ML Engineer

About Us:

We are a forward-thinking company at the intersection of technology and clean energy. Our mission is to transform the way renewable energy is managed and utilized through cutting-edge data analytics and machine learning. By leveraging the power of AI, we help optimize energy systems, reduce inefficiencies, and accelerate the transition to a more sustainable future.

The Role:

As a Machine Learning Engineer, you’ll play a critical role in developing intelligent systems that analyze vast amounts of energy data. You’ll work closely with data scientists, software engineers, and domain experts to design and deploy machine learning models that can forecast energy production, predict demand, and optimize energy storage. This is a unique opportunity to apply your ML expertise to a field that’s directly impacting the planet.

What You'll Be Doing:

• Developing and deploying ML models to predict energy output from renewable sources like solar, wind, and hydropower.
• Designing algorithms that optimize energy storage and distribution, balancing supply and demand in real time.
• Working with big data sets from energy sensors, weather forecasts, and market conditions, transforming raw data into valuable insights.
• Collaborating with data scientists and engineers to automate machine learning pipelines for continuous model improvement and scalability.
• Identifying and solving unique challenges in renewable energy prediction, using tools like Python, TensorFlow, PyTorch, and Scikit-learn.
• Integrating models into production with a focus on efficiency and scalability, using technologies such as AWS, Docker, and Kubernetes.
• Continuously exploring new data sources (like satellite imagery and IoT devices) to improve model accuracy and performance.

Technologies You’ll Use:

• Python, TensorFlow, PyTorch, Scikit-learn for building and training ML models.
• AWS, GCP, or Azure for cloud-based deployment and scaling.
• SQL and NoSQL databases for handling large datasets.
• Docker, Kubernetes for containerization and orchestration of applications.
• Git for version control and collaborative development.

What We’re Looking For:

• Experience in building and deploying machine learning models, particularly in time-series forecasting, optimization problems, or related fields.
• Strong knowledge of Python and common ML frameworks (e.g., TensorFlow, PyTorch).
• Experience working with large datasets, ideally from IoT or sensor data.
• Understanding of cloud infrastructure (AWS, GCP, etc.) and experience deploying ML models in production environments.
• Passion for renewable energy and a desire to work on projects that have a tangible impact on sustainability.
• Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.

Why Join Us?

• Make a real-world impact by applying your skills to a critical global challenge.
• Work with a dynamic and passionate team committed to innovation and sustainability.
• Flexible working arrangements, including remote options and a healthy work-life balance.
• Opportunities for professional growth, learning, and taking ownership of exciting projects.