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BasetenBasetenSan Francisco, CA

Engineering Manager - Model Performance

Leads a team optimizing ML model inference and performance, focusing on frameworks like PyTorch, TensorRT, and CUDA. Requires 5+ years software engineering experience with 2+ years technical leadership, plus expertise in production AI/ML scaling.

260k – 380k/yr
Hybrid5+ YOEEngineering Management

About the role

Responsibilities

  • Lead, mentor, and manage a team of engineers focused on developing and optimizing ML model inference and performance.
  • Oversee technical strategy and architecture decisions, driving improvements across our engineering organization.
  • Collaborate with cross-functional teams to ensure seamless integration and scalability of ML models in production environments.
  • Dive into the codebase of frameworks like TensorRT, PyTorch, CUDA, and others to identify and solve complex performance bottlenecks.
  • Drive the development and deployment of large-scale optimization techniques for various ML models, especially large language models (LLMs).
  • Own the full lifecycle of projects from inception through delivery, including planning, execution, and resource management.
  • Foster a collaborative, inclusive team environment that encourages continuous learning and growth.

Requirements

  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, or a related field.
  • 5+ years of professional experience in software engineering, with at least 2 years in a technical leadership role.
  • Proven experience managing and mentoring teams of engineers.
  • Expertise in one or more programming languages, such as Python, C++, or Go.
  • In-depth understanding of ML model performance optimization, especially using libraries such as PyTorch, TensorRT, and CUDA.
  • Strong knowledge of containerization (Docker) and orchestration systems (Kubernetes).
  • Experience with production-level AI/ML solutions, including scaling and deploying large models.
  • Ability to balance hands-on technical work with team leadership and project management.

Bonus Points

  • Experience enhancing the performance of large language models (LLMs) or similar AI systems.
  • Familiarity with LLM optimization techniques such as quantization, speculative decoding, or continuous batching.
  • Deep knowledge of GPU architecture and performance tuning.
  • Previous experience in a high-growth startup environment.

Benefits

  • Competitive compensation, including meaningful equity.
  • 100% coverage of medical, dental, and vision insurance for employee and dependents.
  • Generous PTO policy including company wide Winter Break.
  • Paid parental leave.
  • Company-facilitated 401(k).
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Skills

PyTorchTensorRTCUDAPythonC++GoDockerKubernetesLLMs
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