Pitchbook

ML Platform & Infrastructure Engineer

Pitchbook$120K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or equivalent experience
  • 3+ years in Software Engineering, MLOps, or ML Infrastructure
  • Strong Python proficiency
  • Experience building internal developer tools, CLIs, or dashboards
  • Experience with cloud infrastructure (AWS or GCP) and containerization (Docker, Kubernetes)

Responsibilities

  • Design and implement CI/CD pipelines for machine learning workflows
  • Automate data ingestion, job orchestration, checkpointing, and artifact management
  • Build scalable evaluation harnesses for benchmarking models on every merge
  • Optimize latency and resource usage for fast experimentation
  • Develop internal SDKs, CLIs, and lightweight UIs for research tools
  • Implement tracking for model performance and cluster health
  • Create dashboards and alerting systems for real-time performance visibility

Benefits

  • Competitive company-sponsored medical, dental, and vision insurance
  • Top-tier relocation and immigration support
Full Job Description
What You'll Do

Training Automation: Design and implement robust CI/CD pipelines for machine learning workflows. Automate nightly and on-demand training runs, including data ingestion, job orchestration, checkpointing, and artifact management, with reliability as a first-class requirement.

Evaluation Infrastructure: Build scalable evaluation harnesses that automatically benchmark models on every merge. Optimize latency and resource usage so experimentation stays fast, and performance regressions are caught immediately.

Research Tooling: Develop internal SDKs, CLIs, and lightweight UIs (e.g., Streamlit, Retool) that empower researchers to:
  • Inspect trajectories and traces
  • Visualize model failures
  • Curate and manage datasets
  • Iterate without friction

You'll make experimentation ergonomic.

Observability & Performance: Implement comprehensive tracking for:
  • Model latency, throughput, and error rates
  • GPU utilization and cluster health
  • Inference cost and unit economics

Build dashboards and alerting systems that give real-time visibility into system performance and reliability.

Minimum Qualifications
  • Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
  • 3+ years in Software Engineering, MLOps, or ML Infrastructure
  • Strong Python proficiency
  • Experience building internal developer tools, CLIs, or dashboards
  • Experience with cloud infrastructure (AWS or GCP) and containerization (Docker, Kubernetes)


Preferred Qualifications
  • Experience designing CI/CD pipelines specifically for ML workflows
  • Familiarity with LLM serving stacks such as vLLM or TGI
  • Experience managing GPU clusters and optimizing distributed workloads


Why This Role Matters

Great research without great infrastructure slows to a crawl.
Great infrastructure multiplies the impact of every researcher.

You will define how experiments scale, how reliability is measured, and how quickly we can ship improvements to real users. The systems you build will directly shape the speed and quality of our progress toward everyday AGI.

Perks

Competitive company-sponsored medical, dental, and vision insurance
Top-tier relocation and immigration support

How to Apply

Send us:
  • A link - or 60-second video - of something you built and why it matters
  • Your resume or LinkedIn
  • Two sentences on the hardest problem you've cracked


Every exceptional candidate hears back within 48 hours.
If you see possibility where others see limits, we'd love to meet you.

About Pitchbook

PitchBook is a financial data and software company that provides research, analysis, and data on private equity, venture capital, and M&A transactions. The company's platform offers a range of tools and services, including market research, deal sourcing, due diligence, and portfolio management. PitchBook serves a variety of clients, including investment banks, private equity firms, venture capital firms, and corporate development teams. The company was founded in 2007 and is headquartered in Seattle, Washington.
Learn more about Pitchbook
Size
1,000 employees
Industry
Founded
2007

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