What are the responsibilities and job description for the ML Model Serving Engineer position at Sesame?
About Sesame
Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice companions part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive.
Responsibilities
Full-time Employee Benefits
Compensation Range: $175K - $280K
Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice companions part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive.
Responsibilities
- Turbocharge our serving layer, consisting of a variety of LLM, speech, and vision models.
- Partner with ML infrastructure and training engineers to build a fast, cost-effective, accurate, and reliable serving layer to power a new consumer product category.
- Modify and extend LLM serving frameworks like VLLM and SGLang to take advantage of the latest techniques in high-performance model serving.
- Work with the training team to identify opportunities to produce faster models without sacrificing quality.
- Use techniques like in-flight batching, caching, and custom kernels to speed up inference.
- Find ways to reduce model initialization times without sacrificing quality.
- Expert in some differentiable array computing framework, preferably PyTorch.
- Expert in optimizing machine learning models for serving reliably at high throughput, with low latency.
- Significant systems programming experience; ex. Experience working on high-performance server systems—you’d be just as comfortable with the internals of VLLM as you would with a complex PyTorch codebase.
- Significant performance engineering experience; ex. Bottleneck analysis in high-scale server systems or profiling low-level systems code.
- Always up to date on the latest techniques for model serving optimization.
- Familiarity with high-performance LLM serving; ex. experience with VLLM, SGlang deployment, and internals.
- Experience with a public cloud platform such as GCP, AWS, or Azure.
- Experience deploying and scaling inference workloads in the cloud using Kubernetes, Ray, etc.
- You like to ship and have a track record of leading complex multi-month projects without assistance.
- You’re excited to learn new things and work in a multitude of roles.
Full-time Employee Benefits
- 401k matching
- 100% employer-paid health, vision, and dental benefits
- Unlimited PTO and sick time
- Flexible spending account matching (medical FSA)
Compensation Range: $175K - $280K
Salary : $175,000 - $280,000