Machine Learning Operations and Data Engineer

Machine Learning Operations and Data EngineerThe CompanyEmancro’s mission is to build general-purpose hospital logistics robots that perform a wide variety of tasks such as organizing and distributing medication and medical supplies within hospitals, and many more tasks in the future. In this way, robots are freeing up medical staff’s time and enable better and more resilient patient care.We are an ambitious and rapidly growing team pushing the boundaries of what is possible in robotics, leveraging recent, cutting-edge breakthroughs in machine learning-enabled, data-driven robotics.

The RoleStart date: As soon as possible, no later than June 1st 2024Location: Berkeley, CA, in person

Work ComponentsDesign, develop, and maintain scalable data pipelines and ETL processes to extract, transform, and load data at large scale (in the order of 100sTB)Setting up and maintaining cloud-database (e.g. DynamoDB, Postgres etc.)Manage containerized environments (e.g., Docker, Kubernetes) for running machine learning workloads.Setting up and Maintaining Cloud multi-GPU training infrastructure (GCP, AWS, Azure) with Pytorch and JaxSetting up and Maintaining MLOps frameworks, e.g. ClearML, ZenML etc.Implement CI/CD pipelines and automation tools to streamline the model development and deployment process.Deploying ML Models on the cloud for low-latency production/serving

Key QualificationsExpert knowledge of using and configuring GCP (Vertex), AWS, Azure Python: 5+ years of experienceMachine Learning libraries: Pytorch, JaxDevelopment tools: Bash, GitData Science frameworks: DatabricksAgile Software developmentCloud Management: Slurm, KubernetesData Logging: Weights and BiasesOrchestration, Autoscaling: Ray, ClearnML, WandB etc.

Optional QualificationsExperience training LLMs and VLMsML for Robotics, Computer Vision etc.Developing Browser Apps/Dashboards, both frontend and backend Javascript, React, etc. Emancro is committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.