- 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.