Staff Machine Learning Engineer

Bachelor's degree in a STEM field (or equivalent experience) plus 6-8 years of experience in machine learning engineering, with a track record of owning and delivering complex ML systems in production

Deep expertise in ML and AI technologies, including Gradient Boosting methods, Deep Learning, and/or Generative AI frameworks, with a focus on backend scalability and reusability

Hands-on experience deploying real-time ML products at scale in cloud environments (AWS strongly preferred), including auto-scaling, monitoring, and alerting

Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar

Solid grounding in software engineering fundamentals, data structures, and algorithms

Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines

Proficiency with CI/CD pipelines (e.g., Github actions),test driven development, and infrastructure as code (e.g., Terraform)

Experience profiling and optimizing existing ML model deployments for latency and throughput

Ability to operate independently on new and ambiguous assignments, determine methods and procedures, and communicate effectively across engineering, product, and business audiences

Experience with state-of-the-art modeling techniques including transformers, self-supervised pre-training, large language models (LLMs), or generative AI

Knowledge of containers, container orchestration (Kubernetes), and cloud-native distributed systems

Background in manufacturing, supply chain, or marketplace environments is a plus — but curiosity and drive matter more

The estimated base salary range for new hires into this role is $200,000-$220,000.00 annually + bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.