MLOps Engineer

MLOps Engineer

Your Role

• Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment
• Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, Torch Serve) and experience with ML'Ops tools
• Develop and maintain CI/CD pipelines for ML workflows
• Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, Torch Serve)
• Optimize ML infrastructure for performance, scalability, and cost-efficiency 

Your Profile

• Strong programming skills in Python, with experience in ML frameworks; understanding of ML-specific testing and validation techniques

• Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques

• Proficiency in cloud platform (AWS) and their ML-specific services

• Strong understanding of DevOps practices and tools (GitLab, Artifactory, Git flow etc.)

• Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques

What you'll love about working here

• We recognize the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance
• Our focus will be your career growth & professional development to support you in exploring the world of opportunities.
• Equip yourself with valuable certifications & training programs in the latest technologies such as MLOps, Machine Learning