Chief Machine Learning Architect

6 days ago

Rajahmundry, Andhra Pradesh, India beBeeMachineLearning Full time ₹ 1,80,00,000 - ₹ 2,50,00,000

Job Opportunity

We are seeking a skilled professional to fill the role of Machine Learning Engineer and develop innovative solutions for our clients. The ideal candidate will have a strong background in machine learning, experience with AWS SageMaker, and the ability to design, develop, and deploy robust ML models in a production environment.

Main Responsibilities:

  • Design and Development: Design, develop, and deploy end-to-end machine learning pipelines on AWS SageMaker.
  • Collaboration: Collaborate with data scientists to translate models and algorithms into production-ready code.
  • Machine Learning Lifecycle: Manage the entire machine learning lifecycle, including data ingestion, model training, validation, and deployment.
  • MLOps: Implement MLOps best practices to automate workflows and ensure model performance and reliability.
  • Optimization: Optimize ML models for performance, scalability, and cost efficiency on the AWS platform.
  • Model Monitoring: Monitor and troubleshoot deployed models to ensure they meet performance and business requirements.
  • Staying Current: Stay current with the latest advancements in machine learning and cloud technologies.

Qualifications and Skills:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • At least 3 years of experience in a machine learning or data science role.
  • Hands-on experience with AWS services, specifically SageMaker.
  • Proficiency in Python and standard ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Experience with containerization technologies like Docker.
  • Solid understanding of MLOps principles and tools for CI/CD.
  • Knowledge of data engineering principles and experience with big data technologies (e.g., Spark, Hadoop).
  • Strong problem-solving skills and the ability to work in a collaborative environment.

Preferred Qualifications:

  • Experience with other AWS services such as S3, Lambda, Glue, and Redshift.
  • Certifications such as AWS Certified Machine Learning – Specialty.
  • Experience with model serving frameworks (e.g., Flask, FastAPI).
  • Experience with version control systems like Git.
  • Familiarity with agile development methodologies.

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