Hands-On Technical Leadership: Adopt a 'lead by example' approach by actively coding and troubleshooting, as well as creating documentation and technical diagrams.
Teaching & Mentorship: You will serve as a mentor and guide to engineers across the organization, teaching and mentoring them to grow their skills.
Code Review: You will do code review and mentor others within the organization regarding best practices in ML Engineering.
Operational Excellence: Guarantee the delivery of superior infrastructure and software that not only meets but exceeds customer expectations, while aligning with the strategic business timelines.
Collaborative Strategy: Forge strong partnerships with product managers, data scientists, and company leadership to promote a culture of open communication and integrated team dynamics.
Guide Innovation: Champion the adoption of cutting-edge technologies, methodologies, and practices to enhance problem-solving efficiency and effectiveness across the AI/ML organization.

At least 7 years of experience in machine learning engineering, software engineering, data science, or similar technical role.
A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is preferred and may substitute for some years of experience.
Demonstrated experience designing and deploying cloud infrastructure (AWS preferred) to support machine learning, and machine learning models, with considerations for scale, reliability and security.
Deep understanding of the machine learning lifecycle and related infrastructure needs
feature stores, a/b testing, model registration, drift detection, automated retraining, etc.
Strong technical expertise.
Software engineering principles, including parallel and distributed computing, version control, reproducibility, and continuous integration.
Machine learning techniques and algorithms, with emphasis on their impact to infrastructure implementation.
Infrastructure as Code (IaC), especially Terraform.
REST API design and implementation.
Object oriented and functional programming in Python.
Multimodal data processing (e.g., combining text, image, and 3D data).
Experience with AWS microservices including SageMaker, Service Catalog, IAM, Lambda, Cloudwatch, ECR, EKS, and Kinesis.
Containerization technologies (Docker and Kubernetes).
Demonstrated ability to interact and communicate effectively at all levels of the organization...

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

Principal ML Engineer, ML Platform Engineering

Key skills