Engineering Manager - Model Performance

ABOUT BASETENBaseten provides the infrastructure, tooling, and expertise needed to bring great AI products to market - fast. Backed by top investors including IVP, Spark Capital, Greylock, and Conviction, we’re trusted by leading AI-driven innovators like Writer, Abridge, Bland, Patreon, Descript, Retool, and Zed to deliver industry-leading performance, security, and reliability for their mission-critical workloads. With our recent $75M Series C funding, we’re growing fast to make AI accessible across all products.THE ROLEAre 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.EXAMPLE INITIATIVESYou'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution availableThe Baseten Inference StackDriving model performance optimizationRESPONSIBILITIESLead, 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.REQUIREMENTSBachelor’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 POINTSExperience 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.BENEFITSCompetitive compensation package (Flexible PTO, 401k, covered healthcare premiums).This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era.An inclusive and supportive work culture that fosters learning and growth.Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.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.

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