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.(ref : hirist.tech)