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, TorchServe) and experience with MLOps 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, TorchServe)

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, Gitflow 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 recognise 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 programmes in the latest technologies such as MLOps, Machine Learning