AI/ML Engineer

Role Overview

Cultural Fit:

Effective communication skills for technical discussions Comfortable with Agile methodologies Ability to work remotely Alignment with customer's mission and values Adaptability to varying organizational structures Data Analysis and Data Architecture Skills Strong problem-solving abilities for complex AI/ML challenges

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