Applied Machine Learning Engineer (LLMs & RL)

Intel Corporation • Santa Clara, CA

2d • 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.
Qualifications: You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Note: For information on Intel’s immigration sponsorship guidelines, please see Intel U.S. Immigration Sponsorship Information

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 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.
• Annual Salary Range for jobs which could be performed in the US: $170,500.00-240,710.00 USD

What This Job Offers

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