Machine Learning Engineer

Location: This is a hybrid role. We prefer Connecticut-based candidates who can work from our office in New Haven several days per week.

About Us

At Noteworthy AI, our mission is to improve the reliability, resiliency, and safety of the electric grid. Our vehicle-mounted cameras and AI help utilities and other grid operators increase their situational awareness of their assets while reducing costs. Our platform autonomously geolocates, photographs, and analyzes grid infrastructure as vehicles drive during routine operations, enabling more proactive grid management. 

We’ve gained significant market traction, validation, and support from customers like Florida Power & Light, FirstEnergy Corp, and Alabama Power, investors like Earthshot Ventures and Techstars, and partners like Nvidia - so we are looking for great people to come and join our growing team! 🚀

About You

You’re excited to roll up your sleeves at a fast-growing startup that is playing a critical role in helping to keep the electric grid energized and resilient.

You are seeking the opportunity to truly impact the company's success while building and delivering solutions that help not only our customers, but all users of the electric grid.

Bonus points if you can… 

• Adapt, solve problems, and quickly learn new skills
• Identify trade-offs between various technical challenges and business requirements
• Wear multiple hats and collaborate with a growing, diverse team
• Present and communicate technical topics to non-technical audiences

Responsibilities

• Lead the design and implementation of advanced machine learning (ML) models and techniques applied to critical vision-based infrastructure inspection. Projects may include:
  • Novel vision-based ML models: classification, object detection, segmentation, depth estimation, keypoint detection, graph estimation, tracking, and more
  • Advanced ML techniques to improve existing models: transfer learning, domain adaptation, synthetic data generation, active learning, continual learning, few-shot learning
  • Novel features on advanced ML pipelines and data engines: anomaly detection, semi-automated labeling, multi-task learning and parameter sharing
• Contribute to improving and maintaining ML-related infrastructure, data pipelines, internal documentation, code & data standards and tooling

Qualifications

• Enrolled in Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• Experience and/or strong technical foundations in machine learning, supervised learning, optimization, neural networks (including CNNs, transformers, GNNs, etc.), and applications in computer vision (image classification, object detection, semantic segmentation, keypoint detection, tracking, etc.)
• Strong proficiency and recent hands-on experience in Python, standard data science libraries (numpy, pandas), and one or more ML libraries (PyTorch, Tensorflow, Keras, scikit-learn, Huggingface, Weights & Biases, Tensorboard, etc.)
• Demonstrated ability to take ownership and execute projects in applied research and development related to machine learning and/or computer vision

Preferred Qualifications

• Enrolled in Master’s or Doctorate degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• Published research and/or academic/industry partnerships in machine learning, computer vision, robotics, computer science or a related field. Peer-reviewed research in leading academic conferences and journals is particularly beneficial.
• Experience and/or strong technical foundations in computer vision
• Experience and/or strong technical foundations in advanced ML training techniques (transfer learning, domain adaptation, semi-supervised learning, etc.)
• Knowledge of ML Ops, best practices for production-grade ML model development
• Experience and/or knowledge of data science theory and practice including databases, SQL, designing efficient data pipelines, handling large volumes of data, generating compelling visualizations
• Experience with Amazon Web Service (AWS) products (S3, Redshift, DynamoDB, Lambda, Sagemaker, etc.) or equivalent cloud services (Microsoft Azure, Google Cloud Platform, etc.)

What We Offer

• Competitive salary, equity, and benefits
• Opportunity to make an impact with AI in the increasingly important energy sector
• Professional development and leadership opportunities
• Flexible work hours in a hybrid setting

In alignment with our core beliefs, Noteworthy AI is an equal opportunity employer (EOE) and all qualified applicants will receive consideration for employment without regard to race, color, religion, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

This position is subject to a pre-employment background check.