Machine Learning Engineer - New Grad

The role

You will train and evaluate models to make large language models cheaper and more capable to serve. This includes training speculative decoding models, compressing models, and designing agentic workflows.

What you will do

• Train, evaluate, and tune speculative decoding models to increase acceptance rates on production workloads.
• Develop and implement optimization techniques like quantization, sparsity, distillation, pruning, and parameter-efficient fine-tuning.
• Build and evaluate agentic systems including tool calling, multi-step planning, retrieval, and long-context reasoning.
• Design rigorous evaluations and benchmarks.
• Translate recent research into working implementations and run ablations.
• Partner with AI performance, compiler, runtime, and product teams to ship model improvements.
• Contribute to emerging areas such as reinforcement learning, post-training, and reward modeling.

Required qualifications

• B.S. in Computer Science, Electrical Engineering, Mathematics, or a related field
• Strong programming skills in Python
• Solid foundation in machine learning, linear algebra, probability, and numerical computing
• Hands-on experience with PyTorch, TensorFlow, or JAX
• Working knowledge of transformer architectures and the LLM training or inference pipeline
• Ability to design a clean experiment, interpret results honestly, and communicate findings clearly

Nice to have

• M.S. or Ph.D. in Computer Science, Electrical Engineering, or a related field
• Research or internship experience in LLM training, post-training, or inference
• Experience with speculative decoding, distillation, quantization, sparsity, or other model efficiency techniques
• Experience building agentic systems, tool-calling pipelines, or LLM evaluation harnesses
• Familiarity with reinforcement learning or preference optimization (RLHF, DPO, GRPO, reward modeling)
• Experience with distributed training frameworks (FSDP, DeepSpeed, Megatron) or inference frameworks such as vLLM, SGLang, or TensorRT-LLM
• Publications at ML venues (NeurIPS, ICML, ICLR, ACL, EMNLP) or meaningful open source contributions

Benefits

• Base salary plus equity
• 95% premium coverage for employee medical insurance
• 77% premium coverage for dependents
• Health Savings Account (HSA) with employer contribution
• Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&H insurance plans
• Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care
• Headspace subscription
• Gympass+ membership
• One Medical membership
• Counseling services with an Employee Assistance Program

Before you apply

• You must submit an application form for each position for which you believe you are qualified

About the company

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide.