Hiring For AI/ML Architect

2 weeks ago

Delhi Hyderabad NCR Pune, India Coforge Full time US$ 1,20,000 - US$ 2,00,000 per year

Key Responsibilities:

Solution Architecture:

  • Design end-to-end ML solutions using AWS services including SageMaker, EMR, Lambda, EKS, and S3.

  • Architect scalable, secure, and cost-effective ML systems tailored to business needs.

  • Collaborate with stakeholders to translate business requirements into technical solutions.

  • Architect migration plan, analyze and understand dependencies

  • Recommend target state architecture and design for ML and DS model lifecyle on AWS SageMaker AI

  • Architect and design Matillion pipelines

  • Design and migrate the EMR workloads

MLOps Engineering:

  • Build and maintain CI/CD pipelines for ML workflows using tools like CodePipeline, MLflow, and SageMaker Pipelines.

  • Automate model training, deployment, and monitoring processes.

  • Implement model versioning, rollback strategies, and performance monitoring.

Data Engineering & Integration:

  • Work with EMR and Spark for large-scale data processing and feature engineering.

  • Ensure seamless integration of data pipelines with ML models and analytics platforms.

Leadership & Collaboration:

  • Lead cross-functional teams including data scientists, engineers, and DevOps professionals.

  • Mentor junior team members and promote best practices in MLOps and cloud architecture.

  • Drive innovation by evaluating emerging technologies and tools in the AI/ML space.


Required Qualifications:

  • Deep expertise in AWS services: SageMaker, EMR, Lambda, S3, CloudFormation, Matillion.

  • Strong programming skills in Python, with experience in ML frameworks (e.g., TensorFlow, PyTorch).

  • Hands-on experience with MLflow, Docker, Kubernetes, and Terraform.

  • Proven track record of deploying and managing ML models in production environments.

  • Excellent problem-solving, communication, and leadership skills.


Preferred Skills:

  • Experience with SageMaker Studio, Model Monitor

  • Familiarity with data governance, security, and compliance in cloud environments.

  • Knowledge of feature stores, data versioning, and experiment tracking.

  • Certifications in AWS

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