Software Engineer - ML Model Performance

Baseten

San Francisco (CA)

On-site

USD 150,000 - 250,000

Full time

14 days+
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Benefits offered by this job

Competitive compensation with equity
100% medical, dental, and vision insurance
Generous PTO policy
Paid parental leave
Company‑facilitated 401(k)

Job summary

A leading AI technology company based in San Francisco is seeking a motivated Software Engineer to enhance ML performance. This role involves implementing advanced techniques for ML model inference, collaborating in a dynamic team, and tackling performance optimization challenges. Ideal candidates will have a relevant degree, programming experience (Python or C++), and familiarity with LLM optimization. This position offers competitive compensation, comprehensive health coverage, and generous PTO policies.

Qualifications

  • Degree in Computer Science, Engineering, Mathematics, or related field.
  • Experience with general‑purpose programming languages.
  • Familiarity with LLM optimization techniques.

Responsibilities

  • Implement and productionize techniques for ML model inference.
  • Deep dive into codebases to debug ML performance issues.
  • Collaborate with a diverse team to design solutions.

Skills

Experience with Python or C++
Familiarity with LLM optimization techniques
Strong familiarity with PyTorch
Understanding of GPU architecture

Education

Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or related field

Tools

TensorRT
CUDA
Docker
Kubernetes

Job description

A leading AI technology company based in San Francisco is seeking a motivated Software Engineer to enhance ML performance. This role involves implementing advanced techniques for ML model inference, collaborating in a dynamic team, and tackling performance optimization challenges. Ideal candidates will have a relevant degree, programming experience (Python or C++), and familiarity with LLM optimization. This position offers competitive compensation, comprehensive health coverage, and generous PTO policies.
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