ML Engineer
Research Engineer building and deploying production voice and multimodal ML models. Requires expert PyTorch, large-scale model training experience, and shipping user-facing ML systems.
About the job
Responsibilities
- Own evaluation pipelines — design, build, and automate offline and live evals that keep our speech and multimodal models honest in production.
- Harness the data — create tooling for safe, versioned, privacy-aware dataset curation and discovery.
- Ship models, not slide decks — partner with research and infra to prototype, train, and deploy state-of-the-art voice models that power Sesame’s real-time companion experience.
- Squeeze silicon — scale training and inference for LLM-class workloads; chase latency, throughput, and cost until the graphs flatten.
- Wire up monitoring and live evals — surface quality regressions before users or PMs notice.
- Move at startup speed — take ideas from whiteboard to production in days, not quarters; leave a clean trail of tests and dashboards behind.
Required Qualifications
- Expert-level PyTorch.
- Proven software engineer who loves ML; comfortable writing production code across the stack.
- Hands-on experience training or fine-tuning large language or other large-scale models with a variety of techniques.
- Evaluation expert — you’ve designed metrics and harnesses that actually predict user happiness.
- Deep knowledge of the ML lifecycle: dataset ops, training pipelines, eval frameworks, deployment, and monitoring.
- History of shipping complex projects to production—especially user-facing, online ML systems—despite shifting requirements and surprise roadblocks.
- High agency and the judgment to know when to sprint solo vs. pull in the squad.
- Track record of setting technical direction, driving consensus, and partnering smoothly with product, infra, and research.
Benefits
- 401 (k) max employer match: 3.5% of compensation
- 100% employer-paid health, vision, and dental benefits for you and your dependents
- Unlimited PTO and sick time
- Flexible spending account with employer matching up to $1,650/year (medical FSA)
- Guardian Employee Assistance Program (EAP)
- Opportunity to share in the company's success with competitive stock options
Skills
PyTorch, Python, Machine Learning, LLMs, Model Training, Model Fine-Tuning, Evaluation Pipelines, Dataset Curation, Ml Deployment, Production Ml Systems
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