×
Register Here to Apply for Jobs or Post Jobs. X

Sr. Machine Learning Engineer

Job in Menlo Park, San Mateo County, California, 94029, USA
Listing for: TEKsystems c/o Allegis Group
Full Time position
Listed on 2026-07-29
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 70 - 85 USD Hourly USD 70.00 85.00 HOUR
Job Description & How to Apply Below
Senior Machine Learning Engineer (LLM Evaluation & AI Agents)

Location: Menlo Park, CA (Hybrid)
Employment Type: 6-Month Contract
Compensation: $70.00-$85.00/hour (W-2)

Help Advance the Next Generation of AI Agents

We're seeking a Senior Machine Learning Engineer to support the development of advanced AI systems capable of interacting with software, tools, and digital environments. This role focuses on evaluating model performance, identifying failure patterns, building benchmark frameworks, and delivering insights that directly improve model quality and training outcomes.
You'll work closely with machine learning researchers, engineers, and cross-functional partners in a fast-moving environment where experimentation, analysis, and problem-solving are central to success.

What You'll Do
  • Design, build, and maintain benchmark suites and evaluation frameworks for AI/ML models
  • Execute large-scale model evaluations and analyze performance across checkpoints
  • Investigate model failures and identify root causes behind poor performance
  • Develop Python and SQL workflows to process, transform, and analyze large datasets
  • Automate evaluation and reporting processes to improve efficiency and scalability
  • Partner with researchers and engineering teams to translate findings into model improvements
  • Document methodologies, experiments, and results
  • Communicate technical findings clearly to both technical and non-technical stakeholders
Required Qualifications
  • Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field
  • 5+ years of hands-on experience developing with Python and SQL
  • 3+ years of applied Machine Learning or ML Engineering experience
  • Experience evaluating machine learning models and analyzing performance metrics
  • Experience designing, implementing, or improving benchmarking and evaluation frameworks
  • Strong analytical and problem-solving skills with the ability to perform detailed failure analysis
  • Experience working with large-scale datasets and data pipelines
  • Comfortable working in Linux-based environments
  • Strong communication and collaboration skills
Preferred Qualifications
  • Experience evaluating Large Language Models (LLMs) or Generative AI systems
  • Exposure to Reinforcement Learning (RL) or Reinforcement Learning from Human Feedback (RLHF)
  • Experience building automated evaluation pipelines
  • Familiarity with agentic AI systems, AI assistants, or autonomous agents
  • Research experience, publications, or contributions to ML/AI projects
What Success Looks Like
  • Delivering reliable benchmark and evaluation frameworks
  • Identifying actionable model failure trends and root causes
  • Providing data-driven recommendations that improve model quality
  • Building scalable evaluation processes that accelerate research and development efforts
  • Collaborating effectively across research, engineering, and product teams
Work Environment
  • Hybrid work arrangement based in Menlo Park, California
  • Collaborative team spanning multiple locations
  • Fast-paced research and engineering environment with evolving priorities
  • Opportunity to work on cutting-edge AI and machine learning initiatives
Interested?

If you're passionate about machine learning evaluation, AI systems, data analysis, and solving complex technical challenges, we'd love to hear from you. Apply today to help shape the future of intelligent systems.
Job Type & Location
This is a Contract position based out of Menlo Park, CA.
Pay and Benefits
The pay range for this position is $70.00 - $85.00/hr.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
Medical, dental & vision Critical Illness, Accident, and Hospital 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available Life Insurance (Voluntary Life & AD&D for the employee and dependents) Short and long-term disability Health Spending Account (HSA) Transportation benefits Employee Assistance Program Time Off/Leave (PTO, Vacation or Sick Leave)
Workplace Type
This is a hybrid position in Menlo Park,CA.
Final date to receive applications
This position is anticipated to close on Aug 10, 2026.

About TEKsystems

We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change.

That's the power of true partnership. TEKsystems is an Allegis Group company.

The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender…
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary