Platform Engineer – AI/ML Infrastructure
DeepgramFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Key technologies and capabilities for this role
Common questions about this position
The role requires 5+ years of experience in software engineering with a focus on ML infrastructure, cloud platforms, or MLOps.
Strong programming skills in Python are required, along with experience in building distributed systems and REST/gRPC APIs.
Candidates need deep knowledge of cloud-native services and infrastructure-as-code like AWS CDK, Terraform, CloudFormation, hands-on experience with model deployment platforms such as AWS SageMaker, Vertex AI, or Kubernetes-based serving stacks, and proficiency in ML lifecycle tools like MLflow, Weights & Biases, BentoML, plus containerization with Docker.
A Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field is required, or equivalent practical experience.
This information is not specified in the job description.
Wearable fitness tracker with personalized insights
WHOOP offers a fitness membership that focuses on improving personal health and performance through a wearable device called the WHOOP Strap 3.0. This device continuously collects physiological data, including heart rate, sleep patterns, and recovery levels, to provide users with personalized recommendations on their daily activity, sleep needs, and readiness for performance. Unlike many competitors, WHOOP operates on a subscription model, where users pay a fee to access the membership, which includes the device and continuous insights through the WHOOP app. This model not only provides a steady revenue stream but also fosters a strong community among users, encouraging engagement through teams, challenges, and social features. The goal of WHOOP is to help users optimize their health and performance while minimizing injury risk.