Join Handshake as a Senior Software Engineer to build scalable ML infrastructure for a fast-growing AI data business.
Posted by employer 3 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 5 hours ago
Skills & Technologies
AI in the day-to-day
Handshake AI supports frontier AI labs, working on complex data at large scale.
Requirements
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
The Senior Software Engineer for Machine Learning Infrastructure at Handshake focuses on developing and maintaining the robust infrastructure that supports the company's AI and ML systems. This role requires expertise in cloud platforms, containerization, and building scalable data pipelines, with a strong emphasis on Python, Go, or TypeScript. Ideal candidates have significant experience in production software engineering and a background in machine learning infrastructure, making it suitable for seasoned professionals looking to impact a rapidly growing AI business. Handshake's collaborative environment includes partnerships with leading AI labs and a diverse team of engineers and scientis
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Quick facts
From the original posting
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
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.
Handshake is hiring a Senior LLM Platform Engineer to join our Data and ML Platform team. This team supports Handshake’s core career marketplace and Handshake AI (HAI) by building the shared data, ML, and LLM infrastructure behind production workflows.
This infrastructure-heavy role primarily owns our shared LLM control plane: LiteLLM gateways, provider integrations, shared clients, access controls, observability, cost attribution, capacity management, and hosted or self-hosted inference. You’ll also contribute to adjacent platform systems for workflow orchestration, model serving, shared cloud infrastructure, and developer enablement—working closely with Backend Platform, HAI engineering, data science, and FDEs.
What You’ll Do
Build and operate our LiteLLM-based AI gateways and shared LLM clients.
Own provider and model onboarding, routing, failover, rate limits, and capacity planning.
Build self-service virtual-key, model-access, budget, and credential-management workflows.
Establish SLOs, observability, cost attribution, and alerts for production LLM traffic.
Safely qualify and roll out new models, providers, SDKs, and gateway configurations.
Support hosted and self-hosted inference through a consistent platform interface.
Partner with product, AI, and FDE teams to turn recurring delivery problems into paved-platform capabilities.
Contribute to the broader Data and ML Platform, including workflow orchestration, model serving, shared cloud infrastructure, and developer tooling.
Participate in team on-call and support, improving runbooks, automation, and reliability across owned platform services.
What We’re Looking For
Strong production software engineering experience in Python, TypeScript, Go, or a similar language.
Experience building or operating high-throughput API gateways, proxies, or multi-tenant platform services.
Hands-on experience with Kubernetes, Terraform, CI/CD, and production service ownership.
Practical experience with LLM provider APIs, including streaming, long-running requests, retries, timeouts, cancellation, and rate limits.
Experience with authentication, quotas, credential management, tenant isolation, and auditability.
Experience building observability for distributed systems and leading production incident response.
Experience with usage metering, cost attribution, capacity planning, or FinOps.
Experience with data or ML platform systems such as BigQuery, Airflow, streaming pipelines, model serving, or ML observability.
Strong judgment in ambiguous environments and a bias toward simple, reliable systems that scale.
Bonus Experience
LiteLLM, Portkey, or a comparable multi-provider AI gateway.
vLLM, Modal, Ray, Triton, PyTorch, or GPU-backed serving.
Temporal or another durable-execution system for long-running LLM requests.
Evaluation, batch inference, fine-tuning, RL, or other post-training infrastructure.
Agent runtimes, sandbox infrastructure, MCP, tool use, or coding-agent infrastructure.
Our Stack
Python, TypeScript, Go, LiteLLM, FastAPI, PostgreSQL, Redis, GCP, Kubernetes, Terraform, Spacelift, BigQuery, Airflow, Dataflow/Beam, Datastream, OpenAI, Anthropic, Gemini, OpenRouter, vLLM, Modal, Anyscale/Ray, Datadog, Arize, Temporal, Cloudflare, and Tailscale
Perks
Handshake delivers benefits that help you feel supported—and thrive at work and in life.
🎯 Ownership: Equity in a fast-growing company
💰 Financial Wellness: 401(k) match, competitive compensation, financial 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
🤝 Connection: Team outings & referral bonuses
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