intel

Sr. Machine Learning Engineer

At a Glance

Location
Us, California, Santa Clara
Employment
Full time
Experience
8+ years
Posted
2026-08-14

Key Requirements

Required Skills

Data ScienceMachine LearningPython

Domain Knowledge

  • Engineering

Requirements

8+ years software development background

4+ years of hands-on experience in machine learning engineering, data science or ML research.

Proficient in Python

Research-engineering balance: Ability to produce production-quality implementations of novel research ideas, balancing rigor with speed.

Clear technical communication: Ability to explain research results, architectural decisions, and trade-offs to both technical and non-technical stakeholders.

Intel Benefits | Intel Careers

Compensation & 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: $195,200.00-361,200.00 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.

Responsibilities

At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design.

We believe transformative AI should have a positive impact on people—powerful in capability, yet honest about its limits and protective of the data and resources it touches.

To get there, we build agentic AI that combines the best of local and cloud intelligence — private, affordable, and sustainable by design.

Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving.

Together, they give people real capability without compromise—data stays private, spend stays predictable, and energy use stays in check.

We are seeking a **Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning.