Senior AI/ML Data Engineer

2 weeks ago

Bengaluru, Karnataka, India beBeeMachine Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Driven by innovation and a passion for fashion, we are seeking an exceptional Lead Machine Learning Data Engineer to spearhead the development of cutting-edge machine learning models.

Job Overview

This is an incredible opportunity to leverage your expertise in MLOps and data engineering to drive business growth and transformation.

Key Responsibilities:

  • Design and deploy scalable machine learning pipelines using scikit-learn, TensorFlow, and PyTorch.
  • Develop and implement robust MLOps best practices and frameworks to ensure model reliability and performance.
  • Collaborate with cross-functional teams to design and implement efficient data pipelines that support business objectives.
  • Utilize Snowflake-centric MLOps leveraging Snowpark developer framework to drive data-driven decision-making.
  • Implement real-time model monitoring and anomaly detection using statistical drift detection.
  • Design and implement modular, testable, and documented transformations using DBT to streamline ML workflows.

Requirements:

  • 6-10 years of experience in MLOps, ML Model Development, and data engineering.
  • Strong problem-solving skills with a proactive approach to optimization.
  • Excellent communication and collaboration skills to work effectively across global teams and time zones.
  • Bachelor's degree in computer science, engineering, data science, or a related field.
  • Proficiency with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and understanding of supervised and unsupervised learning algorithms.
  • Experience with CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI) to automate deployment processes.
  • Adept in programming languages such as Python, Java, or Scala, with solid knowledge of SQL and NoSQL databases.
  • Familiarity with cloud services (AWS, Azure, Google Cloud) and containerization technologies (Docker, Kubernetes).
  • Experience with data pipeline frameworks (e.g., Apache Airflow, Apache Kafka).

Nice to Have:

  • Azure ML integration with Snowflake: Utilize Snowflake as the data layer, Azure ML for model training, and push back results for inference.
  • Anomaly Detection & AutoML: Building modular components that can run and scale via Snowpark.
  • Model Monitoring: Statistical drift detection using Snowflake + Power BI dashboards.
  • Data Build tool (DBT): Modular, testable, and documented transformations feeding ML workflows.

Core Competencies:

  • Strong problem-solving skills with a proactive approach to optimization.
  • Excellent communication and collaboration skills.
  • Experience in designing and implementing MLOps best practices and frameworks.

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