AI Senior Developer

Calpine-posted about 1 month ago
Full-time • Entry Level
Houston, TX
1,001-5,000 employees
Utilities
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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., 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.
  • 5 years of experience in software development, with hands-on exposure to full-stack development or 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 and/or JavaScript (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, 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.
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