Senior Machine Learning Scientist

RWE - Bellevue, WA

Full-time - Senior

Hybrid - Bellevue, WA

1,001-5,000 employees

Specialty Trade Contractors

About the position

The Senior Machine Learning Scientist will be a pivotal member of the AI Weather Lab team at RWE Supply & Trading Americas, LLC, focusing on innovative applications of AI in the renewable energy sector. This role involves leading research and development efforts to advance machine learning techniques, particularly in diffusion and generative models, to address complex challenges in renewable energy applications. The position requires collaboration with cross-functional teams to integrate AI models into scalable solutions, ensuring they meet specific application requirements.

Responsibilities

• Experiment, design, develop, and implement novel neural network architectures for state-of-the-art diffusion and generative models.
• Collaborate with domain experts to ensure models meet application requirements and constraints.
• Work closely with data scientists, software engineers, and machine learning engineers to integrate models into scalable pipelines.
• Stay updated on advancements in machine learning technologies, cloud services, and software engineering best practices.
• Develop reusable components, libraries, and frameworks for algorithm experimentation and performance assessment.
• Contribute to research advances through conference presentations, publications, and open-source contributions.
• Foster a team culture that welcomes diverse viewpoints and expertise.

Requirements

• 7+ years of relevant industry experience in machine learning research and application.
• Extensive track record of research and publications in machine learning, particularly in diffusion models, generative models, or NLP.
• Deep understanding of neural network fundamentals, including CNNs, RNNs, and attention mechanisms.
• Strong mathematical background with expertise in linear algebra, probability theory, and optimization techniques.
• Proficiency in programming languages such as Python and Julia, with experience in developing large-scale models using machine learning packages like PyTorch, TensorFlow, or Jax.
• Extensive experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
• Proven experience in deploying machine learning models in production using containerization and orchestration tools like Docker and Kubernetes.
• Familiarity with version control systems (e.g., Git), CI/CD pipelines, and infrastructure-as-code tools.
• Strong passion for innovation and keeping up-to-date with the latest AI research.
• Exceptional communication and collaboration skills, with the ability to work effectively in cross-functional teams.
• Ph.D. in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field, or a Master's degree with significant industry experience.

Nice-to-haves

• Domain expertise in meteorology, climate science, or the energy sector.
• Experience with distributed systems, parallel computing, and GPU acceleration.
• Proficiency in database technologies for data storage and retrieval (e.g., PostgreSQL, MongoDB, BigQuery).
• Proficiency in Nvidia GPU frameworks (CUDA, cuDNN, TensorRT, NCCL) and HPC technologies.
• Experience with Google Cloud Platform MLOps tools (e.g., Vertex AI).
• Publication record in AI conferences (e.g., NeurIPS, ICML) and journals.

Benefits

• Dynamic of a start-up in a well-established environment.
• Using cutting-edge technology to solve challenging matters.
• Contribution to the company goals of energy transition.
• Hybrid working model with 3 days in the office to foster collaboration and teamwork.
• Diverse and multicultural team in a highly dynamic and rapidly growing business.