INSr AssociateGEN Agentic AI Engineer D&AAdvisoryGurgaon

Job Description & Summary

A career withinData & AnalyticsServices will provide you with the opportunity to help our clients leverage transformation to enhance their customer experiences.

*Responsibilities:

Technical Skills:
Advanced proficiency in Python.
Extensive experience with LLM frameworks (Hugging Face TransformersLangChain) and prompt engineering techniques
Experience with big data processing using Spark for large-scale data analytics
Version control and experiment tracking using Git andMLflow
Software Engineering & Development: Advanced proficiency in Python familiarity with Go or Rust expertise in microservices test-driven development and concurrency processing.
DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform CloudFormation) CI/CD pipelines (GitHub Actions Jenkins) and container orchestration (Kubernetes) with Helm and service mesh implementations.
LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such asvLLMandFastAPI model quantization techniques and vector database management.
MLOps& Deployment: Utilization of containerization strategies for ML workloads experience with model serving tools likeTorchServeor TF Serving and automated model retraining.
Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS GCP Azure) and network security for ML systems.
LLM Project Experience: Expertise in developing chatbots recommendation systems translation services and optimizing LLMs for performance and security.
General Skills: Python SQL knowledge of machine learning frameworks (Hugging Face TensorFlowPyTorch) and experience with cloud platforms like AWS or GCP.
Experience in creating LLD for the provided architecture.
Experience working in microservices based architecture.

Domain Expertise:
Deep understanding of ML and LLM development lifecycle including fine-tuning and evaluation
Expertise in feature engineering embedding optimization and dimensionality reduction
Advanced knowledge of A/B testing experimental design and statistical hypothesis testing
Experience with RAG systems vector databases and semantic search implementation
Proficiency in LLM optimization techniques including quantization and knowledge distillation
Understanding ofMLOpspractices for model deployment and monitoring
Professional Competencies:
Strong analytical thinking with ability to solve complex ML challenges
Excellent communication skills for presenting technical findings to diverse audiences
Experience translating business requirements into data science solutions
Project management skills for coordinating ML experiments and deployments
Strong collaboration abilities for working with cross-functional teams
Dedication to staying current with latest ML research and best practices
Ability to mentor and share knowledge with team members


(PythonFastAPI Microservices K8s RAGVectorDBs)

*Mandatory skill sets

Develop and maintain microservice architecture and API management solutions using REST andgRPCfor seamless deployment of AI solutions.
Collaborate with cross-functional teams including data scientists and product managers to acquire process and manage data for AI/ML model integration and optimization.
Design and implement robust scalable and enterprise-grade data pipelines to support state-of-the-art AI/ML models.
Debug optimize and enhance machine learning models ensuring quality assurance and performance improvements.
Familiarity with tools like Terraform CloudFormation andPulumifor efficient infrastructure management.
Create and manage CI/CD pipelines using Git-based platforms (e.g. GitHub Actions Jenkins) to ensure streamlined development workflows.
Operate container orchestration platforms like Kubernetes with advanced configurations and service mesh implementations for scalable ML workload deployments.
Design and build scalable LLM inference architectures employing GPU memory optimization techniques and model quantization for efficient deployment.
Engage in advanced prompt engineering and fine-tuning of large language models (LLMs) focusing on semantic retrieval and chatbot development.
Document modelarchitectures hyperparameter optimization experiments and validation results using version control and experiment tracking tools likeMLflowor DVC.
Research and implement cutting-edge LLM optimization techniques such as quantization and knowledge distillation ensuring efficient model performance and reduced computational costs.
Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions specializing in text classification sentiment analysis and topic modeling.
Design and execute rigorous A/B tests for machine learning models analyzing results to drive strategic improvements and decisions.
Stayup-to-datewith industry trends and advancements in AI technologies integrating new methodologies and frameworks to continually enhance the AI engineering function.
Contribute to creating specialized AI solutions in healthcare leveraging domain-specific knowledge for task adaptation and deployment.
Enable Skills-Based Hiring No

Preferred Skill Sets:
GenAI / LLMEngineers*Preferred skill sets

Python Machinelearning Deep learning

Years of experience required

5years

EmploymentType :Full Time Permanent

*Education Qualification

Full time B.E