Senior AI/ML Engineer

Role Overview

• The AI/ML Engineer is the architect and guardian of intelligent automation solutions incorporating generative AI and machine learning technologies.
• Ensures operational efficiency and continuous refinement of integrated AI/ML solutions with a strong focus on modern generative AI engineering.
• Responsibility spans the design, maintenance, and optimization of intelligent automation solutions including AI Center troubleshooting and resolution of issues that might arise post-implementation.
• Focus on building generative AI applications with embedded artificial intelligence or machine learning in support of continuous improvement, learning and augmented decision-making.

Requirements

Required Skills:

• Overall experience of 6-10 Years working on Application/framework development
• Min 5+ years of exp in AI/ML-based app/solution development with strong focus on generative AI applications
• Hands-on experience with AWS services including Amazon Bedrock, S3, SageMaker, CDK,Lambda, and other AI/ML services
• Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering, model fne-tuning)
• Hands-on exp with OCR, ICR and OMR technologies is a must
• Good programming knowledge in Python and relevant ML/AI frameworks (TensorFlow, PyTorch, LangChain)
• Good understanding of Document Processing, classifcation, data extraction is a must
• Knowledge in Natural Language Processing (NLP), Deep Learning, and Generative AI is a must
• Hands-on Web application/APIs Development experience is a must
• Profciency in asynchronous/multi-threaded programming
• Strong knowledge of algorithms, data structures, complexity, optimization, caching and security
• Experience with JSON, SOAP, Rest, XML, XHTML, XSD and XSLT
• Strong knowledge of object-oriented concepts and Database concepts Experience with databases like SQL Server, PostgreSQL
• Experience with NoSQL databases and vector databases (for RAG implementations) is a plus
• Knowledge of AWS cloud architecture patterns and serverless computing
• Experience with CI/CD pipelines and DevSecOps practices
• Knowledge of Agile methodologies is desirable
• Experience working with a toolchain that includes TFS, SVN, Git
• Involved in different phases of SDLC and have good working exposure on different SDLCs like Agile Methodologies

Responsibility:

Your responsibility spans the design, maintenance, and optimization of intelligent automation solutions including AI Center troubleshooting and resolution of issues that might arise post-implementation. You will focus on building generative AI applications with embedded artifcial intelligence or machine learning in support of continuous improvement, learning and augmented decision-making.

Key responsibilities include:

Designing and implementing generative AI solutions using Amazon Bedrock, foundation models, and RAG architectures

Building repeatable intelligent solutions/bots for document processing and data cleansing

Developing and deploying scalable ML/AI models on AWS infrastructure

Creating API endpoints and integrations for AI/ML services

Implementing model evaluation, monitoring, and continuous improvement processes Collaborating with cross-functional teams to embed AI capabilities across business functions

Tech Stack

• AWS
• Cloud
• NoSQL
• Postgres
• Python
• PyTorch
• SDLC
• SOAP
• SQL
• Subversion
• Tensorflow
• TFS

Benefits

• Medical
• Dental
• Vision
• Basic Life
• Health Saving Account
• 401K Matching
• Three weeks of PTO/Sick
• 11 Paid Holidays
• Pre-Approved Online Training