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Senior Meta Machine Learning Jobs in Highlands Ranch, CO

As a Senior Associate, you will focus on building meaningful client connections and learning how to ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

... a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and ... Develop machine learning and generative AI models that ship as customer-facing product features

Senior AI/ML Engineer

Denver, CO ยท Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

Senior AI Engineer - SFL Scientific

Denver, CO ยท On-site

$107K - $147K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Senior Applied ML Engineer

Denver, CO ยท Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning systems that power next-generation construction and digital twin solutions. You will apply advanced ML ...

As a Senior Data Scientist at Walmart, you will leverage advanced analytical techniques and ... The team consists of collaborative data scientists and machine learning engineers skilled in ...

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Senior Meta Machine Learning information

See Highlands Ranch, CO salary details

$26.2K

$84.3K

$171.6K

How much do senior meta machine learning jobs pay per year?

As of Jun 15, 2026, the average yearly pay for senior meta machine learning in Highlands Ranch, CO is $84,270.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,600.00 and $108,100.00 per year, depending on experience, location, and employer.

Is L7 senior at Google?

L7 at Google is considered a senior-level position, typically involving significant technical expertise and leadership responsibilities. It is often regarded as a senior or staff level role within Google's engineering hierarchy, requiring extensive experience and advanced skills in areas like machine learning or software development.

How much does L7 make at Meta?

An L7 Senior Meta Machine Learning engineer typically earns a base salary ranging from $250,000 to $350,000 annually, with additional compensation such as bonuses and stock options. Total compensation can exceed $400,000 depending on performance and stock grants. These figures are based on industry reports and may vary by location and experience.

What engineer makes $500,000 a year?

Senior Meta Machine Learning engineers can earn $500,000 or more annually, especially with bonuses and stock options in large tech companies. High compensation typically requires advanced skills in deep learning, extensive experience, and a strong track record of impactful projects.

What is the difference between Senior Meta Machine Learning vs Data Scientist?

AspectSenior Meta Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, ML, or related fields; experience with meta-learning frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch-focused teams developing advanced ML models, often in AI companiesData analysis, modeling, and visualization across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, e-commerce, tech companies

While both roles involve machine learning expertise, Senior Meta Machine Learning specialists focus on developing advanced meta-learning algorithms, often in research settings, whereas Data Scientists apply data analysis and modeling techniques across diverse industries. The roles share similar educational backgrounds but differ in focus and application.

How much does a Meta senior machine learning engineer make?

A senior machine learning engineer at Meta typically earns between $150,000 and $200,000 annually, with total compensation including bonuses and stock options often exceeding this range. Compensation varies based on experience, location, and performance, and the role requires strong skills in deep learning, data analysis, and programming in Python or C++.
What are popular job titles related to Senior Meta Machine Learning jobs in Highlands Ranch, CO? For Senior Meta Machine Learning jobs in Highlands Ranch, CO, the most frequently searched job titles are:
What job categories do people searching Senior Meta Machine Learning jobs in Highlands Ranch, CO look for? The top searched job categories for Senior Meta Machine Learning jobs in Highlands Ranch, CO are:
What cities near Highlands Ranch, CO are hiring for Senior Meta Machine Learning jobs? Cities near Highlands Ranch, CO with the most Senior Meta Machine Learning job openings:
Research Engineer - Machine learning applications to power system operations

Research Engineer - Machine learning applications to power system operations

The National Renewable Energy Laboratory (NREL)

Golden, CO โ€ข On-site

$76K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Job description

Posting Title
Research Engineer - Machine learning applications to power system operations
Location
CO - Golden
Position Type
Regular
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for a researcher who has solid background on machine learning (ML)/artificial intelligence (AI) with enough knowledge about power systems. The candidate will work on research projects that use ML/AI to solve power system problems, specially with the focus on Large Language Models (LLM). Ideal candidate is expected to have in-depth knowledge and extensive research experience related to LLM and agentic AI. Ideal candidate should have solid programming skillset and software development experience. Knowledge and experience about power systems is a plus.
The ideal candidate should be able to conduct research work with limited guidance from senior researchers, and also collaborate with project PI and other power system researchers from the same project team.
Basic Qualifications
Relevant Master's Degree . Or, relevant Bachelor's Degree and 2 or more years of experience . General knowledge and application of engineering technical standards, principles, theories, concepts and techniques. Training in team, task or project leadership responsibilities. Intermediate abilities and knowledge of practices and techniques. Beginning experience in project management. Good writing, interpersonal and communication skills.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
Must have a MS in computer science, electrical engineering, computer engineering or related fields. Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Experience in natural language learning, generative AI, large language models, foundation models, etc.
  • Strong programming skill
  • Experience in using high performance computers, Linux systems

Preferred Qualifications
Preferred Qualifications
  • In-depth knowledge in graph neural networks and reinforcement learning
  • Proven records of research experience related to power systems and power system optimization
  • Have a good fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
  • Proficiency in using Python and machine learning/reinforcement learning packages
  • With strong publication record

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Researcher II / Annual Salary Range: $76,600 - $126,400
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; short*- and long-term disability insurance; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; paid holidays; and tuition reimbursement*. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Limited-term positions are not eligible for long-term disability or tuition reimbursement.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.