Senior MLOps Engineer

4 weeks ago

Bangalore Metropolitan Area, India a Snaphyre Client Full time

Our client, a pioneering AgriTech startup, is revolutionizing agriculture and the environment by harnessing satellite data, artificial intelligence, and grid technology.

The Role

As a seasoned Senior MLOps Engineer, you will oversee the entire lifecycle of machine learning models, from development to production, with a focus on automation, scalability, and monitoring.

Key responsibilities include:

  • Designing and implementing automated ML pipelines for developing, testing, deploying, and monitoring ML models.
  • Collaborating closely with Data Science and Engineering teams to integrate models into production environments.
  • Developing infrastructure for model versioning, scaling, and serving to ensure high availability and low latency.
  • Establishing CI/CD processes for model deployment and data pipelines, ensuring reproducibility and consistency across environments.
  • Monitoring model performance, setting up logging, and creating alert systems for ML models in production.
  • Optimizing ML workloads for performance and cost-efficiency in cloud environments (e.g., AWS, GCP, or Azure).
  • Ensuring data integrity, compliance, and security standards, especially concerning sensitive agricultural data.
  • Participating in green computing initiatives to minimize the carbon footprint of ML operations.
  • Assisting in creating and maintaining a central data platform for collaborative model development and application, ensuring data pipelines and models are well-documented.

Ideal Profile

  • You possess a Bachelor's degree in Computer Science, Engineering, or a related field.
  • You have 6–7 years of experience in IT, focusing on MLOps, DevOps, or Data Engineering roles.
  • You possess expertise with cloud platforms (AWS, GCP, Azure) and infrastructure as code tools (e.g., Terraform, CloudFormation).
  • You demonstrate hands-on experience with Kubernetes or other container orchestration technologies for scaling ML models.
  • You are proficient with CI/CD tools (e.g., Jenkins, GitLab CI, ArgoCD) and familiar with version control (e.g., Git).
  • You have experience with data pipeline orchestration tools like Apache Airflow or Kubeflow.
  • You understand monitoring tools and techniques for tracking model performance (e.g., Prometheus, Grafana, ELK stack).
  • You are knowledgeable in data management and ETL processes, particularly with agricultural and environmental data.
  • You show proficiency in Python, with exposure to ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • You have experience in the agriculture sector or climate tech, with knowledge of carbon/GHG emissions projects.
  • You are familiar with geospatial data and remote sensing tools (e.g., Sentinel-2, Google Earth Engine) is a plus.
  • You display a commitment to automation, efficiency, and sustainability in ML operations.

What's on Offer?

  • Work with a well-funded AgriTech startup tackling critical challenges in Agriculture and the Environment
  • Play a pivotal role in shaping a high-impact product driving the future of Agriculture
  • Work with state-of-the-art technologies in AI, remote sensing, and data analytics

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