Job Description

Senior Machine Learning Operations Engineer

Must have:

• 5+ years of professional experience in implementing MLOps framework to scale up ML in production.
• Hands-on experience with Kubernetes, Kubeflow, MLflow, Sagemaker, and other ML model experiment management tools including training, inference, and evaluation.
• Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)
• Proficiency with ML model training frameworks (PyTorch, Pytorch Lightning, Tensorflow, etc.).
• Experience with GPU computing to do data and model training parallelism.
• Solid software engineering skills in developing systems for production.
• Strong expertise in Python.
• Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent.
• Experience working with cloud data processing technologies (S3, ECR, Lambda, AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.).
• Having Geospatial / Remote sensing experience is a plus.