MLOps Engineer

About the Role

Join our ML team to design, build, and maintain production ML pipelines. You will work closely with data scientists to deploy, monitor, and scale machine learning models in production environments.

Key Responsibilities

• ✓Build and maintain ML pipelines for model training and deployment
• ✓Implement MLOps best practices and workflows
• ✓Monitor model performance and detect drift
• ✓Automate model retraining and deployment processes
• ✓Manage ML infrastructure and compute resources
• ✓Collaborate with data scientists on model optimization
• ✓Ensure reproducibility and versioning of ML experiments

Required Qualifications

• •Bachelor's degree in Computer Science, Data Science, or related field
• •3+ years of experience in MLOps or ML Engineering
• •Strong understanding of ML model lifecycle
• •Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
• •Proficiency in Python and ML libraries
• •Knowledge of containerization and orchestration (Docker, Kubernetes)
• •Experience with model serving platforms (TensorFlow Serving, MLflow)

Nice to Have

• +Experience with cloud ML services (SageMaker, Vertex AI)
• +Knowledge of model monitoring tools
• +Understanding of feature stores
• +Experience with distributed training
• +Familiarity with AutoML platforms

What We Offer

• ★Competitive salary with performance bonuses
• ★Access to latest ML tools and platforms
• ★Conference and training opportunities
• ★Flexible working arrangements
• ★Health and wellness benefits
• ★Collaborative team environment