About Neural Magic
Based in Somerville, Massachusetts, Neural Magic is a series A startup backed by leading investors including Andreessen Horowitz, NEA, NEA, Pillar, VMware, Verizon Ventures, Comcast Ventures, and Amdocs. At Neural Magic we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and VLLM to every enterprise on the planet. Neural Magic accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As a leading developer and maintainer of the vLLM project and inventor of state-of-the-art techniques for model quantization and sparsification, Neural Magic provides a stable platform for enterprises to build, optimize and scale LLM deployments.
Our Mission
Neural Magic is on a mission to bring the power of open-source LLMs and vLLM to every enterprise on the planet.
Your Role
As an ML Engineer, you will work closely with our product and research teams to develop SOTA deep learning software. You will collaborate with our technical and research teams to develop training and deployment pipelines, implement model compression algorithms, and productize deep learning research. If you are someone who wants to contribute to solving challenging technical problems at the forefront of deep learning, this is the role for you!
Join us in shaping the future of AI!
Use your understanding of machine learning to tackle meaningful technical problems
Collaborate with research and product development teams to build machine learning products
Prototype and implement appropriate ML algorithms, tools, and pipelines
Create and manage training and deployment pipelines
Collaborate with a cross-functional team about market requirements and best practices
Keep abreast of developments in the field
Proven experience as a machine learning engineer or similar role
Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc
Knowledge of common ML frameworks (like PyTorch or Keras) and libraries (like NumPy and scikit-learn)
Strong programming skills with proven experience implementing Python-based machine learning solutions
Experience with engineering and supporting ML pipelines in a popular ML framework such as PyTorch, TensorFlow, jax, etc.
Experience with engineering and maintaining training and/or deployment pipelines for Generative models / NLG / LLMs
Ability to interpret and implement research ideas and algorithms
Creative, collaborative, and innovation-focused
Strong sense of project ownership and personal responsibility
Bachelor's in Computer Science, Mathematics or similar field
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