Engineering Manager - Model Performance

Join Our Dynamic Team at Baseten

Join our dynamic team at Baseten, where we're revolutionizing AI deployment with cutting-edge inference infrastructure. Backed by premier investors such as IVP, Spark Capital, Greylock, and Conviction, we're trusted by leading enterprises and AI-driven innovatorsincluding Descript, Bland.ai, Patreon, Writer, and Robust Intelligenceto deliver top-tier performance, security, and reliability for their production workloads. With our recent $75 million Series C funding, we're poised to accelerate our mission to make AI accessible across all products. If you're passionate about tackling impactful challenges and building transformative solutions from the ground up, we invite you to join us on this exciting journey!

The Role

Are you passionate about advancing the frontiers of artificial intelligence while leading a team of exceptional engineers? We are looking for a Tech Lead Manager focused on ML performance and inference. This role is ideal for someone with a strong engineering background who is eager to lead and mentor a team while remaining hands-on with technology. If you thrive in a fast-paced startup environment and are excited about both leadership and technical challenges, we want to hear from you.

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 package (Unlimited PTO, 401k, covered healthcare premiums).
• An opportunity to lead a talented engineering team at a rapidly growing startup in the machine learning space.
• Inclusive and supportive work culture with ample opportunities for professional development.
• Exposure to a wide range of ML use cases, offering unmatched learning and networking potential.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.