Time Series Researcher - Remote Opportunity at Applied Computing

About the Role

We are seeking a skilled Time Series Researcher to join Applied Computing in a remote capacity. As a Time Series Researcher, you will play a pivotal role in developing Orbital, our innovative foundation model designed for energy operations. This position focuses on creating and deploying time-series models that operate effectively under real-world constraints, ensuring that our clients can harness their operational data efficiently. Your work will directly contribute to our mission of achieving sustainable abundance for a growing planet.

What You'll Own

• Design and implement foundational time-series models that support forecasting, classification, and optimization tasks.
• Integrate physics-informed structures into learning systems to enhance model performance.
• Develop uncertainty-aware models that quantify confidence under various operational conditions.
• Containerize and deploy models using Docker on AWS/Azure, ensuring robust production workflows.
• Establish rigorous benchmarking and validation protocols to ensure model reliability and performance.

Requirements

• PhD in Computer Science, Statistics, Applied Mathematics, Physics, or a related field.
• First-author publications in time-series modeling, forecasting, or physics-informed machine learning.
• 3+ years of hands-on research experience in time-series or sequence modeling.
• Strong foundation in deep learning and probabilistic modeling.
• Expert Python skills with experience in production-grade PyTorch code.
• Experience deploying ML models into real systems.

Nice to Have

• Familiarity with reinforcement learning techniques.
• Experience with CI/CD pipelines for machine learning.
• Knowledge of classical statistical models.

What We Offer

• Competitive salary in the range of $120,000 to $150,000.
• Remote or hybrid work options with an office in Fitzrovia.
• Attractive benefits package including health insurance and professional development opportunities.
• Opportunity to work on cutting-edge AI technologies in the energy sector.
• Collaborative and innovative work environment focused on real-world impact.