Sr. AI Engineer

Overview

As an AI/ML Full Stack Engineer at Calpine Inc., you will contribute to the development of AI-driven tools and applications to optimize energy operations, enhance forecasting, and improve operational efficiency. You will work on both front-end and back-end development, integrating machine learning models, including large language models (LLMs) and generative AI, into Calpine’s energy management systems. This role is ideal for professionals with up to 5 years of experience who are passionate about AI, web development, and solving real-world energy sector challenges.

• AI/ML Integration: Collaborate with data scientists to integrate machine learning models (e.g., Tensor Flow, PyTorch, 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.

• Experience: 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).

• AI/ML
  
  Experience:
  
  Candidates should have experience or demonstrable familiarity with AI/ML frameworks such as Tensor Flow, PyTorch, or scikit-learn, with a focus on developing, fine-tuning, or deploying machine learning models for practical applications.
• AI/ML Platforms: Exposure to building or integrating AI-driven solutions, such as predictive analytics, anomaly detection, or optimization algorithms, is highly valued.
• LLM/Generative AI: 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.
• Problem Solving: Demonstrated 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., Tensor Flow, PyTorch, scikit-learn) and generative AI platforms or LLMs (e.g., GPT, BERT, or similar).
• Experience with databases (e.g., Postgre
  
  SQL, Mongo
  
  DB) and REST API development.
• Basic understanding of cloud platforms (e.g., AWS, GCP, Azure) is a plus.
• Knowledge of version control systems (e.g., Git).

• Strong problem-solving skills and eagerness to learn.
• Ability to work collaboratively in a fast-paced, team-oriented environment.
• Good communication skills to articulate technical concepts to non-technical stakeholders.

• Experience with containerization (e.g., Docker) or CI/CD pipelines.
• Familiarity with front-end styling frameworks like Tailwind CSS.
• Exposure to energy sector data or analytics (e.g., time-series data, forecasting).
• Contributions to open-source projects or personal AI/ML projects, particularly those involving generative AI or LLM-based applications.

• Medical, vision and dental
• Prescription drug coverage
• Calpine’s Retirement Savings Plan (401(K)) matching
• Paid time off and paid parental leave
• Comprehensive health programs, Wellness Program, telemedicine, Employee Assistance Program, FSAs and more
• Life insurance
• Education reimbursement program
• Adoption assistance
• Scholarship and vocational grant programs
• Training and education opportunities
• Bonus eligible