms (on-prem, cloud, and hybrid quantum computing environments). Familiarity with modeling linear and non-linear optimization problems, rapid prototyping, integrating optimization solutions into existing architectures, leveraging APIs, and utilizing open-source tools will be crucial.

If you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

WHAT YOU’LL DO

• Design, develop, and implement highly efficient optimization algorithms and software solutions to solve challenging problems in areas such as resource allocation, scheduling, routing, mission planning, control systems, and supply chain logistics.
• Apply classical optimization techniques (e.g., linear programming, mixed-integer linear programming, combinatorial optimization, network flow, dynamic programming, heuristics, metaheuristics) to model and explore novel approaches.
• Utilize GenAI tools (e.g., OpenAI Codes, Claude Code, GitHub Copilot) to rapidly prototype, refine, and test algorithmic solutions, improving development velocity and code quality.
• Develop robust data models and efficient data pipelines to support complex optimization problems, ensuring data integrity and efficient processing for algorithmic inputs and outputs.
• Collaborate with multidisciplinary teams (software engineers, data scientists, domain experts, product managers) to integrate optimization engines and services into larger defense systems and platforms.
• Perform rigorous testing, validation, and performance analysis of optimization solutions, ensuring scalability, reliability, and accuracy under diverse operational conditions.
• Participate actively in the entire Software Development Lifecycle (SDLC) from requirements gathering and design to deployment, monitoring, and maintenance.
• Support Anduril- and customer-funded R&D efforts, contributing to technical documentation, presentations, and patent applications.

REQUIRED QUALIFICATIONS

• Bachelor's degree in Computer Science, Software Engineering, Applied Mathematics, Operations Research, or a related quantitative field.
• 3+ years of professional experience in software development with a dedicated focus on optimization, algorithmic problem-solving, or operations research.
• Experience solving optimization problems in defense, transportation, supply chain, logistics, network optimization, smart grids or similar
• Expert proficiency in Python for scientific computing and robust software development.
• Strong theoretical and practical understanding of classical optimization algorithms (e.g., linear programming, mixed-integer linear programming, constraint programming, network flow, dynamic programming, heuristics, meta heuristics).
• Hands-on experience with optimization libraries and commercial/open-source solvers (e.g., SciPy Optimize, PuLP, CVXPY, Gurobi, CPLEX, OR-Tools, GEKKO). Experience with Gurobi is a plus.
• Solid experience with data modeling, data structures, and algorithms to efficiently prepare, process, and manage data for optimization problems.
• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.
• Proficiency in using numerical computing libraries such as NumPy, SciPy, and Pandas.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Ability to develop, test, and deploy software effectively on Linux-based systems.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.
• Experience with Git version control, build tools, and CI/CD pipelines.
• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.
• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.

PREFERRED QUALIFICATIONS

• • Master's or Ph.D. in Computer Science, Applied Mathematics, Operations Research, or a closely related quantitative field.
  • Familiarity with or a strong interest in quantum optimization algorithms, quantum computing concepts, or quantum-inspired heuristic approaches. Experience with D-Wave’s quantum annealing platform is a plus.
  • Experience with performance-critical programming languages such as C++ or Java.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying scalable optimization solutions or high-performance computing (HPC) environments.
  • Prior experience in defense, aerospace, logistics, supply chain management, robotics, or manufacturing optimization domains.
  • Familiarity with integrating machine learning models with optimization techniques (e.g., prescriptive analytics, reinforcement learning for optimization).
  • Excellent communication skills with the ability to articulate complex technical concepts, present findings, and influence technical direction across diverse teams.
  • Willingness to travel up to approximately 10%.

ESA is hiring a GIS Analyst/Developer to join our Pacific Northwest Technology Services team based out of our Seattle, WA, and/or Portland & Bend, OR offices. The ideal candidate will support multidisciplinary project teams across ESA's Pacific Northwest offices. This is a hybrid role with 3 days per week in either our Portland or Seattle offices, with availability expected during Pacific Time business hours.

Who you are

• You have 2 to 7 years of professional GIS experience and a degree in GIS, geography, computer science, environmental science, or a related field.
• You are strong across the fundamentals: coordinate systems and projections, spatial data management, spatial analysis, cartographic design, and field data collection. You also write reusable Python, manage code in Git, work with APIs and databases, and use AI coding assistants.
• You are proficient across the full range of GIS work, lean toward automation and tool-building, are a strong collaborator, and are motivated to grow within a project-based consulting environment.
• You are organized, deadline-driven, and able to manage multiple project assignments without losing track.
• You communicate clearly with people who do not speak GIS or code and are attentive to detail with a sound sense of judgment to know when a deliverable is ready to ship. Cartographic judgment matters: your maps need to be accurate, readable, and are commonly a focal point of client reports.
• You thrive in a fast-paced work environment where no two projects look the same. You are wired to collaborate, and constantly looking for better tools and patterns, especially for work that recurs.
• Must possess technical skills to include ArcGIS Pro and ArcGIS Online for spatial analysis, web maps, and application development (Experience Builder, Dashboards, StoryMaps); able to configure field data collection tools (Field Maps, Survey123, Fulcrum); Python beyond arcpy (pandas, geopandas, rasterio, and similar libraries); SQL for querying and maintaining spatial and non-spatial databases (PostgreSQL/PostGIS a plus); and Git and GitHub for version control and code review.
• Additional skills that are highly valued include remote sensing and machine learning (imagery analysis, classification, OBIA workflows, and classifiers such as Random Forest), R for statistical or spatial analysis, JavaScript (and ArcGIS JavaScript API) for customizing Experience Builder or Dashboards, fluency with AI coding assistants such as Claude Code, Copilot, or Cursor, and familiarity with Pacific Northwest datasets and sources. Consulting experience is a plus.

What Will You Do for ESA

• The day-to-day work includes building and maintaining geodatabases for restoration, planning, permitting, and infrastructure projects, producing maps, figures, and spatial analyses for technical reports, NEPA and SEPA documents, and client deliverables.
• Configure field data collection tools for biological surveys, cultural resource inventories, and site assessments; and developing web maps, dashboards, and Experience Builder applications used directly by project teams and clients.
• You will write Python for automation, data pipelines, and custom tools, and manage code in shared Git repositories with code review and basic CI practices.
• You will also support remote sensing and machine learning workflows when projects call for them.
• You will collaborate closely with biologists, hydrologists, planners, cultural resources specialists, engineers, landscape architects, and other GIS analysts. The diversity of disciplines on the team makes the work engaging and underscores the importance of strong communication and time management alongside technical expertise.

What's Special About Our Geospatial Team in the Pacific Northwest

The Pacific Northwest geospatial team supports public agencies, tribes, and communities across the region. Recent and ongoing clients include the Bonneville Power Administration, Washington Department of Fish and Wildlife, Washington and Oregon Departments of Natural Resources, US Army Corps of Engineers, WSDOT, ODOT, Northwest tribes, port authorities, and local jurisdictions across Washington and Oregon.

Our work is embedded within ESA's core technical disciplines: Biological Resources, Cultural and Historic Resources, Environmental Planning, and others. Beyond the Pacific Northwest, our team regularly supports work from ESA's California Regions and Southeast Region, which brings exposure to challenges such as CEQA review and wildfire recovery in California, and sea-level rise and coastal resilience in Florida.

Our team is part of ESA's broader Technology Services Practice. For projects that grow beyond traditional GIS, we collaborate with in-house data engineers, software developers, and architects, allowing us to deliver more complex, integrated solutions.

What's Special About ESA

ESA is a 100% employee-owned environmental consulting firm. Every eligible employee receives an annual ESOP allocation, which means you build equity in the company through the work you do. Other benefits include medical, dental, and vision insurance with 70% of premiums covered for you and your family; a 401(k) with company match; paid vacation, sick leave, and holidays; tuition reimbursement; professional development bonuses; and support for attending conferences. Mentorship and career development are an active part of how the team works.

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

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

As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customer stakeholders, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide one of our largest AI native customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
  • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
  • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

The Work: 

• Analyze & Innovate: Uncover trends and anomalies, turning raw data into strategic intelligence. 

• Model & Predict: Develop and maintain models using machine learning, AI, and statistical techniques. 

• Code & Transform: Use Python (pandas, PySpark) and SQL for data parsing, ETL, and complex analysis. 

• Visualize & Communicate: Create interactive dashboards and visualizations with Power BI, Tableau, or Databricks. 

• Collaborate & Build: Partner with Data Engineers to define data requirements and support development. 

• Explore & Experiment: Research and test new tools to solve challenging problems. 

 Here’s what you need: 

• • Experience building NLP, LLM, or using GenAI tools (e.g. LoRA, LangChain, RAG, LLM Fine Tuning or PEFT) 
  • Proficiency in Python (pandas, PySpark) and SQL 
  • Hands-on experience with data visualization tools like Power BI, Tableau, or Databricks 
  • Strong quantitative and analytic abilities to analyze and validate data 
  • Understanding of analytical model development and data-driven decision-making
  • Must be a US Citizen 

 Bonus points if you have: 

• Experience designing and implementing a custom Generative AI solution
• Experience working in a cloud environment (Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP))
• Experience working with federal clients 
• Experience in a specific domain like Cybersecurity or Fraud Detection 

 Security Clearance:  

• Active Secret or Top Secret or TS/SCI or TS/SCI with polygraph clearance

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

As a Solutions Architect on the Digital Natives team, you will work with the leading data engineering, data science & ML teams in the market to push the boundaries of what big data architectures are capable of. 

Reporting to the Field Engineering Manager, you will collaborate with strategic customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

We are looking for high technical aptitude individuals with a deep sense of ownership and a desire to help customers ship solutions at production scale. Ideal candidates are deeply curious, capable of operating with confidence in ambiguous situations, and are extremely adaptable. 

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Drive technical discovery and solution design, focusing on winning competitive deals and accelerating time-to-value in strategic accounts.
• Continuously research & learn new technologies and their implementations on Databricks
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our customers
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.
• Work closely with account executives to create and execute account penetration strategies, focusing on winning technical decision-makers and building new customer champions.
• Build trusted advisor relationships with senior and executive stakeholders by articulating the business value of Databricks in clear, outcomes-driven terms.
  
  

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Strong executive presence with the ability to influence C/VP-level stakeholders and align technical solutions to strategic business priorities.
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification
  
  

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end.

Main Responsibilities

• Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform.
• Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows.
• Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role.
• Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow.
• Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup.
• Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices.
• Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.
• Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.
• Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
• As part of our team, you will have the opportunity to work on all aspects of complex National Security problems.
• Annual travel up to 25%.

Preferred Qualifications

• B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.
• 3+ years of customer-facing experience in the design and implementation of AI/ML solutions.
• Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow).
• Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI).
• Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.
• Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
• Ability to work in a fast-paced environment and balance priorities across multiple projects at once.
• Experience reviewing and drafting responses to federal Requests for Comment (RFCs), Requests for Information (RFIs), Requests for Proposals (RFPs), etc. is preferred
• Experience working across the Civilian, DOD and NATSEC agencies, inclusive of experience in Federal Law Enforcement, Healthcare, Financial/Regulatory and Military operations and logistics
• Candidates must have an active TS (Top Secret) Clearance

Compensation range $170K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Locations

#LI-CG1

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform.

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources, and applying ML to enrich our datasets with predictive and generative intelligence. As a senior engineer, you will take ownership of key technical components and ensure that our systems meet the highest standards of performance, reliability, and security.

Primary Job Responsibilities:

• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards
• Support a culture of technical excellence by mentoring peers, sharing knowledge, and participating in code and design reviews. Promote innovation and continuous improvement through collaborative engineering practices
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested

Skills and Qualifications:

• Bachelor’s or advanced degree in Computer Science, Mathematics, Data Science, or a related technical field, advanced degree preferred
• 6+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus
• Deep proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $170,000-$240,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform. 

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy. 

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources and applying ML to enrich our datasets with predictive and generative intelligence.  

Primary Job Responsibilities:

• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities 
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards 
• Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best practices 
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities 
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects 
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices 
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles 
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested   

Skills and Qualifications:

• Bachelor’s degree in Computer Science, Mathematics, Data Science, or related technical field, advanced degrees are preferred 
• 2+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction 
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact 
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus 
• Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake 
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $125,000-$180,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite

What You’ll Do

Are you a senior-level data scientist with a passion for building and deploying high-impact fraud or credit risk models? Koalafi is seeking an experienced Data Scientist to lead the development, deployment, and monitoring of machine learning models that sit at the core of our portfolio’s profitability. This role requires someone who thrives in an end-to-end environment—designing predictive models, operationalizing them in production, and ensuring they continue to perform in a dynamic market.

You will be a key contributor to Koalafi’s decisioning ecosystem, owning models that directly influence credit outcomes, fraud mitigation, and the financial performance of the company. Beyond technical expertise, you will bring strong business intuition, enabling you to translate modeling insights into strategic decisions. This position reports to the Manager of Data Science and regularly partners with senior leaders across Risk, Fraud, Analytics, and Technology.

Responsibilities

• Build, deploy, and maintain production-grade credit and fraud models that are foundational to our real-time decisioning platform and essential to portfolio profitability
• Own the full MLOps lifecycle—from feature engineering, model training, and experiment management to production deployment, performance monitoring, drift detection, and continuous optimization
• Architect and scale end-to-end ML pipelines, ensuring reliability, reproducibility, and seamless integration with core decisioning services
• Design robust model monitoring frameworks that enable tracing, profiling, explainability, and rapid root-cause analysis for production incidents or model degradation
• Partner with data science, risk, and engineering leaders to shape modeling strategy, improve credit policy, and strengthen fraud defenses in response to customer behavior and macroeconomic trends
• Drive continuous improvement of existing models, incorporating new data sources, advanced techniques, and rigorous validation processes
• Communicate complex model logic and insights to non-technical stakeholders, clearly linking modeling decisions to business outcomes and strategic priorities

About You

• 5+ years of hands-on experience building and deploying machine learning models, with a strong grasp of the end-to-end modeling lifecycle from feature engineering to validation and productionization
• 5+ years of professional experience writing performant, maintainable Python code in a collaborative production environment, leveraging core data science libraries like pandas, numpy, xgboost, and scikit-learn
• 2+ Years of experience working on Credit or Fraud risk models
• Proficient in SQL for querying, transforming, and analyzing large datasets, and comfortable working across relational databases and cloud-based data platforms
• Strong understanding of data structures, algorithms, and software engineering principles, and apply them to build robust and scalable data solutions
• Bachelor’s degree in a quantitative or STEM field (e.g., Statistics, Mathematics, Computer Science, Engineering) and demonstrate strong analytical and problem-solving skills in your work
• Location Requirement: This position requires regular in-person attendance at one of our two office locations (Richmond, VA or Arlington, VA). Candidates must already be located within a commutable distance to either location, as relocation assistance is not available at this time

Preferred Qualifications

• Advanced technical and analytical background, ideally with a Master’s or PhD in a quantitative or STEM field, and a strong understanding of probability, statistics, and predictive modeling algorithms (e.g., Boosting, Random Forests, Decision Trees, Bayesian models)
• Exposure to data and compute platforms such as Snowflake and Databricks
• Background in financial services or experience working in fast-moving, high-growth environments such as startups
• Experience with modern ML infrastructure and tooling, including MLOps frameworks (e.g., MLflow, BentoML), CI/CD automation, and model observability, monitoring, and lifecycle management
• Familiarity with large language models (LLMs) and their deployment in production environments