We are seeking an experienced Machine Learning Engineer to join the Machine Learning Operations team in Client's R&D AI Center of Excellence. In this role, you will build and operate the infrastructure that turns Data Scientists' models into production systems - from scalable training and inference pipelines to optimized on-device deployment on edge hardware. The Machine Learning Operations team supports all projects in the Center of Excellence, including Client's inVue Dx's computer vision and microscopy-based diagnostics, and you will contribute to high impact problems.
Job Description:
Partner with Data Scientists to productionize machine learning and computer vision models, and implement scalable, efficient training and inference pipelines
Optimize models for performance and scalability, including GPU/CUDA-level tuning and edge/embedded inference optimization (e.g., TensorRT, DLA)
Work with software engineers and Data Scientists to integrate ML models into production systems on the cloud and at the edge
Collaborate with Data Scientists to identify and analyze data requirements
Develop and implement data preprocessing and feature engineering pipelines
Build and maintain infrastructure-as-code for ML platforms and deployments
Stay up to date with the latest developments in machine learning, computer vision, and MLOps
Required Skillsets:
Previous experience in machine learning as evidenced by delivering solutions into production
Excellent software engineering skills including a test-driven mindset
Strong programming skills in Python and Spark
Experience with distributed computing frameworks such as Ray, and ML frameworks such as PyTorch and modern foundation/vision models
Experience with ML tech stacks, including Databricks (including Databricks Asset Bundles), MLflow, Amazon AWS (EC2, S3, Lambda), containerization technologies such as Docker, and infrastructure-as-code tools including Terraform and CloudFormation
Experience optimizing and deploying models for GPU or edge inference (CUDA, TensorRT); familiarity with NVIDIA edge platforms (Jetson Orin/Thor) and tooling (Nsight, DeepStream SDK) a plus
Familiarity with computer vision and/or microscopy/scientific imaging data a plus
Experience creating and deploying applications to AWS Lambda
High level of comfort with Linux
Experience with SQL
Strong problem-solving and analytical skills
Excellent communication and collaboration skills.
