We are looking for a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.

As a Manager, CSE (AI & Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.

This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.

The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering “white-glove” experiences for strategic customers.

What You’ll Do:

Team Leadership & Development

• Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth
• Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.
• Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.
• Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.
• Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.
  
  

Strategic Customer Support

• Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.
• Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.
• Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.
• Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.

Technical & Cross-Functional Operations

• Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
• Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product — including Jira escalation routing, Sev1 bridge management, and post-incident documentation.
•  Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content — treating documentation infrastructure as a core operational lever for team scalability.
• Contribute to the vision for AI and automation within support—building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.
• Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.

Key Metrics:

• Customer Satisfaction (CSAT) for strategic accounts
• Time to Response and Resolution (TTR) for strategic customers
• Tier 1 resolution rate vs. escalation rate
• Time-to-escalation and engineering handoff SLA adherence
• SLA adherence and escalation response times
• Support productivity and quality (QA scores)
• Post-incident documentation completion rate

What You’ll Add to DigitalOcean:

• Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.
• Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.
• Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.
• Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
• Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.
• Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.

Preferred Qualifications:

• Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).
• Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• ITIL or equivalent service management certification

Compensation Range: 

• $125,000 - $153,000

*This is a remote role

JR: 2026-7692

#LI-Remote

Who we are

About Stripe

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

What you’ll do

About the internship

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

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

Responsibilities

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

Who you are

Minimum requirements

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

Preferred qualifications

You Might Also Have:

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

Application requirements

Please submit the following with your application:

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

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

The Community You Will Join:

At Airbnb, we believe technology has the power to bring people together — and our engineers are the ones building it. Our Engineering org is a diverse, fast-moving group of teams working across Payments, Trust, Marketing, Relevance & Personalization, and more. Together, we're tackling some of the hardest problems in tech: search relevance at global scale, fraud prevention, seamless payments, and fueling growth — all while delivering a product experience that feels effortless and beautiful. We're also at the forefront of integrating AI and machine learning into our products — from personalized search experiences to intelligent trust and safety systems — and we're looking for curious engineers who are excited to grow alongside this technology.

If you're energized by engineering that creates real-world human connection — and by the idea that your code will be experienced by millions of people around the world — you'll feel right at home here.

The Difference You Will Make:

As a Software Engineer (New Grad) at Airbnb, you’ll play a vital role in building, supporting, and refining the products and systems that make Airbnb’s mission possible. Your work will directly contribute to high-quality, reliable experiences for our global community—whether you’re fixing bugs, launching well-defined features, or enhancing existing components. You'll also have the opportunity to contribute to AI-powered features, applying foundational knowledge of machine learning concepts and modern AI tools to build smarter, more personalized experiences for our hosts and guests. By clearly communicating challenges and collaborating with teammates across functions, you’ll help drive projects forward with transparency and trust.

You’ll foster a sense of belonging by actively seeking feedback, sharing your own learnings, and supporting the onboarding of new team members. You’ll help uphold Airbnb’s commitment to excellence by following best practices, delivering tasks autonomously, and continually improving your technical skills. Your curiosity, empathy, and commitment to candid communication will empower you to make a meaningful impact—on projects, teammates, and Airbnb’s inclusive culture.

A Typical Day: 

• Attend team syncs to discuss priorities, share progress, and surface any blockers with transparency.
• Dive into coding—fixing bugs, developing features, or refining APIs and components—while applying best practices for code quality, error handling, and testability. Leverage AI-assisted development tools (e.g., Claude Code or similar) to accelerate your workflow and improve code quality.
• Participate in design or code reviews, ask clarifying questions, and apply feedback to improve your work. Work closely with cross-functional partners like product managers and designers to ensure your tasks align clearly with broader goals.
• Dedicate time to expanding your technical knowledge through documentation, mentorship, or internal knowledge-sharing sessions. This includes staying current on AI/ML developments relevant to your team's domain — whether that's recommendation systems, natural language understanding, or AI safety practices. Seek guidance from managers or tech leads when tackling unfamiliar problems.
• Contribute to team activities, such as onboarding new hires (e.g., being an onboarding buddy), sharing observations from the hiring process, or joining in cultural events focused on diversity, inclusion, and innovation.
• Share updates on your progress and next steps, highlighting challenges or learnings. 

Your Expertise:

This role is designed for recent graduates (Bachelor's or Master's) with less than 1 year of full-time professional experience who are ready to grow fast and make an impact.

• Strong foundation in Computer Science fundamentals — data structures, algorithms, design patterns, and systems thinking
• Proficiency in one or more of: Java, Scala, Ruby, Ruby on Rails, C++, SQL, HTML/CSS, JavaScript, Objective-C, Swift (iOS), or Kotlin (Android)
• Foundational awareness of AI/ML concepts — such as supervised learning, model evaluation, or working with APIs backed by large language models (LLMs) — gained through coursework, personal projects, or internships
• Familiarity with Python and common AI/ML libraries (e.g., NumPy, scikit-learn, or PyTorch) is a plus, as is experience integrating cloud-based AI services or LLM APIs
• An understanding of responsible AI principles — including fairness, privacy, and safety — and a curiosity about how these apply to real-world product development
• Bonus points for leadership experience, community involvement, or teaching/mentoring — we love engineers who invest in others

Your Location:

Preference for candidates based in San Francisco, California or Seattle, Washington with the ability to commute to the office three days per week. Additional in-person attendance for team meetings or offsites may be required as needed. Domestic Relocation support will be provided for candidates open to relocating.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

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

Your Role at impact.com:

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

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

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

What You'll Do:

Yield Optimization & Pricing Models

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

Inventory Allocation & Supply Optimization

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

Data Architecture & Feature Engineering

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

Real-Time Inference & Production ML

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

Experimentation & Performance Measurement

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

Self-Learning Systems & Feedback Loops

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

Cross-Functional Collaboration

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

What You Bring:

Required

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

Preferred / Nice to Have

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

What Sets You Apart

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

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

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

Benefits and Perks: 

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

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

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

#LI_Seattle

ABOUT THIS OPPORTUNITY

We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren't just an expert in XGBoost or Transformers; you are an expert in building the pipelines that make these models reliable, scalable, and impactful.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.
• GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.
• MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.
• Strategic Leadership: Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• 5+ years in a professional Data Science role with a track record of deploying models at scale.
• Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus.
• Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL.
• Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference).
• Experience with ETL/ELT processes, specifically using dbt.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

Our Tech Stack

• Data Warehouse: BigQuery
• Orchestration: Airflow (Cloud Composer)
• Modeling: Vertex AI Pipelines, JupyterLab
• Deployment: Docker, GKE (Google Kubernetes Engine)

Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in.

What Sets You Apart

• The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates.
• Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources.
• Communication: You can explain the "why" behind a complex neural network architecture to an executive without using jargon.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions. For this position, applicants can expect to make between $126,000 to $149,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

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 an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook’s MLOps team. The team is responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team’s work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.

Primary Job Responsibilities:

• Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
• Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
• Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
• Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
• Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
• Ensure MLOps roadmap items are delivered on time and have exceptional quality
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders
• Establish and drive a culture founded on creating belonging, psychological safety, candor, connection, cooperation, and fun
• Understand how to apply agile, lean, and principles of fast flow to team efficiency and productivity 
• 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, Master’s, or PhD in Computer Science, Mathematics, Data Science, or a related field
• 3+ years of experience in an engineering leadership role, managing globally distributed teams
• 6+ years of experience in hands-on development of Machine Learning algorithms
• 6+ years of experience in hands-on deployment of Machine Learning services
• 6+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• 6+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 70%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, and KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions
• Ability to be a team player who can also work independently
• Experience working across multiple development teams is a plus
• Proficiency with the Microsoft Office suite including in-depth knowledge of Outlook, Word, and Excel with the ability to pick up new systems and software easily 
• 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: $240,000-$300,000
• Target annual bonus percentage: 15%

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-TK1

#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 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

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 an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook’s MLOps team. The team is responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team’s work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.

Primary Job Responsibilities:

• Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
• Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
• Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
• Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
• Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
• Ensure MLOps roadmap items are delivered on time and have exceptional quality
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders
• Establish and drive a culture founded on creating belonging, psychological safety, candor, connection, cooperation, and fun
• Understand how to apply agile, lean, and principles of fast flow to team efficiency and productivity 
• 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, Master’s, or PhD in Computer Science, Mathematics, Data Science, or a related field
• 3+ years of experience in an engineering leadership role, managing globally distributed teams
• 6+ years of experience in hands-on development of Machine Learning algorithms
• 6+ years of experience in hands-on deployment of Machine Learning services
• 6+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• 6+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 70%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, and KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions
• Ability to be a team player who can also work independently
• Experience working across multiple development teams is a plus
• Proficiency with the Microsoft Office suite including in-depth knowledge of Outlook, Word, and Excel with the ability to pick up new systems and software easily 
• 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: $240,000-$300,000
• Target annual bonus percentage: 15%

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-TK1

#LI-Onsite