About this opportunity
Trace Air Quality, Inc lists this Machine Learning Engineer opportunity in northern, Kentucky. Review the employer’s description below for duties, qualifications and application requirements.
Job description
WORK AT TRACE AQ
Machine Learning Engineer
Overview
We are seeking someone who is passionate about building. If our mission to deliver the world’s best air quality solutions resonates with you, this position may be for you. We are looking for an innovative, self-motivated Machine Learning Engineer & Researcher to join our team. Trace AQ is at the forefront of data science and AI advancement as a frontier lab focused on Physics-Based AI that leverages the capabilities of supercomputing for deterministic Newtonian physics amplified by probabilistic models built utilizing neural networks on transformer architecture. This role is ideal for someone who thrives in a fast-paced, high-growth startup environment and is passionate about using data and AI to drive real-world impact.
You will contribute directly to the research, design, and deployment of ML models and scientific frameworks that power Trace's air quality technologies—from predictive algorithms and environmental modeling to technical feasibility research and product experiments. If you are passionate about exploring new ML paradigms, building applied solutions, and helping improve the health of people and the planet, we want to hear from you.
Trace Air Quality is an equal-opportunity employer.
What we're looking for / Responsibilities
Research and prototype ML models for environmental forecasting and more
Ability to perform research and collaborate with the team to produce technical written materials
Design and run scientific experiments to evaluate novel techniques for air quality prediction and exposure risk assessment
Explore and apply the latest developments in generative AI, foundation models, and reinforcement learning where relevant
Work across product, data, and engineering teams to translate ambiguous ideas into concrete research questions and system designs
Write clean, modular, and reproducible code (Python, PyTorch, JAX, etc.) for experimentation and deployment
Publish internal reports and presentations to drive technical clarity and long-term innovation strategy
Stay at the forefront of research in air quality modeling
Qualifications
Proficient in Python & R
Experience building out ML models (specifically neural network/deep learning architectures),
Math/statistics/computing background to support understanding model performance
Familiarity with MLOps tools (e.g. Weights & Biases, MLflow, Ray, Docker)
Education aligned with responsibilities
Comfort working in a startup, lab, or rapid R&D environment
Experience designing and interpreting A/B tests or causal inference techniques
Trace Air Quality Values
The Best & Brightest - Our strength is our people and team. Big imaginations, passionate souls, and tenacious spirits aligned to create, build, and help each other.
Think Big - We aim to tackle difficult problems to leave things better than we found them. We are never afraid to take on a challenge and we’re bold enough to challenge what others think is impossible.
Results Driven - We use world-class science and technology to create incredible value for the communities, businesses, and people we serve.
About Trace Air Quality
Trace Air Quality is on a mission to deliver the world’s best air quality solutions. With a deep understanding that air quality directly impacts every person's quality of life, Trace AQ uses it’s foundation in cutting-edge data science to provide actionable insights to businesses, agencies, and consumers. By transforming complex environmental data into simple, reliable insights and alerts, Trace AQ empowers its users to make informed decisions in the face of rapidly changing air quality conditions. Specializing in the forecasting of smoke, dust, inversions, and other air quality hazards, Trace AQ sets the standard for accurate, timely, and industry-leading air quality intelligence.
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Who can apply
Review the original listing for work authorization, qualifications and employer requirements.