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Senior Software Engineer, LLM Platform

Handshake · San Francisco, California

Location
San Francisco, California, United States
Employment
Full time
Level
Senior
Posted
10 July

About this role

About Handshake

Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.

In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.

Why join Handshake now:

  • Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel

  • Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions

  • Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders

  • Build a massive, fast-growing business with billions in revenue

About Handshake AI

Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.

About the Role

We’re looking for a Senior Software Engineer to join our ML Infrastructure & Platform team. This team powers both Handshake’s core career marketplace and Handshake AI by building the shared infrastructure behind our production ML and AI systems.

This is an infrastructure-heavy role for an engineer who enjoys building scalable platforms at the intersection of software engineering, machine learning, and generative AI. You’ll help teams move quickly from prototype to production while building the reliable, high-performance systems that power training, evaluation, and inference across Handshake.

What You’ll Do

  • Build and operate the shared infrastructure behind production ML and AI, including data pipelines, feature stores, training, and model serving.

  • Develop and scale our LLM platform, including provider integrations, orchestration, observability, and controls for cost, latency, and reliability.

  • Build evaluation infrastructure, including LLM eval harnesses, benchmarks, and quality measurement pipelines.

  • Support post-training workflows, including fine-tuning, reinforcement learning pipelines, and supporting data infrastructure.

  • Optimize inference infrastructure for open and fine-tuned models, including GPU serving, batching, and autoscaling.

  • Partner with AI, Data Science, and Product teams to productionize new models and establish best practices for ML infrastructure across Handshake.

  • Improve the reliability, scalability, and developer experience of our ML platform.

Desired Capabilities

  • 5+ years of production software engineering experience using Python, Go, TypeScript, or similar languages.

  • Experience building and operating cloud infrastructure on AWS, GCP, or similar platforms.

  • Strong experience with Kubernetes, Docker, Terraform, CI/CD, and operating production services.

  • Hands-on experience building ML infrastructure, including model serving, training pipelines, feature stores, embeddings, or ML observability.

  • Experience with modern data platforms such as BigQuery, Airflow, Spark, Beam/Dataflow, or streaming pipelines.

  • Practical experience building production systems with LLMs or generative AI, including orchestration, provider APIs, observability, and performance optimization.

  • Strong systems design skills, sound engineering judgment, and the ability to thrive in ambiguous, fast-moving environments.

Extra Credit

  • Experience with Ray, Anyscale, KubeRay, Ray Serve, vLLM, Triton, PyTorch, or GPU-backed inference and training.

  • Experience designing LLM evaluation frameworks, benchmarking systems, or quality regression testing.

  • Experience with Vertex AI, Bigtable, Redis, or feature platform infrastructure.

  • Experience with post-training techniques such as fine-tuning, RLHF, reinforcement learning, or reward modeling.

  • Experience building agentic systems, MCP integrations, tool use, memory systems, or voice AI applications.

Perks

Handshake delivers benefits that help you feel supported - and thrive at work and in life.

The below benefits are for full-time US employees.

🎯 Ownership: Equity in a fast-growing company

💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching

🍼 Family Support: Paid parental leave, fertility benefits, parental coaching

💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend

📚 Growth: $2,000 learning stipend, ongoing development

💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office

🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days

🤝 Connection: Team outings & referral bonuses

Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

As published by Handshake. Applications are handled on their site.

Skills this posting mentions

ServiceCI/CDStreaming

About Handshake

Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 500), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond.

All 85 openings at Handshake

One click, then it is written

Apply to Handshake with a resume written for this role.

Queue Senior Software Engineer, LLM Platform and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Handshake’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • 25 sent a week, free
  • No card
  • Nothing sent until you say so

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Put this to work

Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

Free, no card. Up to 25 applications sent a week, and nothing is sent until you say so.

Listed from the job board Handshake publishes. Refolk is not the employer and does not handle their hiring. Applications go to Handshake directly.

Hiring at Handshake? Post this role to the Refolk talent pool for $299, once. No commission, refunded if I find nobody. Post a role for $299