Lead MLOps Engineer - Kubernetes

We are Series C funded Startup building Analytical products & solutions.

Position : Lead MLOps Engineer

Work Location : Bangalore, India

Experience : 8 to 12 yrs

Education : Bachelors / Masters / PhD Degree in Computer Science/Machine Learning

Requirements :

- Atleast 3+ years of 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.).

Roles and Responsibilities :

- Architect, build and integrate end-to-end life cycles of large-scale, distributed machine learning systems i.e. ML Ops using cutting-edge tools/frameworks.

- Develop tools and services for explainability of ML solutions.

- Implement distributed cloud GPU training approaches for deep learning models.

- Build software/tools that improve the rate of experimentation for the research team and extract insights from it.

- Identify and evaluate new patterns and technologies to improve the performance, maintainability, and elegance of our machine learning systems.