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.

ABOUT THE TEAM

The Discovery team at Anduril is at the forefront of incubating and maturing high-potential, software-defined, AI-native offerings that meet the toughest, newest challenges across hardware, software, space, and cyber domains. We're the architects of mission autonomy and mesh networking, delivering scalable hardware solutions that meet some of the most urgent national security needs. By working hand-in-hand with elite teams in Perception, AI, Motion Planning, Hardware, Test Engineering, Space, Networking, and Vehicle hardware, we craft cutting-edge, end-to-end systems that redefine mission success.

ABOUT THE JOB

As a Staff Modeling and Simulation Engineer, you will own the understanding and design of the mission solution which includes designing mission trajectories, building models to help craft mission solutions, and developing simulations to solve key mission needs. You will carefully listen to stakeholder needs and then design rigorous math and physics analyses leading to clear and compelling value propositions. You will work closely with related teams, including Systems Engineering, GNC, Software, Mission Operations, Hardware Engineering and others. You will lead physics-level modeling, mission design, constellation design, simulation and analysis for a wide variety of defense missions.

This role is directly tied to ongoing, funded programs within Anduril’s Discovery Business Line. The programs require building and fielding a resilient, software-defined spacecraft systems across numerous mission threads. We work with mission partners and customers to deploy reliable and robust capabilities on operationally relevant fielding timelines to meet complex challenges across the DOD and IC.

WHAT YOU’LL DO

• Develop model-driven analysis (and often the models themselves)
• Develop a deep understanding of transformational value of Anduril platform, autonomy, simulation, and perception products
• Use our advanced internal M&S capabilities to give our analyses an asymmetric advantage over competitors
• Convey the value through life of AI-powered distributed systems over traditional industrial offerings
• Provide rigorous analytical products which will be used to guide hardware engineering and convince stakeholders of our value advantage

REQUIRED QUALIFICATIONS

• Currently possesses and is able to maintain an active U.S. Top Secret security clearance
• Strong domain experience in fields like missile defense, Space, radar, sensor fusion, etc. 
• Proven track record of independently owning and executing program deliverables with little to no management
• Outstanding communication skills to include visual presentation of complex data
• Proficiency with physics-math scripting (e.g., MATLAB, SIMULINK, Python+numpy, scipy)
• Strong engineering background, preferably in Astrodynamics, Aerospace Engineering, Dynamics and Controls Engineering, or other related engineering field

PREFERRED QUALIFICATIONS

• 10+ years in a relevant Science/Engineering field
• Space Mission MS&A experience - for example, working knowledge of constellation design, space trajectory design, and physics-level modeling across a wide variety of space missions
• Spacecraft & Payload MS&A experience— ability to perform physics-based trade-space analyses for spacecraft propulsion, power, thermal management, and payloads such as RADAR, SATCOM, and/or EOIR
• Rendezvous Proximity Operations (RPO) Trajectory Design & Space Payloads experience
• Strong background in orbital mechanics and space environment
• Exceptional proficiency with physics-math scripting of your choice (e.g., MATLAB, SIMULINK, Python+numpy, scipy)
• Proficiency with STK and Astrogator
• Proficiency with AFSIM
• Experience with genetic algorithms, machine learning, AI, and reinforcement learning algorithms

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%.

Data Scientist 

Location: Woodinville, WA

Details: Hybrid 

Redapt Inc. is a pioneering world-class data center infrastructure integrator, technology engineering firm, and cloud services provider. Our teams focus on delivering innovative solutions and services that power our customers' most demanding applications and enable them to extract powerful insights from data that drive true business value.   

We are looking for a versatile AI/ML Engineer who can lead, sell, design, and implement modern architecture for a diverse set of customers and industries. The ideal candidate would have deep experience in designing high-value advanced analytics solutions utilizing popular analytical frameworks running on Azure, GCP, and AWS. This position will be responsible for leading customer conversations, creating and presenting project architecture, and leading delivery.

Primary responsibilities include mentoring and leading other consultants, leading pre-sales workshops with finance and technology executives to uncover innovative ways to apply advanced analytics techniques to solve business problems in new ways. The role can be hands-on when necessary but should have Direct delivery experience to recommend technologies, solutions, and help troubleshoot.    

Responsibilities: 

• Drive growth through business development, resourcing, and quality delivery. 

• Monitor business impact and value generation of analytics projects. 

• Help create go-to-market strategies around advanced AI/ML Services and hardware. 

• This role will be directly involved in the business development process, delivering customer demos to show the value of how data can drive business goals. 

• Create proposals and SOWs. 

• Work closely with sales and other practice leaders to recommend strategies to grow our data science services. 

• Manage full sales cycles, end-to-end, for high potential clients. 

• Evaluate business impact and priority initiatives for our portfolio of managed analytics customers.  

• Talent Leadership and Product Ownership. 

• Help with planning and staffing for data science projects. 

• Provide support for project managers through developing tasks, estimates, and dependencies to meet expectations. 

• Train the data science team on best practices and new technology initiatives.  

• Anticipate the impact of new technologies and frameworks and help create compelling data science offerings to our clients. 

Skills you bring with you: 

• Knowledge of how to use data science/AI/ML techniques in operations to impact corporate financials.  

• Working knowledge of DevOps process (CI/CD) applied to data science and ML ops. 

Qualifications: 

• Bachelor’s or Master’s Degree in Advanced Math, Data Science, or Computer Science.  

• 5-8+ years of experience with advanced data science techniques, frameworks, libraries, and technologies including but not limited to: 

• Tensorflow, KubeFlow, Python, R, Keras, NumPY, SciKit, PyTorch, SQL.
  
  
• Azure ML, Vertex AI, SageMaker, Databricks, Big query/Redshift/Snowflake
  
  
• ELT/ELT/Pipeline Design, Data Modeling, Spark, Airflow/DBT and API Integration Patterns

Nice to have: 

• LLM’s, RAG, Vector Databases, Prompt Evaluation, GenAI Solution Patterns 

The base salary range for this full-time position in the US is $130,000 - $140,000 annually + bonuses + benefits.  Redapt salary ranges are determined by role, level, and location.  The salary range displayed in each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations.  Please note, the base pay offered may vary within the range depending on a wide array of factors including but not limited to work location, job related knowledge/skills, relevant education/training, and level of experience.  Please note that the compensation details listed in the US role postings reflect the base salary only, and do not include bonuses or benefits. 

Equal Employment Opportunity: 

Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need. 

#LI-TS1

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