Join Remobi as a Data Scientist to build and deploy reinforcement learning models that optimize real-time control of energy grid systems. This role focuses on developing scalable, responsible AI solutions that reduce emissions, support compliance, and improve operational efficiency.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Data Scientist – Grid Optimization & AI Compliance
About Remobi:
We are Remobi – we empower businesses to scale, innovate, and achieve their goals through high-quality technical solutions delivered by high-performing, high-quality, REMOTE nearshore technology teams. Join our Remobi community to gain access to meaningful, innovative freelance projects and play a key role in shaping how companies operate!
Position Overview:
Location: Fully Remote
Role Type: Freelance/B2B/Contract
Duration: Initial 12 Months
Position Summary:
We’re hiring a Data Scientist to build and deploy reinforcement learning (RL) models that optimize real-time control of energy grid systems. This role focuses on developing scalable, responsible AI solutions that reduce emissions, support compliance, and improve operational efficiency. You’ll work with cutting-edge tools like Grid2Op, L2RPN, and ICTE, integrating your work into cloud-native environments with Python and AWS.
This position suits someone passionate about sustainability, operational AI, and solving complex, real-world challenges.
Responsibilities:
- Design, train, and deploy RL models to optimize real-time grid operations.
- Use open-source grid simulation platforms (Grid2Op, L2RPN, ICTE) to develop and validate models.
- Ensure models comply with regulatory and sustainability standards for AI systems.
- Deploy and scale models using AWS services such as SageMaker, Lambda, and S3.
- Collaborate with engineers, compliance teams, and energy operations specialists.
- Translate technical insights into clear communications for varied stakeholders.
Qualifications:
- Proven experience with Reinforcement Learning, ideally applied to physical or control systems.
- Advanced Python programming and model deployment skills.
- Hands-on use of tools like Grid2Op, L2RPN, ICTE, or similar simulation environments.
- Experience deploying models on AWS (SageMaker, Lambda, S3).
- Familiarity with smart grid technologies or energy systems is a plus.
- Understanding of AI governance, sustainability metrics, or regulatory frameworks.
- Degree in Computer Science, Engineering, Applied Mathematics, or related technical discipline.
If you’re interested in this role or know someone who might be a great fit, feel free to apply or get in touch!
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