AI Engineer

Job Summary:

We are seeking an experienced AI Engineer with AWS expertise to design, build, and deploy scalable artificial intelligence and machine learning solutions on the AWS cloud platform. The role involves leveraging AWS AI/ML services, managing data pipelines, and ensuring high-performance model deployment in production environments.

Key Responsibilities:

Design, develop, and deploy AI and ML models using AWS cloud infrastructure.

Utilize AWS AI/ML services such as Amazon SageMaker, AWS Lambda, AWS Glue, Comprehend, Rekognition, and Polly.

Build and manage end-to-end machine learning pipelines (data ingestion, training, deployment, and monitoring).

Integrate AI models with existing applications via API Gateway or Lambda functions.

Implement data preprocessing, feature engineering, and model optimization for better accuracy and performance.

Monitor model performance, retraining cycles, and automate ML workflows using AWS tools.

Collaborate with cross-functional teams including data scientists, DevOps, and cloud engineers.

Maintain best practices for security, scalability, and cost optimization on AWS.

Research and recommend new AWS tools or AI frameworks to enhance solution performance.

Qualifications & Skills:

Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.

Experience: 5 +years of experience in AI/ML engineering with strong exposure to AWS.

Technical Skills:

Proficiency in Python and experience with libraries such as TensorFlow, PyTorch, scikit-learn, and pandas.

Hands-on experience with Amazon SageMaker for building, training, and deploying ML models.

Strong knowledge of AWS core services, including:

EC2, S3, Lambda, Glue, CloudFormation, Step Functions, and API Gateway.

AWS AI/ML services: SageMaker, Rekognition, Comprehend, Lex, Polly, Bedrock (for GenAI).

Understanding of MLOps on AWS, including CI/CD for ML pipelines.

Experience in containerization and orchestration (Docker, ECR, ECS, or Kubernetes).

Familiarity with data engineering workflows on AWS using Glue, Redshift, or Athena.

Good understanding of cloud security, IAM, and cost optimization principles.

Soft Skills:

Strong analytical and problem-solving abilities.

Excellent teamwork and communication skills.

Ability to work in an agile, fast-paced environment.

Continuous learning mindset for new AWS and AI technologies.

Preferred Qualifications:

AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect certification.

Experience with Generative AI, LLMs, or AWS Bedrock.

Familiarity with data versioning tools (DVC, MLflow) and monitoring solutions (CloudWatch, SageMaker Model Monitor).

Experience integrating AI solutions with business applications or APIs.

Key Performance Indicators (KPIs):

Accuracy and performance of deployed AI models.

Uptime and scalability of AI systems on AWS.

Cost efficiency and resource optimization on AWS infrastructure.

Speed of AI model development-to-deployment lifecycle.

Job Type: Full-time

Pay: ₹1,000,000.00 - ₹1,500,000.00 per year

Work Location: In person