Interesting Job Opportunity: i2k2 - Lead AWS AI/ML Engineer

i2k2; Delhi; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

i2k2 is seeking an experienced AWS AI & Machine Learning Lead based in Delhi, India, to spearhead the architecture and deployment of machine learning pipelines. The ideal candidate will lead teams and integrate cutting-edge Generative AI services into client platforms.

Responsibilities include mentoring junior engineers on AI development and overseeing the implementation of MLOps practices. Candidates should possess strong expertise in AWS services and have a proven track record in delivering scalable AI/ML solutions.

Qualifications

• Minimum 5 years in a leadership role in AI & Machine Learning.
• Expertise in AWS AI & Machine Learning services.
• Experience in designing and managing MLOps pipelines.

Responsibilities

• Architect and deploy end-to-end machine learning pipelines on AWS.
• Integrate advanced Gen AI services into client platforms.
• Lead implementation of MLOps practices.

Skills

AWS AI & Machine Learning

Generative AI

Cloud Architecture

Machine Learning

Data Engineering

MLOps & DevOps

Programming and Software Development

Tools

Amazon SageMaker

Docker

Kubernetes

Job description

We are seeking an experienced AWS AI & Machine Learning Lead with at least 5 years in a leadership role. The ideal candidate will possess strong expertise in AWS AI & Machine Learning services and have the ability to work independently while effectively leading and mentoring a team.

Key Responsibilities

• Architect and deploy end‑to‑end machine learning pipelines on AWS to streamline model development and production readiness.
• Integrate advanced Gen AI services and large language models into existing client platforms to automate workflows and improve user experiences.
• Lead the implementation of MLOps practices to ensure continuous integration, deployment, and monitoring of AI models at scale.
• Collaborate with data engineering teams to build robust data pipelines that feed high‑quality, structured data into AI models.
• Mentor junior engineers and technical staff on best practices for cloud‑native AI development and infrastructure optimization.
• Evaluate emerging AI technologies and frameworks to maintain the company's competitive advantage in the cloud services market.

Key Skills & Experience Required

• AWS AI & Machine Learning
• Generative AI
• Machine Learning (hands‑on expertise in designing and managing MLOps pipelines mandatory; model building optional)
• AWS AI Services
• Cloud Architecture
• Data Engineering
• MLOps & DevOps
• Programming and Software Development
• End‑to‑end AI/ML solution design and implementation
• Proven track record of delivering scalable AI/ML solutions, driving technical excellence, and leading teams in a fast‑paced, cloud‑native environment

AWS AI & Machine Learning Services

• Amazon Bedrock
• Bedrock Agents
• Bedrock Knowledge Bases
• Model Customization
• Prompt Engineering
• RAG Architecture
• Multi‑Agent Systems
• AI Guardrails

Machine Learning Pipeline

• Amazon SageMaker
• SageMaker Pipelines
• Feature Store
• Model Training & Deployment
• Hyperparameter Tuning
• Model Monitoring

AI Services

• Amazon Textract
• Amazon Comprehend
• Amazon Rekognition
• Amazon Transcribe
• Amazon Translate
• Amazon Polly
• Amazon Lex
• Amazon Kendra

Cloud Architecture

• AWS Well‑Architected Framework
• Multi‑Account Architecture
• IAM & Security
• VPC Design
• API Gateway
• Lambda
• ECS
• EKS
• Step Functions
• EventBridge

Data Engineering

• Amazon S3
• Glue
• Athena
• Redshift
• DynamoDB
• RDS
• Aurora
• Kinesis
• Kafka
• Data Lakes
• Data Warehousing

MLOps & DevOps

• CI/CD for ML
• SageMaker Pipelines
• Docker
• Kubernetes
• MLflow
• Model Registry
• Monitoring & Observability

Programming & Software Development

• Python
• SQL
• PySpark
• FastAPI
• Streamlit
• LangChain
• LangGraph