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 RoleWe’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 DoBuild 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.
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.
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.
Skills Required
- 5+ years production software engineering experience using Python, Go, or TypeScript
- Experience building and operating cloud infrastructure on AWS or GCP
- Strong experience with Kubernetes, Docker, Terraform, and CI/CD operating production services
- Hands-on experience building ML infrastructure: model serving, training pipelines, feature stores, embeddings, or ML observability
- Experience with modern data platforms: BigQuery, Airflow, Spark, Apache Beam/Dataflow, or streaming pipelines
- Practical experience building production systems with LLMs or generative AI, including orchestration, provider APIs, and observability
- Experience optimizing inference infrastructure for GPU serving, batching, and autoscaling
- Strong systems design skills and ability to thrive in ambiguous, fast-moving environments
- Experience with Ray, Anyscale, KubeRay, Ray Serve, vLLM, Triton, or PyTorch
- Experience designing LLM evaluation frameworks, benchmarking, or quality regression testing
- Experience with Vertex AI, Bigtable, Redis, or feature platform infrastructure
- Experience with post-training techniques such as fine-tuning, RLHF, or reward modeling
Handshake Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Handshake and has not been reviewed or approved by Handshake.
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Leave & Time Off Breadth — Time-off practices include flexible/unlimited PTO, companywide recharge weeks in summer and winter, plus additional volunteer and personal holiday time. Feedback suggests sabbaticals and coordinated breaks help people actually use rest time.
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Parental & Family Support — Parental leave is described as extended for primary and secondary caregivers, and family-oriented policies are highlighted. Fertility and family-support resources are referenced in public materials.
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Healthcare Strength — Core coverage spans medical, dental, and vision, with added mental-health resources and wellness programming. Feedback suggests these supports contribute meaningfully to overall wellbeing.
Handshake Insights
What We Do
Handshake is the #1 place to launch a career with no connections, experience, or luck required. The platform connects up-and-coming talent with 650,000+ employers - from Fortune 500 companies like Google, Nike, and Target to thousands of public school districts, healthcare systems, and nonprofits. Earlier this year, we announced our $200M Series F funding round. This Series F fundraise and new valuation of $3.5B will fuel Handshake’s next phase of growth and propel our mission to help more people start, restart, and jumpstart their careers.
Why Work With Us
How someone builds their career is foundational. We believe in working with the higher education community to help students build meaningful careers. We are at the nexus of universities, students and employers— and we’re able to connect the very best pieces of each side. We’re proud to create a community where students can be more successful.
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