Machine Learning Ops Engineer

1 week ago

Bengaluru, Karnataka, India Zinnov Management Consulting Full time ₹ 3,00,000 - ₹ 40,00,000 per year

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, ₹4,000,000.00 per year

Benefits:

  • Food provided
  • Health insurance
  • Provident Fund

Application Question(s):

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

Work Location: In person

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