Requirements:
Required Skills:
- 2 years of minimum working experience as a DevOps engineer.
- 1 year of minimum experience working closely with an ML team.
- Experience in creating, deploying, and maintaining centralized KubeFlow infrastructure on top of one or multiple Kubernetes clusters
- Proficiency in creating CI/CD pipelines for microservice-based architectures using Jenkins
- Proficiency in python. The candidate should be able to write production-grade code in python.
- Proficiency in Git, docker and docker-compose
- Experience with Kubernetes. The candidate should be comfortable with kubectl and helm.
- Experience working with tools in the AWS ecosystem - particularly with Infrastructure as Code (IaC), CloudFormation, IAM, API Gateway, Lambda, Load Balancers, dynamodb, RDS, ECR, ECS and EKS.
Desired Skills:
- AWS certified developer/solution architect
- Experience in workflow orchestration tools like Apache Airflow, Prefect, MetaFlow, Luigi etc.
- Prior experience/familiarity with machine learning frameworks e.g., PyTorch, TensorFlow, ONNX etc.
- Experience/Familiarity with a model serving in ML and working with frameworks like TensorFlow Serving, TorchServe, KFServing, Seldon, BentoML etc.
- Experience working with computer vision technologies is a bonus
Responsibilities:
- Work closely with the ML team to plan, build, maintain, and improve an end-to-end MLOps platform on top of KubeFlow for research, model training, logging and model serving
- Work closely with the ML team, integration team(s) and the cloud administrators to deploy and integrate ML services into a wide range of products
- Build complex container-based workflows that include multiple data and model components for machine learning applications
- Designing and implementing CI/CD pipelines with git, Jenkins, and AWS for ML research-based projects
- Continuously improve latency, concurrency, horizontal scaling, and overall API performance for deployed applications by introducing new tools/technologies crafted for ML
- Understanding and analyzing the current development and deployment specs for the ML team and proposing scopes of improvement and solutions to improve the same
Share your profile on -careers@xecurify.com
NOTE - Work From the office
Locations - Pune ( Balewadi / Baner)