AgriTech MLOps Automation Expert

2 days ago

Bangalore Metropolitan Area, India a Snaphyre Client Full time
Senior MLOps Engineer

We are seeking a highly skilled Senior MLOps Engineer to oversee the entire lifecycle of machine learning (ML) models, from development through production, with a focus on automation, scalability, and monitoring.

The ideal candidate will possess expertise in cloud platforms (AWS, GCP, Azure), infrastructure as code tools (e.g., Terraform, CloudFormation), and container orchestration technologies for scaling ML models. Additionally, they will have experience with CI/CD tools (e.g., Jenkins, GitLab CI, ArgoCD), data pipeline orchestration tools like Apache Airflow or Kubeflow, and monitoring tools and techniques for tracking model performance.

In this role, you will design and implement automated ML pipelines for developing, testing, deploying, and monitoring ML models. You will collaborate closely with Data Science and Engineering teams to integrate models into production environments, ensuring high availability and low latency. Furthermore, you will establish CI/CD processes for model deployment and data pipelines, ensuring reproducibility and consistency across environments.

You will also be responsible for optimizing ML workloads for performance and cost-efficiency in cloud environments, 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 is also an essential aspect of this role.

About the Role

  • Design and implement automated ML pipelines for developing, testing, deploying, and monitoring ML models.
  • Collaborate closely with Data Science and Engineering teams to integrate models into production environments.
  • Establish CI/CD processes for model deployment and data pipelines, ensuring reproducibility and consistency across environments.
  • 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 Candidate Profile

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

What We 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.
  • State-of-the-art technologies in AI, remote sensing, and data analytics.

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