Information Technology

Interesting Job Opportunity: AI/ML Engineer

Information Technology

Pune•On-site•3-5 Yrs•Jun 18

Job description

AI/ML EngineerLLM EngineerAI Model DeploymentDevOps for AIResponsible AIGenerative AI

Overview

AI/ML Engineer with responsibilities including model design and build, data preprocessing, feature engineering, performance tuning, building agentic systems, LLM application development, communicating findings, responsible AI practices, deployment lifecycle management, automation and pipeline management, monitoring and maintenance, infrastructure management, data and model versioning, collaborative communication.

Responsibilities

Work closely with data scientists and business to design and implement AI algorithms, frameworks and architectures
Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources
Integrate structured and unstructured data from internal and external systems into centralized data platforms
Optimize data workflows and queries for performance, scalability, and cost-efficiency
Building Agentic Systems: Developing intelligent AI agents that can reason, plan, and execute tasks autonomously using LLMs and other tools
LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques like parameter-efficient fine-tuning (PEFT) (e.g., LoRA, QLoRA)
Implementing Retrieval-Augmented Generation pipelines to enhance the knowledge and accuracy of LLMs
Utilizing vector databases for efficient storage and retrieval of embeddings generated by LLMs
Crafting effective prompts to elicit desired responses from LLMs
Connecting LLMs and generative models with other systems and APIs to create comprehensive solutions
Collaborate extensively with data scientists, and business during model development and deployment
Maintain updated documentation with details of all aspects of model development lifecycle
Build AI systems which are trustworthy and beneficial considering ethical principles such as fairness, transparency, accountability, privacy and reliability
Implement quantifiable metrics detecting bias, explainability and adherence to regulatory compliance
Orchestrate robust and error-free deployment of AI models into production environments
Ensure that models are deployed securely in compliance with relevant regulations
Create and manage automated pipelines for AI/ workflows including training, testing and deployment
Accelerate the AI model lifecycle ensuring continuous availability of updated and optimized model algorithms, reducing manual errors
Implement CI/CD pipelines to automate the testing and deployment of new model versions, enabling updates reducing manual intervention
Set up monitoring systems to track key metrics such as prediction accuracy, response times, resource utilization, and error rates of deployed models
Identify and troubleshoot issues, ensuring the models continue to perform as expected
Manage the infrastructure required for training, testing, and running AI models in production, including provisioning hardware and software resources, leveraging cloud platforms and containerization technologies like Docker and Kubernetes
Implement version control for data and models, allowing for tracking changes, testing older versions, and ensuring reproducibility
Establish data governance practices and experiment tracking for auditing and compliance purposes
Collaborate extensively with data scientists, software engineers, and DevOps teams to ensure smooth integration AI models
Maintain updated documentation with details of all aspects of model deployment and lifecycle

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Interesting Job Opportunity: AI/ML Engineer

Job description

Overview

Responsibilities