Applied Machine Learning Engineer (LLMs & RL)

Job Details:

Job Description:

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

Minimum Qualifications and Experience:

Bachelor's degree (B.S. or B.A.) in Computer Science, Electrical Engineering, Mathematics, Statistics, or related STEM field.

In addition you must have 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.

Preferred Qualifications and Experience:

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

Take the next step in your career journey by applying today, and become part of Intel's mission to shape the future of technology through innovation, collaboration, and excellence.

Job Type: Experienced Hire

Shift: Shift 1 (United States of America)

Primary Location: US, California, Santa Clara

Additional Locations: US, California, Folsom, US, Oregon, Hillsboro

Business group: The Client Computing Group (CCG) is responsible for driving business strategy and product development for Intel's PC products and platforms, spanning form factors such as notebooks, desktops, 2 in 1s, all in ones. Working with our partners across the industry, we intend to deliver purposeful computing experiences that unlock people's potential - allowing each person use our products to focus, create and connect in ways that matter most to them.

Posting Statement:

Position of Trust N/A

Benefits

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.

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

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. Job posting details (such as work model, location or time type) are subject to change.

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.