AI/ML Full Stack Engineer

AI/ML Full Stack Engineer

Houston, TX

Full time

• AI/ML Integration: Collaborate with data scientists to integrate machine learning models (e.g., using TensorFlow, PyTorch, or scikit-learn) for applications such as energy demand forecasting, predictive maintenance, or carbon emission optimization.
• Back-End Development: Develop and optimize server-side logic, APIs, and database interactions using Python (Flask, FastAPI, or Django) or Node.js to support energy data processing.
• App Development: Build and maintain responsive user interfaces for internal tools and dashboards using modern JavaScript frameworks (e.g., React, Vue.js) and CSS frameworks like Tailwind CSS.
• Generative AI Development: Design and implement generative AI solutions, including LLM-based applications (e.g., using models like GPT or BERT), to create automated reports, simulate energy scenarios, or enhance decision-support tools for operational teams.
• Data Pipeline Support: Assist in building and maintaining data pipelines for processing real-time and historical energy data to support AI-driven applications.
• API Development: Design and implement RESTful APIs to connect front-end interfaces with AI/ML back-end services and energy data systems.
• Testing and Debugging: Write unit and integration tests to ensure code quality and debug issues across the full stack.
• Collaboration: Work with energy analysts, engineers, and product managers to deliver solutions that align with Calpine s operational and sustainability goals.
• Continuous Learning: Stay updated on AI/ML advancements, including generative AI and LLMs, full-stack development trends, and energy industry innovations to contribute innovative ideas.

• Position typically requires 10 years of IT experience, with 5 years of experience focused in software development, with hands-on exposure to full-stack development and experience with AI/ML projects (professional work, internships, personal projects, or coursework acceptable).

• Candidates should have experience or demonstrable familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn, with a focus on developing, fine-tuning, or deploying machine learning models for practical applications.
• Exposure to building or integrating AI-driven solutions, such as predictive analytics, anomaly detection, or optimization algorithms, is highly valued.
• Experience with generative AI platforms and large language model (LLM)-based applications, such as chatbots, automated content generation, or decision-support systems, is a significant plus.
• Candidates should demonstrate an ability to apply AI/ML techniques to solve business problems, ideally in domains like energy, operations, or data-driven decision-making.

• Bachelor s degree in computer science, Engineering, Data Science, or a related field (or equivalent experience).

• Proficiency in Python (Node.js, React, or similar frameworks).
• Familiarity with AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) and generative AI platforms or LLMs (e.g., GPT, BERT, or similar).
• Experience with databases (e.g., PostgreSQL, MongoDB) and REST API development.
• Basic understanding of cloud platforms (e.g., AWS, Google Cloud Platform, Azure) is a plus.
• Knowledge of version control systems (e.g., Git).