Applied Machine Learning Engineer (LLMs & RL)

Intel • Folsom, CA

22h • Hybrid

About The Position

We are seeking an Applied Machine Learning Engineer (LLMs & RL) to join our team, focused on fine-tuning large language models (LLMs). This role sits at the intersection of research and engineering: the ideal candidate designs and implements post-training pipelines, develops RL environments and reward models, and conducts training runs to improve model capabilities for agentic applications. You will work with a dynamic team and your key responsibilities will include but are not limited to: Design and maintain post‑training pipelines, from data ingestion through deployment Develop reinforcement learning environments, reward models, and evaluation signals Debug, optimize, and scale distributed training workloads Design and execute research experiments and ablation studies Develop benchmarks and evaluation metrics for model capability and alignment Behavioral traits that we are looking for: Ability to work independently in ambiguous problem spaces Strong debugging and problem‑solving skills Balance of research rigor and engineering execution Clear technical communication and collaborative mindset Demonstrated learning agility and growth mindset Intel invests in our people and offers a complete and competitive package of benefits employees and their families through every stage of life. See Intel Benefits for more details.

Requirements

• Bachelor's degree (B.S. or B.A.) in Computer Science, Electrical Engineering, Mathematics, Statistics, or related STEM field.
• 3+ years of experience in the following:
• Experience in machine learning engineering, data science, ML research or modeling fine tuning.
• Programming: Python/C++ as the primary development language for ML research and engineering
• Core ML fundamentals: LLM architectures, optimization, and model training fine tuning evaluation technics.

Nice To Haves

• Masters or PhD degrees are preferred.
• Hands-on experiences implementing and scaling the full post-training pipeline for language models including supervised fine tuning and reinforcement learning.
• Previous experiences designing and building evaluation frameworks and benchmarks that accurately measure model capability improvements and alignment quality
• Modeling distillation quantization experience

Responsibilities

• Design and maintain post‑training pipelines, from data ingestion through deployment
• Develop reinforcement learning environments, reward models, and evaluation signals
• Debug, optimize, and scale distributed training workloads
• Design and execute research experiments and ablation studies
• Develop benchmarks and evaluation metrics for model capability and alignment

Benefits

• Intel invests in our people and offers a complete and competitive package of benefits employees and their families through every stage of life.
• We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation.
• Find out more about the benefits of working at Intel .

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees