Contribute to the design, development, and testing of various inference optimization algorithms
Design, implement, and optimize model compression pipelines
Develop and maintain speculative decoding frameworks
Collaborate closely with research scientists to translate experimental ideas into robust, production-ready systems
Profile and optimize end-to-end LLM performance
Benchmark, evaluate, and implement strategies for optimal performance on target hardware
Build tools to streamline model training, evaluation, and deployment
Participate in technical design discussions and propose innovative solutions
Contribute to open-source projects, code reviews, and documentation
Mentor and guide team members, fostering a culture of continuous learning and innovation
Stay current with LLM architectures, inference optimizations, and hardware advancements.

Strong understanding of machine learning and deep learning fundamentals
Experience in LLM Inference Optimizations and NLP
Experience with tensor math libraries such as PyTorch and NumPy
Strong programming skills with proven experience implementing Python based machine learning solutions
Ability to develop and implement research ideas and algorithms
Experience with mathematical software, especially linear algebra
Understanding of Linear Algebra, Gradients, Probability, and Graph Theory
Strong communications skills with both technical and non-technical team members
BS, or MS in computer science or computer engineering or a related field
A PhD in a ML related domain is considered a strong plus.

Senior Machine Learning Engineer

Key skills