Machine Learning Ops Engineer

Overview

Job Title: Machine Learning Ops Engineer

Job Level: Mid-Level

Job Location: Bangalore, India

Key Responsibilities:

• Design, implement and maintain ML pipelines for model training, validation, and deployment
• Automate model deployment processes using CI/CD pipelines and containerization technologies
• Monitor model performance, data drift, and system health in production environments
• Collaborate with data scientists to operationalize machine learning models and algorithms
• Implement version control for models, datasets, and ML experiments using MLOps tools
• Optimize ML infrastructure for scalability, reliability, and cost-effectiveness
• Troubleshoot and resolve issues related to model deployment and production systems
• Maintain documentation for ML workflows, deployment processes, and system architecture
• This position may require availability outside of standard business hours as part of a rotational on-call schedule.

What You’ll Need to Be Successful (Required Skills):

• 2-4 years of experience in software development, DevOps, or data engineering
• Proficiency in Python, SQL, and at least one ML framework such as TensorFlow, PyTorch, Scikit-learn
• Experience with containerization (Docker) and orchestration tools (Kubernetes)
• Knowledge of cloud platforms such as AWS, Azure, GCP and their ML services
• Understanding of CI/CD pipelines, version control (Git), and infrastructure as code
• Familiarity with monitoring tools and logging frameworks for production systems
• Experience with data pipeline tools such as Apache Airflow, Kubeflow, or similar
• Strong problem-solving skills and ability to work in fast-paced, collaborative environments.

Education/ Certifications:

• Bachelor's degree in computer science, Information Management or related field.

Preferred Skills:

• Experience with MLOps platforms such as MLflow, Weights & Biases, Neptune
• Knowledge of streaming data processing such as Kafka, Kinesis
• Familiarity with infrastructure monitoring tools such as Prometheus, Grafana
• Understanding of model interpretability and explainability techniques
• Experience with feature stores and data versioning tools
• Certification in cloud platforms such as AWS ML, Azure AI, GCP ML.

Job Types: Full-time, Permanent

Pay: ₹3,000,000.00 - ₹4,000,000.00 per year

Benefits:

• Food provided
• Health insurance
• Provident Fund

Schedule:

• Day shift
• Morning shift

Supplemental Pay:

• Performance bonus
• Yearly bonus

Application Question(s):

• Are You in Bangalore?
• Are you ok with 5 days' work from office?
• What is your current notice period?

Work Location: In person