Senior Machine Learning Operations Engineer

3 weeks ago

Bangalore Metropolitan Area, India Sagri Full time

Sagri, a pioneering AgriTech startup, combines satellite data, AI, and grid technology to tackle critical agricultural and environmental challenges. Our mission is to visualize agricultural land, promote sustainable farming practices, reduce carbon emissions, and drive positive change for farmers, the planet, and future generations.

The Role

We're seeking an MLOps Engineer to manage the end-to-end lifecycle of machine learning models, from development to production. You'll collaborate closely with data scientists, engineers, and domain experts to ensure seamless deployment, maintenance, and optimization of ML models for projects like crop classification, soil health analysis, and carbon emission monitoring.

  • Design and implement automated ML pipelines for developing, testing, deploying, and monitoring ML models.
  • Collaborate with Data Science and Engineering teams to integrate models into production environments.
  • Develop infrastructure for model versioning, scaling, and serving to ensure high availability and low latency.
  • Establish CI/CD processes for model deployment and data pipelines, ensuring reproducibility and consistency across environments.
  • Monitor model performance, set up logging, and create alert systems for ML models in production.
  • Optimize ML workloads for performance and cost-efficiency in cloud environments.
  • Ensure data integrity, compliance, and security standards, especially concerning sensitive agricultural data.
  • Participate in green computing initiatives to minimize the carbon footprint of ML operations.

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.
  • 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.
  • Experience in the agriculture sector or climate tech is a plus.

What's on Offer

  • Work with a well-funded AgriTech startup tackling critical challenges in Agriculture and the Environment.
  • Contribute to a high-impact product driving the future of Agriculture.
  • Work with state-of-the-art technologies in AI, remote sensing, and data analytics.
  • Opportunity for rapid career growth in a fast-expanding startup.

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