Machine Learning Engineer; SmartBidder
Listed on 2026-07-06
-
IT/Tech
Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software), Data Analyst
Overview
Machine Learning Engineer (Smart Bidder), Boulder, CO (Hybrid or Remote). This position supports Ascend Analytics’ Smart Bidder 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 data science skills will support mission-critical decision analytics for renewable and battery storage power providers around the globe.
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.
- Collaborate with 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 technical and nontechnical stakeholders.
- Collaborate within the software team and with the analyst team.
- Contribute to technical design reviews, implementation strategies, operational system support, and sprint planning within an agile scrum process.
- 2+ years of 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, Power Systems, or related fields.
- Experience performing independent research, including reading academic papers, developing and testing hypotheses, and analyzing experimental results.
- Demonstrated software coding experience in Python.
- Familiarity with data processing in Python (Pandas, Num Py, Sym Py, Scikit-Learn) and machine learning development in PyTorch (or similar).
- Strong interpersonal skills, a collaborative mindset, and a results-oriented work ethic.
- Demonstrated interest in the energy sector (e.g., coursework, professional development activities, podcasts, independent reading).
- Ability to communicate with impact and confidence, effectively conveying ideas and influencing outcomes, both orally and in writing.
- Familiarity with cloud computing platforms (Azure, AWS) and containerization (Docker).
- Understanding of basic microeconomic principles.
- Knowledge of wholesale electricity markets.
- Integrity: act with honesty and uphold high ethical standards.
- Purpose Driven: deliver meaningful impact for customers, industry, and the energy transition.
- Belonging: foster an inclusive environment with diverse perspectives.
- Innovation: embrace change and continuous improvement.
- One Team Mindset: collaborate across teams and prioritize shared success.
- Competitive compensation, structured to grow with your experience, 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.
We offer a competitive salary range of $100,000–$160,000 USD annually. Compensation is tailored to experience. The Boulder, CO office operates on a hybrid schedule (3 days in-office, 2 days remote). We prefer candidates who can work from Boulder HQ, though strong remote candidates will be considered.
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:
visa sponsorship is not available at this time.
(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).