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Machine Learning Engineer Jobs in Broomfield, CO

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Machine Learning Engineer

Denver, CO ยท On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Showing results 21-40

Machine Learning Engineer information

See Broomfield, CO salary details

$31.7K

$129.8K

$195K

How much do machine learning engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for machine learning engineer in Broomfield, CO is $129,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $156,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Broomfield, CO?

The most popular types of Machine Learning Engineer jobs in Broomfield, CO are:

What are popular job titles related to Machine Learning Engineer jobs in Broomfield, CO?

For Machine Learning Engineer jobs in Broomfield, CO, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Broomfield, CO look for?

The top searched job categories for Machine Learning Engineer jobs in Broomfield, CO are:

What cities near Broomfield, CO are hiring for Machine Learning Engineer jobs?

Cities near Broomfield, CO with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Broomfield, CO as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $129,752 per year, or $62.4 per hour.

Machine Learning Engineer (SmartBidder)

Silversmith Capital Partners

Boulder, CO โ€ข On-site

$100 - $160/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Key responsibilities

  • Prototype and experiment with machine learning models and algorithms for short-term energy market forecasting.

  • Work with analysts to integrate, evaluate, automate, and generalize data science models within production software.

  • Design and write scalable, production-quality code in Python and implement systems for data collection, storage, and processing at scale.


Job description

Machine Learning Engineer (SmartBidder), Boulder, CO (Hybrid or Remote)

This position will be a key member supporting Ascend Analyticsโ€™ SmartBidder team, which works on optimization and management of energy storage and renewable assets. You will be part of a collaborative team advancing software solutions and analytics to support the cleanโ€‘tech power revolution. Your strong data science skills will support missionโ€‘critical decision analytics for renewable and battery storage power providers around the globe.

Our Mission @ Ascend

At Ascend Analytics, our mission centers on creating sustainable economic value for energy buyers and producers to transform the power industry. Our team combines advanced analytics, cloudโ€‘based technology, and deep market expertise to help our clients solve complex challenges across grid reliability, power market volatility, renewable integration, infrastructure development, and energy investment strategy. As a highโ€‘growth, private equityโ€“backed company, Ascend continues to expand its market leadership while investing in innovation, talent, and scalable solutions for an increasingly dynamic energy market.

Your Impact @ Ascend

Real influence. Real outcomes. At every level.

  • Highโ€‘impact work. Shape the tools and decisions that drive the clean energy transition.
  • Direct exposure. Work alongside executive leadership and key utility and corporate clients.
  • Room to grow. A rapidly scaling SaaS business with real advancement opportunities.
  • Collaborative culture. A team that values creative thought, inclusion, and workโ€‘life balance.
Key Responsibilities
  • Prototype and experiment with novel machine learning models and mathematical/statistical algorithms for shortโ€‘term energy market forecasting.
  • Optimize and enhance computational efficiency of algorithms and software design.
  • Work with our team of analysts to integrate new features, evaluate performance, automate, and generalize data science models within production software.
  • Design and write clean, scalable, production code in Python.
  • Implement systems for collecting, storing, and working with data at scale.
  • Communicate clearly and effectively (orally and in writing) with both technical and nontechnical stakeholders.
  • This position involves working collaboratively both within your software team and outside with the analyst team.
  • The software development team follows an agile scrum process, and all team members are expected to contribute to technical design reviews, implementation strategies, operational system support, and sprint planning.
Key Qualifications Required
  • 2+ Years experience in a highly related role.
  • BS or MS in Engineering, Computer Science, Data/Information Science, Physics, Applied Mathematics, Signal Processing, Operations Research, Statistics, Economics, or Power Systems (or related fields).
  • Experience performing independent research including reading academic papers, developing and testing hypotheses, and analyzing experimental results.
  • Demonstrated academic or professional software coding experience in Python.
  • Familiarity with data processing in Python (including Pandas, Numpy, Sympy, Scikitโ€‘Learn) and machine learning development in Pytorch (or similar).
  • Strong interpersonal skills, a collaborative teamโ€‘first mindset and resultsโ€‘oriented work ethic.
  • Demonstrated interest in the energy sector (e.g. coursework, professional development activities, podcasts, independent reading, etc.).
  • Ability to communicate with impact and confidence, effectively conveying ideas and influencing outcomes, both orally and in writing.
Preferred
  • Familiarity or exposure to cloud computing platforms and ecosystems, e.g., Azure, AWS, and containerization, e.g., Docker.
  • Understanding of basic microeconomic principles.
  • Knowledge of wholesale electricity markets.
Our Values @ Ascend
  • Integrity: We act with honesty and uphold the highest ethical standards, doing the right thing even when itโ€™s difficult.
  • Purpose Driven: We are united by a shared purpose โ€“ to deliver meaningful impact for our customers, our industry, and the energy transition to a lowโ€‘carbon future.
  • Belonging: We foster a respectful, inclusive environment where everyone is valued, diverse perspectives are embraced, and equitable opportunities are provided for all.
  • Innovation: We anticipate and address new challenges, embracing change and continuous improvement.
  • One Team Mindset: We collaborate across teams and functions, supporting one another and prioritizing shared success over individual wins.
Your Value @ Ascend

We offer competitive compensation โ€” calibrated to your experience and structured to grow with you โ€” along with a comprehensive benefits package.

  • Medical, dental, and vision coverage.
  • Life and disability insurance.
  • Parental leave for growing families.
  • FSA, HSA, and dependent care accounts.
  • 401(k) with 3% nonโ€‘elective contribution.
  • Flexible PTO to take time when you need it.

We offer a competitive salary range of $100,000โ€“$160,000 USD annually. Compensation is flexible and will be tailored to your experience and background. Weโ€™re proud to offer pay that is often above industry average. But the perks donโ€™t stop there โ€” weโ€™re committed to creating a workplace where people can do meaningful work, grow their careers, and still have a life outside the office. Youโ€™ll enjoy flexible work hours, a collaborative environment, and real opportunities for advancement.

Collaboration is in our DNA, and we thrive on the energy of working together โ€” the spontaneous ideas, faceโ€‘toโ€‘face teamwork, and culture you can only build in a room.

But we also value the focus and freedom that remote flexibility brings. Thatโ€™s why our Boulder, CO office runs on a hybrid schedule (3 days inโ€‘office, 2 days remote). We prefer candidates who can work from Boulder HQ, though weโ€™re open to strong remote candidates as well.

Need accommodations?

Contact us at recruiting@ascendanalytics.com.

Ascend Analytics is an Equal Employment Opportunity employer. We celebrate diversity and are committed to an inclusive environment for all employees regardless of race, religion, color, national origin, sex, sexual orientation, gender identity or expression, age, veteran status, disability, or genetic information.

Note: We regret that we are currently unable to offer visa sponsorship.

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