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Jr Machine Learning Engineer Jobs in Colorado (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Aurora, 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 ...

Bespoke Labs

Machine Learning Engineer

Denver, 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 ...

Bespoke Labs

Machine Learning Engineer

Greeley, 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 ...

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Jr Machine Learning Engineer information

What does a Jr Machine Learning Engineer do?

A Jr Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the guidance of more senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, model training, testing, and helping to integrate models into production systems. They also work on debugging issues, documenting code, and staying up-to-date with the latest industry trends and tools. Junior engineers typically collaborate closely with cross-functional teams to deliver AI-powered solutions.

What are the key skills and qualifications needed to thrive as a Jr Machine Learning Engineer?

To thrive as a Jr Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, as well as experience with data preprocessing and version control systems, is typically required. Strong analytical thinking, problem-solving skills, and the ability to collaborate effectively help you stand out in this role. These competencies are crucial for developing, optimizing, and deploying machine learning models that address real-world business challenges.

What are some common challenges faced by Jr Machine Learning Engineers in their first year on the job?

Jr Machine Learning Engineers often encounter challenges such as understanding complex codebases, managing large datasets, and bridging the gap between academic concepts and real-world applications. Collaboration with data scientists, software engineers, and product teams can also be a learning curve, as effective communication is crucial for project success. Additionally, balancing tasks like model development, testing, and deployment within fast-paced agile environments can be demanding, but these experiences provide valuable opportunities for skill growth and professional development.

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

AspectJr Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often with advanced certifications
Work EnvironmentFocus on developing and deploying ML models, coding, and data preprocessingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, consulting, research institutions

The Jr Machine Learning Engineer primarily develops and deploys ML models, requiring coding skills and familiarity with ML frameworks. Data Scientists analyze data, build statistical models, and interpret insights. While both roles work with data, the Jr Machine Learning Engineer is more focused on implementation, whereas Data Scientists focus on analysis and strategy.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, industry, and experience. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What cities in Colorado are hiring for Jr Machine Learning Engineer jobs?

Cities in Colorado with the most Jr Machine Learning Engineer job openings:

Infographic showing various Jr Machine Learning Engineer job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer (SmartBidder)

Boulder, CO • On-site

Silversmith Capital Partners
Investment Clubs and Venture Capital Companies • 11 - 50 employees
Learn more about Silversmith Capital Partnersexternal

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 11 days ago

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 Analytics’ 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 clean‑tech power revolution. Your strong data science skills will support mission‑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, cloud‑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 high‑growth, private equity–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.

  • High‑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 work‑life balance.
Key Responsibilities
  • Prototype and experiment with novel machine learning models and mathematical/statistical algorithms for short‑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, Scikit‑Learn) and machine learning development in Pytorch (or similar).
  • Strong interpersonal skills, a collaborative team‑first mindset and results‑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 it’s difficult.
  • Purpose Driven: We are united by a shared purpose – to deliver meaningful impact for our customers, our industry, and the energy transition to a low‑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 — calibrated to your experience and structured to grow with you — 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% non‑elective contribution.
  • Flexible PTO to take time when you need it.

We offer a competitive salary range of $100,000–$160,000 USD annually. Compensation is flexible and will be tailored to your experience and background. We’re proud to offer pay that is often above industry average. But the perks don’t stop there — we’re committed to creating a workplace where people can do meaningful work, grow their careers, and still have a life outside the office. You’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 — the spontaneous ideas, face‑to‑face teamwork, and culture you can only build in a room.

But we also value the focus and freedom that remote flexibility brings. That’s why our Boulder, CO office runs on a hybrid schedule (3 days in‑office, 2 days remote). We prefer candidates who can work from Boulder HQ, though we’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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