Senior Machine Learning Engineer (Tapestry)

Key Skills

AWS, Azure, Design, Google Cloud Platform (GCP), Machine learning techniques, PyTorch, TensorFlow

Job Description

About the role:

We're looking for a Senior Machine Learning Engineer to join our team. In this role, you will be responsible for developing and deploying state of the art machine learning models to solve complex challenges that face today’s electric grid. You’ll have the opportunity to lead model building and development across diverse ML domains such as time series analysis, planning and reinforcement learning, multi modal information retrieval and reasoning and agentic AI. In this role, you will be responsible for end to end ML model training and deployment, working with and mentoring junior machine learning engineers, helping lead cross-functional collaborations and build the state of the art machine learning models to help power the grid of tomorrow.

How you will make 10x impact:

• Design, train, and deploy machine learning models in production environments.
• Lead the end to end development of ML systems for one or more of planning and reinforcement learning, forecasting and multimodal machine learning
• Actively collaborate with leaders in product, engineering, and data science teams to address key business problems
• Mentor junior engineers and scientists and contribute to the team’s technical growth.
• Stay abreast of the latest advancements in machine learning

What you should have:

• Master’s Degree/Bachelor's Degree in Machine Learning, Computer Science, Statistics or equivalent practical experience.
• 6+ years of professional experience in machine learning model development and engineering.
• Deep expertise in one or more of the following areas: planning and control, reinforcement learning, forecasting, multimodal machine learning and information retrieval
• Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
• Experience with building and deploying ML systems at scale, and a proven ability to perform applied ML research and develop the state of the art
• Proven ability to work on cross-functional projects and deliver results in a fast-paced, collaborative environment

It’d be great if you also had these:

• PhD in Machine Learning, Computer Science, Statistics, or a related field
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Familiarity with MLOps practices and tools.

A strong portfolio of projects demonstrating expertise in multiple ML domains..

The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.