AI/ML - Tech Lead / Architect

Armakuni (AWS Premier Partner) , a trusted partner in helping organizations leverage cloud-native technologies to achieve agility, scalability, and resilience.

• Cloud-Native Transformation : Guiding businesses through adopting cloud-native practices to optimize their operations
• DevOps and Platform Engineering : Building robust, secure, and scalable platforms tailored to your unique needs.
• Data Engineering : With our data engineering service you can transform your data into actionable business outcome
• Gen AI & ML : Empower Business strategy with AI-Driven growth through Gen-AI Services
• Tailored Solutions : Providing expert consulting services to deliver long-term success for your teams.

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currently hiring AI/ML - Tech Lead / Architect to join our team!

The following are requirements of skills set:

Skills : Gen AI, LLMs, AWS Sagemaker, AWS Bedrock, MLOps-Mlflow, Kuberflow

Experience : 5-10 Years

Location : Ahmedabad / Hybrid

Roles & Responsibilities :

Model Development & Deployment:

• Design, build, and deploy machine learning models to production environments using AWS SageMaker, AWS Bedrock, and other AWS AI/ML services.
• Develop and deploy Generative AI applications using various LLMs.
• Work on data preprocessing, exploratory data analysis (EDA), feature engineering, and model training pipelines using various ML pipelines and AWS services.
• Implement best practices for model versioning, monitoring, and scaling in production.

Collaboration & Communication

• Collaborate with data engineers to translate business requirements into ML models and work on data science-related problems as needed.
• Work with DevOps and Data Engineering teams to deploy and maintain models in production, with a strong understanding of MLOps.
• Present findings and progress to stakeholders, ensuring alignment with business objectives.

Innovation & Improvement

• Continuously explore and implement new AWS AI/ML services (e.g., Amazon Rekognition, Comprehend, Lex, Polly, AWS Bedrock, and open-source LLMs) to improve existing solutions.
• Optimize models for performance, scalability, and cost-effectiveness in the AWS cloud environment.

Documentation & Compliance:

• Maintain detailed documentation of model architectures, training processes, and deployment pipelines.
• Ensure compliance with industry standards and data privacy regulations.