Data Engineer

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! 🚀

You are 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’re experienced writing Python and enabling machine-learning model development by processing and handling data

You want to grow your career by working with a dynamic research team on cutting-edge applied AI research and development, contributing to novel ML research, and learning key skills for AI and ML engineering

• Process and handle data to enable machine-learning (ML) and AI development tasks (i.e., dataset curation, labeling, training, inference, evaluation) and maintain a traceable, automated ML operations workflow
• Lead analyses and experiments to identify salient data for ML development and characterize the performance of (ML) models.
• Design, build, and improve data pipelines, interfaces, visualizations, and associated code infrastructure
• Maintain databases and data lakes for ML development while ensuring data integrity and security
• Support and interface with internal stakeholders to generate high-quality deliverables for customers
• Contribute to internal documentation, code, and data standards and tooling

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field OR commensurate experience in software development, data science, math, and statistics
• Strong proficiency and recent experience in Python and standard data science libraries (numpy, pandas, scikit-learn, matplotlib, seaborn)
• Demonstrated ability to write efficient and reliable software following best practices in software design, testing, review, and documentation
• Strong technical communication skills
• Ability to collaborate and work effectively on complex software systems in a team setting
• A growth mindset, a willingness to take ownership of your work, and an ability to adapt to the challenges of a fast-paced startup environment

Preferred Qualifications

• Experience designing data pipelines, handling large volumes of data, and generating compelling visualizations
• Experience in SQL, relational databases, and/or related topics (i.e., database design, query optimization, NoSQL, RDSMS, etc.)
• Experience with Amazon Web Service (AWS) products (e.g., S3, Redshift, DynamoDB, Lambda, Sagemaker) or equivalent cloud services (Microsoft Azure, Google Cloud Platform)
• Experience and/or strong technical foundations in computer vision, like cameras and image capture, image encoding and storage, image processing and filtering, 3D vision, feature extraction
• Experience and/or strong technical foundations in machine learning, supervised learning, optimization, neural networks, applications in computer vision (image classification, object detection, semantic segmentation, keypoint detection, tracking, etc.)
• Hands-on experience writing ML training and/or inference code in Python and common libraries (e.g., PyTorch, Tensorflow, Keras, scikit-learn, Huggingface, Weights & Biases, Tensorboard)
• Knowledge of ML operations and best practices for production-grade ML model development

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