Senior Software Engineer, Machine Learning Infrastructure

Apply; San Francisco (CA); On-site; USD 170,000 - 250,000; Full time

Benefits offered by this job

Equity

401(k) match

Parental leave

Medical/dental/vision

Learning stipend

Office perks SF

Job summary

Handshake is seeking a Senior Software Engineer to join our ML Infrastructure & Platform team, powering Handshake’s core career marketplace and Handshake AI by building shared infrastructure for production ML and AI systems, including training, evaluation, and inference.

You will work on scalable cloud-based services with Python/Go/TypeScript, Kubernetes, Terraform, and CI/CD, collaborating with AI, Data Science, and Product teams to productionize models, improve observability, and optimize cost

Qualifications

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

Responsibilities

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

Skills

Python

Go

TypeScript

Cloud infrastructure

Kubernetes

Docker

Terraform

CI/CD

ML infrastructure

Education

Bachelor's degree in CS or related field

Tools

AWS

GCP

Vertex AI

BigQuery

Airflow

Spark

Beam/Dataflow

Job description

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

• Equity in a fast‑growing company.
• 401(k) match, competitive compensation, financial coaching.
• Paid parental leave, fertility benefits, parental coaching.
• Medical, dental, and vision, mental health support, wellness stipend.
• $2,000 learning stipend, ongoing development.
• Internet, commuting, and free lunch/gym in our SF office.
• Flexible PTO, 15 holidays + 2 flex days.
• Team outings & referral bonuses.

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