Sr. Machine Learning Operations Engineer

2 weeks ago

Ahmedabad Pune, India beBeeMachineLearning Full time ₹ 5,00,000 - ₹ 8,00,000
Job Title: Sr. Machine Learning Operations Engineer

We are seeking a highly skilled MLOps Engineer to join our team.

  • Key Responsibilities:
    • Design and implement scalable, reliable, and secure pipelines for deploying machine learning models to production.
    • Develop and maintain infrastructure as code (IaC) for managing cloud resources, compute environments, and data storage.
    • Implement monitoring tools to track the performance of models in production, identify issues, and optimize performance.
    • Collaborate with data scientists to understand model requirements and ensure models are production ready.
    • Automate the end-to-end process of training, testing, deploying, and monitoring models.
    • Develop and maintain CI/CD pipelines for machine learning projects.
    • Implement model versioning to manage different iterations of machine learning models.
    • Ensure that the deployed models and data pipelines are secure and comply with industry regulations.
    • Create and maintain detailed documentation of all processes, tools, and infrastructure.
  • Qualifications:
    • 5+ years of experience in a similar role (DevOps, DataOps, MLOps, etc.)
    • Bachelor's or master's degree in computer science, Engineering, or a related field.
    • Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
    • Strong understanding of machine learning lifecycle, data pipelines, and model serving.
    • Proficiency in programming languages such as Python, Shell scripting, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.).
    • Exposure to deep learning approaches and modeling frameworks (PyTorch, TensorFlow, Keras, etc.)
    • Experience with CI/CD tools like Jenkins, GitLab CI, or similar
    • Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
    • Strong software engineering skills in complex, multi-language systems
    • Comfort with Linux administration
    • Experience working with cloud computing and database systems
    • Experience building custom integrations between cloud-based systems using APIs
    • Experience developing and maintaining ML systems built with open-source tools
    • Experience developing with containers and Kubernetes in cloud computing environments
    • Familiarity with one or more data-oriented workflow orchestration frameworks (MLFlow, KubeFlow, Airflow, Argo, etc.)
    • Ability to translate business needs to technical requirements
    • Strong understanding of software testing, benchmarking, and continuous integration
    • Exposure to machine learning methodology and best practices
    • Understanding of regulatory requirements for data privacy and model governance.
  • Preferred Skills:
    • Excellent problem-solving skills and ability to troubleshoot complex production issues.
    • Strong communication skills and ability to collaborate with cross-functional teams.
    • Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack).
    • Knowledge of database systems (SQL, NoSQL).
    • Experience with Generative AI frameworks
    • Preferred cloud-based or MLOps/DevOps certification (AWS, GCP, or Azure)

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