Introduction

Tensor Energy is creating the operating system of our distributed renewable energy future. We are helping companies in the renewable energy industry to connect their assets to the cloud, manage them on their behalf, and monetize the assets on electricity markets.

We are looking for a MLOps and machine learning engineer to drive forward the development of our machine learning cloud infrastructure.

If you...

are passionate about bringing lasting change to our energy system to decarbonize the economy and to prevent catastrophic climate change 🌍 thrive in a fast-moving, multicultural startup environment ⚡ are a problem solver, unafraid to take leadership, who can deliver under conditions of uncertainty 🔥 ... we would love to talk to you.

Please include any links to open-source repos with your work and any relevant published papers/articles in your application.

Responsibilities

• Design, build, and deploy machine learning pipelines on AWS cloud
• Build CI/CD pipelines (Github) for ML
• Set up automatic deployment, monitoring, versioning of ML models
• Set up automatic validation, tuning, and testing of ML models
• Assist in the design and development of ML models for time series forecasting and other applications
• Communication and collaboration with the rest of the data science team and others in the company

Required qualifications

• Experience in designing and implementing MLOps pipelines in AWS
• Knowledge of Python, good knowledge of ML frameworks such as Scikit-learn, Keras, PyTorch, TensorFlow
• Ability to develop and understand machine-learning models, especially for time-series forecasting
• Fluent in English

Good to have

• Understanding of the energy industry or willingness to learn