Machine Learning Engineer - Power Systems

3 days ago

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Sea Change Advisors

Talent Advisory and Recruiting for Venture Capital and Private Equity

Venture Capital • Consulting • Talent Advisory • Recruiting • Climate Tech

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Description

• Design and lead the implementation of robust and scalable data science and machine learning architecture integrated into the product platform. • Working with the R&D and Data Science teams, deploy prototype models to production. • Re-train and re-deploy models based on quality parameters collected in continuous monitoring. • Define and monitor quality parameters for ML models in production. • Work closely with data science teams to take newly developed models into production. • Optimize the performance, scalability, and reliability of ML Models and generative AI systems. • Design, implement, and evaluate large-scale ML models and generative AI systems in the energy domain and applications. • Design and implement ML toolchains and data platforms to scale ML solutions in production. • Collaborate with other machine learning engineers, data scientists, and domain experts to understand the requirements and challenges of natural language processing and generation tasks. • Define best practices for data engineering, feature engineering, and model deployment.

Requirements

• Master's degree or PhD in Electrical, computer science, power systems, machine learning, natural language processing, or a related field. • Strong knowledge in mathematical modeling, RNNs, CNNs, Transformers, LSTMs, transfer learning, reinforcement learning, imitation learning, GANs, and time-series analysis and modeling of dynamic systems. • Prior experience in operationalizing machine learning workflows. • Hands-on experience with AWS cloud technologies (SageMaker, Apache Airflow, Kubeflow, ECS/EKS). • Prior experience in the electricity & energy domain is preferred. • Strong experience in developing and deploying large-scale ML Models and generative AI systems using frameworks such as numpy, scipy, pandas, scikit-learn, TensorFlow, PyTorch, Hugging Face, or OpenAI). • Proficient in Python and other programming languages for data analysis and machine learning. • Excellent problem-solving, analytical, and communication skills. • Passionate about natural language processing, generative AI, and creating impactful solutions.

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