, Software Engineering/Machine Learning

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About Aspen Power

Aspen Power is a distributed energy platform with the dual mission of accelerating and democratizing decarbonization. We partner with businesses, communities, and others in the industry to develop, construct, and operate renewable energy assets. Our experienced team is passionate about solving our clients’ energy challenges to deliver a sustainable future throughout the U.S. For more information, please visit aspenpower.com.

Position Overview:

Reporting to the Software Engineering team, the Software Engineering Data Science and Machine Learning will work closely with our dedicated team to support the management and optimization of our data pipelines, contributing to the company's mission of sustainable energy solutions. This offers a unique opportunity to gain hands-on experience in the exciting and rapidly growing field of solar energy. The ideal candidate will demonstrate an entrepreneurial passion for renewable energy development and a desire to work with clients to transform the way they procure energy.

This is a 10-week program (approximately June 9 – August 15, 2025), approximately 25–30 hours/week with the opportunity to transition to full-time employment upon successful completion.

Responsibilities:

Full-Stack Application Development: Collaborate with the team to design, develop, and maintain our core application that supports various solar operations.

Data Science & Machine Learning: Assist in updating our current data pipelines and helping the company gain more insight into the data using ML techniques.

Internal API Maintenance: Maintain and develop new endpoints connecting other services/data sources to our tools.

Collaboration and Communication: Work collaboratively with cross-functional teams, providing insights and updates on pipelines, and ensure smooth implementations of stakeholder needs.

Qualifications:

Must be passionate about the renewable energy business, hardworking and thrive in the fast pace of a rapidly growing company. In addition, the candidate must possess:

Applicants from relevant academic backgrounds (Computer Science, Data Science, Machine Learning, Software Engineering, or a related field) or with equivalent practical experience are encouraged to apply.

Proficiency in at least one programming (e.g., Python, C#, or JavaScript).

Experience (or coursework) with full-stack web development frameworks (e.g., Svelte, React, Node.js, etc.).

Familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, or PyTorch) and basic model deployment practices.

Excellent analytical, problem-solving, and teamwork skills.

Personal Characteristics:

Collaborative and engaging team member who partners well with others

Strong team and demonstrated client management skills

Results-driven, with a strong work ethic and commitment to excellence

Executive presence, outgoing with strong communication and presentation skills

Builds trust by demonstrating high ethical standards and personal integrity

Ability to adapt and learn quickly

Analytical problem solver who views obstacles as challenges

Self-motivated, self-starter who can work independently when necessary

Location: NYC - remote/hybrid

At Aspen Power, our work model includes three ways of working: virtual, in-person, and hybrid (a hybrid of in-person and virtual). On site .

Compensation Range: $25 per hour (undergraduate student or degree) - $45 per hour (graduate student or degree)

Learn more about our generous employee benefits and perks by visiting aspenpower.com

Equal Employment Opportunity

We are committed to equal-employment principles and are dedicated to and the strength it brings to the workplace. All qualified applicants will receive consideration for employment without regard to , , , , (including , childbirth or medical condition related to or childbirth), or expression, , physical or mental , medical condition, legally protected genetic information, marital status, veteran status, military status, or any other protected category or class that may be applicable.

NOTE: Due to the large volume of applicants, only candidates under serious consideration will be contacted.