Senior Software Engineer, Data Science

Enphase Energy is a global energy technology company and a leading provider of solar, battery, and electric vehicle charging products. Founded in 2006, our innovative microinverter technology revolutionized solar power, making it a safer, more reliable, and scalable energy source. Today, the Enphase Energy System enables users to make, use, save, and sell their own power. Enphase is also of the most successful and innovative clean energy companies in the world, with more than 80 million products shipped across 160 countries.

Join our dynamic teams designing and developing next-gen energy technologies and help drive a sustainable future!

This role at Enphase requires working

3 days a week

, with plans to transition back to a full 5 day in office schedule over time.

About the role

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For our Customer Experience team, we seek Hands-On Senior Data Scientist who can work on designing & implementing high quality scalable optimization-based applications and platforms, while providing technical leadership and mentoring to a small team of talented developers in agile environment. Your ability to take ownership of architecture, design, and implementation of maintainable, high-quality, and high-performing Machine Learning systems and Optimization applications is essential for success in this role.Provide hands-on technical expertise to design, engineer, deploy, and deliver highly scalable optimization-based applications. Drive improvements in technical architecture, standards, and processes. Drive engineering excellence while managing/mentoring talented team of developers in agile environment. Work closely with product management and other stakeholders for system design and delivery.As an Optimization and AI/ML Expert, you will be responsible for developing and implementing advanced machine learning models, optimization algorithms, and analytical tools. You will leverage your expertise to solve complex business problems by using data-driven approaches and predictive modelling techniques. The ideal candidate will have a strong background in AI/ML, optimization, and applied mathematics, with a passion for designing efficient solutions to tackle large-scale, real-world challenges.

What you will do

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• Optimization & AI/ML Model Development: Design, develop, and implement AI/ML models and optimization algorithms to address business challenges and improve decision-making.
• Data Analysis & Feature Engineering: Work with large datasets to preprocess, analyze, and engineer features for model development. Ensure data quality and integrity.
• Performance Improvement: Apply optimization techniques (e.g., linear programming, constraint programming, heuristic algorithms) to optimize business operations, resource allocation, and other key processes.
• Collaboration & Problem-Solving: Collaborate with cross-functional teams, including data engineers, business analysts, and domain experts, to identify problems and translate them into solvable AI/ML models.
• Research & Innovation: Stay updated on the latest trends in optimization, machine learning, and AI research. Evaluate and apply emerging technologies and techniques to enhance system performance.
• Model Evaluation & Tuning: Conduct model evaluation using appropriate metrics, tune hyperparameters, and ensure that models perform optimally in production environments.
• Documentation & Reporting: Document the methodology, processes, and results of AI/ML projects. Communicate findings to stakeholders and contribute to technical reports or presentations.
• Deployment & Monitoring: Work with engineering teams to deploy AI/ML models into production. Monitor model performance and provide support for scalability and robustness.

Who you are and what you bring

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• Experience: 5 years + of experience in AI/ML, optimization, and data science with a proven track record of applying these skills to real-world business challenges.
• Strong Analytical Skills: Expertise in quantitative analysis, applied mathematics, and optimization algorithms (e.g., integer programming, dynamic programming, convex optimization).
• Proficiency in Programming: Strong programming skills in Python, R, and/or MATLAB. Experience with libraries like TensorFlow, PyTorch, Scikit-learn, or similar.
• Machine Learning Expertise: Deep understanding of supervised and unsupervised learning, reinforcement learning, and model validation techniques. Familiarity with deep learning and neural networks is a plus.
• Optimization Knowledge: Solid knowledge of optimization techniques for solving complex resource allocation, scheduling, or routing problems.
• Data Handling & Analysis: Experience with big data technologies (Hadoop, Spark), data preprocessing, and feature engineering techniques.
• Problem-Solving Mindset: Ability to translate business problems into mathematical models and find creative solutions.
• Communication Skills: Strong written and verbal communication skills to effectively convey technical concepts to non-technical stakeholders.
• Advanced Degree: A Master's or Ph.D. in Computer Science, Mathematics, Engineering, Operations Research, or a related field is highly desirable.
• Experience in the deployment and scaling of AI/ML models in production environments.
• Knowledge of cloud platforms such as AWS, Google Cloud, or Azure.
• Familiarity with optimization software/tools like Gurobi, CPLEX, or other commercial solvers.
• Experience with reinforcement learning and optimization in dynamic or uncertain environments.

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