491 Generative Ai Jobs - Page 19

Develop and implement AI scripts using Python to automate processes and tasks. Apply knowledge of the OpenAI API to create complex AI workflows and enhance automation solutions. Lead the deployment of AI solutions in Azure Apply Langchain Required Candidate profile 5+ years of development experience in .NET , Python and Azure 3+ years of experience in Data Science, Machine learning along with hands on experience with GenAI and LLMs

Job Description for GB5A(Dev) Primary Role Primarily responsible for working as Tech Lead i.e. leading the team and mentoring it technically. Provide hands-on technical leadership in the design, development, and deployment of generative AI models and systems. Serve as the technical point of contact for cross-functional teams, ensuring seamless collaboration between product, engineering, and data science teams. Responsibilities & KPIs Guiding the team technically and helping them solve the technical problems, throughout the project. Responsible for defining project goals, timelines, and deliverables in collaboration with stakeholders. Ensure scalability, robustness, and cost-efficiency of AI solutions. Conduct code reviews, provide constructive feedback, and ensure adherence to best practices in AI development. Build and maintain workflows to manage multiple POCs and project workloads efficiently. Collaborate with data scientists and domain experts to ensure model accuracy and relevance. Architect end-to-end Generative AI pipelines for model training, evaluation, and deployment using state-of-the-art tools and techniques Optimize AI models for speed, accuracy, and cost-efficiency. Ensure compliance with security and ethical standards. Address challenges like data drift and model degradation Proactively introduce innovative generative AI methodologies to address complex business challenges. Foster a culture of experimentation and continuous learning within the team. Ensure alignment between business goals and technical implementations. Desired Skills B.E./B.Tech degree in Computer Science, Information Science, or a related field from a leading institute preferred. Good leadership and people management skills. Excellent communication skills for translating technical concepts to non-technical stakeholders. Hands-on experience with Python Hands-on experience in machine learning, natural language processing, deep learning, and Generative AI technologies like LLM, RAG, Multi Modal architecture. Familiarity with frameworks like TensorFlow, PyTorch, Keras or Hugging Face. Familiarity with MLOps and CI/CD pipelines for AI workflows. Knowledge of cloud platforms (AWS, Azure, or GCP) for deploying AI solutions. Familiarity with current AI trends and open source technologies. Strong problem-solving and analytical skills. Ability to work on multiple projects simultaneously and manage priorities effectively. Exposure to financial services domains is a plus. Basic understanding of UI Frameworks (e.g. Angular) is a plus.

Location: Remote Timings: Full Time (As per company timings) Notice Period: (Immediate Joiner - Only) Experience: 4 Years Key Responsibilities: Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications. Host and deploy LLMs on custom infrastructure, ensuring high availability and performance. Conduct LLM evaluation following best practices as outlined in the Hugging Face LLM Evaluation Guide. Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs. Ensure model scalability, security, and compliance with industry standards. Required Skills and Experience : Experience: 4 years of hands-on experience with Generative AI and LLMs. (Total IT experience is not a priority.) Domain Expertise: Prior experience in the fintech or financial services domain is essential. LLM Fine-Tuning: Demonstrated expertise in fine-tuning LLMs for live production environments (academic or PoC projects are not relevant). Infrastructure Management: Experience with hosting and deploying LLMs on custom infrastructure. LLM Evaluation: Proficiency in conducting LLM evaluations using industry-recognized methodologies and frameworks. Technical Skills : Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Strong understanding of LLM architectures and their optimization techniques. Familiarity with cloud-based or on-premise infrastructure for AI deployments Location-Remote,Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649

Job Summary We are looking for a highly skilled Technical Architect with expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. The ideal candidate should have experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overall experience of 9-12 years. This role involves architecting AI/ML/GenAI-driven applications, ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams. Key Responsibilities Technical Leadership & Architecture Design and implement scalable, secure, and high-performance architectures on AWS for AI/ML applications. Architect multi-tenant, enterprise-grade AI/ML solutions using AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions. Lead full lifecycle development of AI/ML/GenAI solutionsfrom PoC to productionensuring reliability and performance. Define and implement best practices for MLOps, DataOps, and DevOps on AWS. AI/ML & Generative AI Expertise Design Conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures using models like Claude (Anthropic), Mistral, Llama, and Titan. Optimize LLM inference pipelines, embeddings, vector search, and hybrid retrieval strategies for AI-based applications. Drive ML model training, deployment, and monitoring using AWS SageMaker and AI/ML pipelines. Cloud & Infrastructure Management Architect event-driven, serverless, and microservices architectures for AI/ML applications. Ensure high availability, disaster recovery, and cost optimization in cloud deployments. Implement IAM, VPC, security best practices, and compliance. Team & Client Engagement Lead and mentor a team of ML engineers, Python Developer and Cloud Engineers. Collaborate with business stakeholders, product teams, and multiple clients to define requirements and deliver AI/ML/GenAI-driven solutions. Conduct technical workshops, training sessions, and knowledge-sharing initiatives. Multi-Client & Business Strategy Manage multiple client engagements, delivering AI/ML/GenAI solutions tailored to their business needs. Define AI/ML/GenAI roadmaps, proof-of-concept strategies, and go-to-market AI solutions. Stay updated on cutting-edge AI advancements and drive innovation in AI/ML offerings. Key Skills & Technologies Cloud & DevOps AWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS MLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK) Security: IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito AI/ML & GenAI LLMs & Generative AI: Bedrock (Claude, Mistral, Titan), OpenAI, Llama ML Frameworks: TensorFlow, PyTorch, LangChain, Hugging Face Vector DBs: OpenSearch, Pinecone, FAISS RAG Pipelines, Prompt Engineering, Fine-tuning Software Architecture & Scalability Serverless & Microservices Architecture API Design & GraphQL Event-Driven Systems (SNS, SQS, EventBridge, Step Functions) Performance Optimization & Auto Scaling

Experience: 4+ years of overall experience, with at least 2+ years of hands-on work in Generative AI and Agentic systems Key Skills: Practical application of LLMs, Gen AI, Agentic frameworks (note: candidates may reference tools like CrewAI or AutoGen), prompt engineering, fine-tuning, RAG, multi-agent systems, and autonomous AI agents Technical Proficiency: Strong coding skills in Python; experience with ML frameworks like TensorFlow or PyTorch; familiarity with tools such as LangChain, and platforms like Databricks or AWS Role Type: Individual Contributor only please do not source candidates with a managerial background Location: Mumbai or Bangalore Shift Timing: 12:00 PM – 9:00 PM

Job Description Azure Cloud Data Analytics, AI and Computer Vision Specialist Job Title: Azure Cloud Data Analytics, AI and Computer Vision Specialist Industry: Software Development Employment Type: Full Time Location: Noida, India About Us: We are a health tech-focused organization creating innovative, scalable solutions to transform lives. We are seeking a skilled Azure Cloud Data Analytics, AI and Computer Vision Specialist to drive impactful projects and lead cutting-edge product development.At I-Line Pvt Ltd, were on a mission to redefine healthcare through cutting-edge technology. Our focus is on creating intelligent, affordable, and accessible healthcare solutions that harness the power of AI, AR/VR, IoT, and advanced tech to build the healthcare systems of the future. Collaborating with some of the largest hospitals in the country, we are deeply committed to identifying and solving real-world problems with innovative and unconventional approaches. If you're driven by innovation and eager to make a tangible impact in healthcare, this could be your next big move. Responsibilities: Azure Data Analytics Pipelines: Build cost-effective, scalable Azure data pipelines from scratch, optimizing ETL processes and handling large datasets reliably. Product Development: Involved with 0-to-1 product development in data analytics and AI space, from ideation to execution, ensuring innovative and impactful solutions. Computer Vision Development: Develop and deploy advanced computer vision models, including object detection, classification, segmentation, and real-time applications. LLM-Based Product Development: Design AI-driven solutions leveraging large language models (LLMs), with a focus on health tech innovations. Innovation in Health Tech: Build transformative, AI-enabled products while adhering to regulatory standards and data security protocols. Qualifications: Proven experience in Azure data pipelines using tools like Data Factory, Synapse Analytics, and Databricks. Expertise in Python, SQL, deep learning frameworks (TensorFlow, PyTorch), and deploying AI-based solutions. Experience in 0-to-1 product development is a strong advantage. Education: B.Tech from a premier institute is highly preferred. A Ph.D. in a relevant field is an outstanding advantage. Prior experience in health tech is highly desirable. Please share CV at madhulika.mishra@IQline.co.in

As a Development Engineer at Nokia, you will be a key player in our dynamic software team, driving innovative solutions for high-complexity features in our telecommunications products. Your expertise in Kubernetes and cloud-native architectures will be pivotal as we deploy containerized machine learning applications to enhance performance and reliability. Our work environment emphasizes creativity, teamwork, and a commitment to pushing the boundaries of technology in 4G, 5G, and IoT. You have: Bachelor's degree in engineering with 2-5 years of experience in Core Java on Telco grade products. Proficiency in Python programming. Experience with Kubernetes for deploying containerized ML applications. Experience in developing and deploying neural network or LSTM-based models. It would be nice if you also had: Exposure to Generative AI (GenAI) development and tools. Familiarity with Telecommunications concepts and technologies (e.g., 4G, 5G, IoT, network management). Develop innovative software solutions for complex challenges in next-gen telecommunications products. Enhance and refactor existing codebases while adhering to best practices for code quality and performance. Implement and manage Kubernetes for deploying scalable, containerized ML applications. Contribute to the architecture design by creating foundational components focused on performance and scalability.

Software Architect Generative AI & LLM Systems job location Hyderabad - Noida or Gurgaon Job Overview We are seeking a highly experienced and hands-on Software Architect to lead the design and deployment of Large Language Model (LLM)-powered applications across cloud and on-prem environments. This role demands deep expertise in full-stack software development, high-performance inference systems, and cutting-edge generative AI workflows. You will play a key role in scaling AI infrastructure, maximizing throughput, and educating cross-functional teams on best practices for building LLM-driven solutions. Key Responsibilities LLM Deployment & Infrastructure Design: Architect, deploy, and maintain LLMs on cloud-based GPU clusters (e.g., AWS, GCP, Azure) or on-premise hardware including NVIDIA HGX and smaller GPU-accelerated instances. Bonus points for experience deploying containerized LLM applications in GPU clusters. Performance Optimization on Software Layer: Optimize LLM serving stacks using frameworks such as vLLM, TensorRT-LLM, or DeepSpeed to improve inference throughput and reduce time-to-first-token latency. Prompt Engineering & Optimization: Design, test, and refine prompts for LLMs to extract the highest quality output. Mentor team members on prompt engineering strategies and few-shot examples. I nference Efficiency & Scalability: Architect systems to maximize low-latency performance and time-to-first-token even under high demand. GenAI Application Architectu re: Build and lead GenAI application development using Langchain, designing modular pipelines for agents, tools, and memory systems. Define architectural patterns and reusable workflows. Team Enablement & Education: Educate and upskill engineering teams on best practices in GenAI development, inference performance, and prompt design through documentation, workshops, and code reviews. RAG with SQL-based Systems: Design and implement retrieval-augmented generation (RAG) pipelines that leverage SQL-like structured databases for high-relevance grounding. Vector Database Integration (Nice-to-Have): Bonus: Architect and optimize RAG systems using vector embeddings and specialized vector databases such as FAISS, Weaviate, or Pinecone. Requirements Must-Have Skills: 7+ years of full-stack development and software architecture experience Proven track record deploying LLMs in production, both on-premise and cloud GPU environments Strong hands-on experience with v LLM, Langchain, and model serving performance tuning Deep knowledge of prompt engineering, token economy, and optimizing LLM behavior Experience designing and scaling inference pipelines for latency and throughput Strong experience with Python and either TypeScript or Golan g Familiarity with deploying applications to hyperscalers (AWS, GCP, Azure) Strong knowledge of SQL databases and data retrieval strategies for grounding LLM responses Nice-to-Have Skills: Experience with vector databases and embedding-based retrieval in RAG pipelines Experience with orchestrating containerized LLM deployments using Kubernetes or Ray Familiarity with streaming inference systems and token-by-token UX optimizations Background in AI/ML systems, MLOps, or research-to-prod workflows conact 95134 87487

Role & responsibilities Mandatory: 2-5 years of experience in roles involving cloud platforms, data science, Python development, and experience with GenAI models . Proven track record of designing and deploying scalable cloud-based data solutions and delivering impactful AI/ML and GenAI models. Preferred candidate profile 2-5 years of hands-on experience in the development and deployment of Machine Learning (ML) projects. Exposure to Computer Vision and Natural Language Processing (NLP), especially Large Language Models (LLMs), will be a significant advantage. Drive innovation: Explore, experiment with, and integrate cutting-edge ML techniques and frameworks into projects. Experience in Computer Vision, NLP, and LLMs in production environment will be a plus. Exposure to data volume extremes (high volume, constrained volume) will be a plus. Document workflows, methodologies, and findings for both technical and non-technical stakeholders.

About the role: Were building an agentic AI platform that turns one line of text and a video feed into end-to-end, real-time computer-vision solutionsthink semantic video search, object / action recognition, and task-oriented visual agents deployable with a single click. As a Gen AI ML Engineer, youll architect the core vision & multimodal-reasoning stack and pave the road from prototype to production. Roles and Responsibilities: Semantic video search Ship a pipeline that allows users to type show every forklift near aisle 5 in the last 30 minutes and get keyed-off clips in 1 s. Wire embeddings to a hybrid FAISS/HNSW index; surface results through a simple REST & React playground. Create agentic pipelines Chain vision language models and zero/few-shot vision models with LLM planners (Gemini, GPT-4o, AutoGen, etc.) so a single prompt becomes a multi-step perception workflow. Profile and accelerate inference (TensorRT, ONNX, quantization, batching) to meet latency / throughput targets on GPU and CPU fleets. Rapid prototyping loops Run weekly paper-to-prototype spikes: reproduce a fresh arXiv idea, benchmark, and decide go/no-go in 5 days. Hand successful python scripts & checkpoints to MLOps for productionizationno plumbing marathons. Data & Evaluation Spin up scalable pipelines for video ingestion, labeling (active learning, weak supervision), experiment tracking, and continuous evaluation. Collaborate & Lead Partner with product and ML Ops engineers; set research direction, mentor future hires, and establish best practices. Must-have skill set: 13 years deep-learning research experience (internships & grad work count). Fluency in Python + PyTorch; comfortable hacking large vision/LLM repos. Proof you ship ideasfirst-author paper, OSS repo, Kaggle medal, or faithful reproduction of a cutting-edge model. Hands-on with LLM prompting/fine-tuning and at least one agent framework. Able to turn fuzzy product asks into measurable experiments and explain results clearly. Bonus cred: Large-scale video retrieval or temporal grounding experience. Prior work building agentic-AI pipelines that combine perception models with LLM reasoning. Open-source contributions to GenAI/vision libs (OpenCLIP, Vid2Seq, ViperGPT, etc.). What can you expect? Ability to shape the future of manufacturing by leveraging best-in-class AI and software; we are a unique organization with niche skill set that you would also develop while working with us World class work culture, coaching and development Mentoring from highly experienced leadership from world class companies (refer to Ripik.AI website for details) International exposure

Job Description: We are seeking an experienced Technical Architect to lead the architecture and implementation of a next-generation Generative AI system. This role requires expertise in Microsoft Azure technologies and enterprise-grade software design. The ideal candidate will be responsible for setting up scalable architecture, guiding development teams, and ensuring security and compliance with best practices and organizational standards. Tech Stack: Azure, .NET Core, C#, Blazor/Angular/React, Azure DevOps, Cognitive Services, SQL, Cosmos DB, Power BI & more Location: Primarily Work from Home with a short 5-day visit to our Bangalore office once every 6 months Employment Type: Full Time Key Responsibilities: Design and implement enterprise software systems using modern Microsoft and Azure technologies. Define system architecture for a Generative AI project, ensuring scalability, performance, and security. Lead and participate in architecture reviews and code reviews, enforcing secure coding and software design best practices. Mentor developers, assist in resolving technical challenges, and propose long-term architectural solutions. Evaluate third-party tools and frameworks, and make recommendations aligned with project needs. Manage CI/CD pipelines using Azure DevOps or GitHub Actions for seamless deployment and integration. Automate provisioning and deployments using ARM templates, Azure CLI, PowerShell, Helm, and Bicep. Implement solutions using Azure PaaS services like Azure Functions, App Services, Logic Apps, and Cognitive Services. Monitor application performance and reliability using Azure Monitor, Application Insights, and profiling tools. Work closely with stakeholders to gather requirements, provide updates, and translate business needs into technical solutions. Efficiently handle multiple projects, ensuring timely delivery and problem resolution. Technical Skills Required: Languages & Frameworks: C#, .NET Core/Framework, ASP.NET, MVC, WCF, Web API, Entity Framework, LINQ/PLINQ Frontend: Blazor, Angular, React, Vue.js, jQuery, Bootstrap, Knockout Database: SQL Server (with tuning), Azure SQL, Cosmos DB, NoSQL, Blob Storage BI & ETL Tools: SSIS, SSRS, Power BI DevOps & Automation: Azure DevOps (Repos, Pipelines, Artifacts, Boards), GitHub Actions, PowerShell, ARM, Bicep, Helm Cloud Expertise: IaaS, PaaS, SaaS, Azure Functions, App Services, Logic Apps, Cognitive Services Monitoring & Security: Application Insights, Azure Monitor, Secure Coding Practices Bonus: Exposure to Generative AI technologies and implementation Candidate Profile: 10+ years of experience in software development and architecture Strong leadership, team collaboration, and communication skills Ability to drive end-to-end architecture strategy and execution Proven problem-solving skills and a proactive mindset Comfortable working in fast-paced, agile environments

JOB DESCRIPTION Title: Software Engineer - Data Science Full time Chennai Data Scientist Role Type: Location: Reports to: Summary of the profile: We are seeking a highly motivated and innovative Data Scientist with 3-5 years of experience to join our team, with a focus on leveraging Generative AI and Large Language Models (LLMs). The ideal candidate will be passionate about exploring the potential of these cutting-edge technologies to solve complex problems and create impactful solutions. You will collaborate with cross-functional teams to research, develop, and deploy generative AI models and LLM-powered applications. What youll do here: Explore and experiment with various generative AI models (e.g., GANs, VAEs, diffusion models) and LLMs (e.g., GPT, BERT, Llama). Fine-tune pre-trained LLMs for specific tasks and domains. Develop and implement generative models for tasks like data augmentation, content generation, and synthetic data creation. ¢ ¢ ¢ Prompt engineering, and prompt iteration. Collect, clean, and preprocess large text datasets for LLM training and evaluation. Perform natural language processing (NLP) tasks such as text classification, sentiment analysis, and entity recognition. ¢ ¢ Use LLMs to assist in data cleaning and data understanding. Develop and evaluate machine learning models, including those leveraging generative AI and LLMs. ¢ Evaluate model performance using relevant metrics and techniques, including those specific to LLMs (e.g., perplexity, BLEU score). ¢ ¢ Tune hyperparameters to optimize model performance. Create compelling visualizations and reports to communicate insights from generative AI and LLM experiments. ¢ ¢ Present findings to both technical and non-technical audiences. Collaborate with engineers, product managers, and researchers to define project requirements and deliver solutions. ¢ ¢ Communicate effectively with team members and stakeholders, both verbally and in writing. Stay up-to-date with the latest advancements in generative AI and LLMs. Copyright © RESULTICKS Solution Inc 1 ¢ ¢ Assist in deploying generative AI models and LLM-powered applications to production environments. Monitor model performance and retrain models as needed. What you will need to thrive: ¢ ¢ 3-5 years of professional experience in data science, with a growing interest in Generative AI and LLMs. Proficiency in Python and relevant libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers). ¢ ¢ ¢ ¢ ¢ ¢ Experience with NLP techniques and libraries. Understanding of machine learning algorithms and statistical concepts. Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI). Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience with Prompt engineering, version control systems like Git and cloud platforms like GCP, AWS or Azure is a plus Preferred Skills: ¢ ¢ ¢ ¢ ¢ ¢ Experience with fine-tuning LLMs for specific tasks. Experience with deploying LLMs in production environments. Knowledge of deep learning architectures relevant to generative AI and LLMs. Familiarity with vector databases. Experience with RAG (Retrieval Augmented Generation) architectures. Experience with the Langchain Library. Education: ¢ Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. Core competencies: ¢ Communication, Analytical & Problem-Solving Skills Copyright © RESULTICKS Solution Inc 2 About RESULTICKS RESULTICKS is a fully integrated connected experience platform for Real Time Audience Engagement. RESULTICKS empowers brands to create data-driven communications to their audiences and drives business decisions through its award-winning, AI-powered big data cloud solution. Supported by the worlds first customer data blockchain, RESULTICKS unlocks incredible digital transformation possibilities by delivering the full 360 view of the customer through data consolidation and omnichannel orchestration. Built from the ground up by experts in marketing, technology, and business management, RESULTICKS enables brands to make a transformational leap to conversion- driven, growth-focused personalized engagement. With an advanced CDP at its core. RESULTICKS offers AI-powered omnichannel orchestration, complete analytics, next-best engagement, attribution at the segment-of-one level, and the worlds first marketing block chain. ¢ RESULTICKS has been named to the Gartners Magic Quadrant 2021 for Multichannel Marketing Hubs for five years in a row and has been awarded with the Microsoft Elevating Customer Experience with AI award. ¢ Headquartered in Singapore and New York City, RESULTICKS is one of the top global martech solutions servicing both B2B/B2B2C and B2C segments. RESULTICKS global presence includes the United States, India, Singapore, Indonesia, Malaysia, Vietnam, Thailand, and the Philippines. Watch video on RESULTICKS - https://www.youtube.com/watch?v=G_OwGy6unP8 Copyright © RESULTICKS Solution Inc 3

Immediate opening for "AI Architect (Generative AI)" Location : Remote Experience :- 15 to 23 yrs Quantaleap INC. is seeking a highly experienced AI Architect with deep expertise in Generative AI to drive innovative solution design and architecture for enterprise use cases. This role requires a strategic thinker with a strong foundation in AI/ML technologies and a proven ability to lead high-impact AI initiatives across diverse domains. Key Responsibilities: Architect end-to-end AI solutions leveraging Generative AI technologies (LLMs, diffusion models, transformers, etc.). Evaluate and recommend cutting-edge tools, frameworks, and models suitable for enterprise-grade deployments. Collaborate with cross-functional teams for RFP responses, technical proposals, and client presentations. Lead the development of scalable AI solutions from POC to production across multiple industry verticals. Guide technical teams on best practices in AI model development, fine-tuning, and deployment. Must-Have Skills: 15+ years of overall experience with a strong focus on AI/ML architecture In-depth knowledge of Generative AI technologies, including LLMs (GPT, BERT), GANs, and foundation models Experience in deploying AI models in cloud-native and on-prem environments Strong understanding of MLOps, data pipelines, and model lifecycle management Proven track record in presales, RFP responses, and enterprise solutioning Excellent stakeholder management and client-facing communication skills Interested can share their updated resume to anitha.mudaliyar@quantaleap.com

Open & Direct Walk-in Drive event | Hexaware technologies, Data Scientist AI/ML with GEN AI in Chennai, Tamilnadu on 10th May [Saturday] 2025 NLP, Python, ML, GEN AI, Deep Learning, Chat GPT Dear Candidate, I hope this email finds you well. We are thrilled to announce an exciting opportunity for talented professionals like yourself to join our team as a Data Scientist AI/ML with GEN AI. We are hosting an Open Walk-in Drive in Chennai, Tamilnadu on 10th May [Saturday] 2025 , and we believe your skills in Data Scientist AI/ML with GEN AI align perfectly with what we are seeking. Details of the Walk-in Drive: Date: Chennai, Tamilnadu on 10th May [Saturday] 2025 Experience: 9 years to 12 years Time: 9.30 AM to 4PM Point of Contact: Aishwarya G / AISHWARYAG5@hexaware.com Venue: HEXAWARE TECHNOLOGIES H-5, Sipcot It Park, Post, Navalur, Siruseri, Tamil Nadu 603103 Work Location: Open (Bangalore/ Pune/ Mumbai/ Dehradun/ Chennai/ Coimbatore) Key Skills and Experience: GenAI & Data Science; Digital Architecture & Enablement; Emerging Tech & Innovation Evangelist Principles and workings of generative models. Knowledge of saving and loading AI models, such as using formats like ONNX or native formats of deep learning frameworks. Cloud platforms like AWS, GCP, or Azure, especially services related to AI and ML. Containerization tools like Docker to package the application and its dependencies. GPUs, TPUs, or other accelerators, and how to leverage them for AI inference. Techniques like model quantization, pruning, and distillation to improve inference speed and reduce memory footprint. Distribute incoming application traffic across multiple instances to ensure optimal resource utilization. Set up monitoring tools to track the health, uptime, and performance of the deployed application. Secure deployment of applications, including encryption, authentication, and authorization mechanisms. Data protection principles, especially when handling user data or other sensitive information. Proficiency with tools like Git. CI/CD pipelines and tools like Jenkins, Travis CI, or GitHub Actions. Networking principles to ensure the application is accessible and communicates effectively with other services or databases. Integrating databases to store or retrieve data, especially if the AI application requires real-time data access. What to Bring: Updated resume Photo ID, Passport size photo Mention "Aishwarya G" at the top of your resume. How to Register: To express your interest and confirm your participation, please reply to this email with your updated resume attached. Walk-ins are also welcome on the day of the event. This is an excellent opportunity to showcase your skills, network with industry professionals, and explore the exciting possibilities that await you at Hexaware Technologies. If you have any questions or require further information, please feel free to reach out to me at AISHWARYAG5@hexaware.com We look forward to meeting you and exploring the potential of having you as a valuable member of our team.

Open & Direct Walk-in Drive event | Hexaware technologies, Data Scientist AI/ML with GEN AI in Chennai, Tamilnadu on 10th May [Saturday] 2025 NLP, Python, ML, GEN AI, Deep Learning, Chat GPT Dear Candidate, I hope this email finds you well. We are thrilled to announce an exciting opportunity for talented professionals like yourself to join our team as a Data Scientist AI/ML with GEN AI. We are hosting an Open Walk-in Drive in Chennai, Tamilnadu on 10th May [Saturday] 2025 , and we believe your skills in Data Scientist AI/ML with GEN AI align perfectly with what we are seeking. Details of the Walk-in Drive: Date: Chennai, Tamilnadu on 10th May [Saturday] 2025 Experience: 9 years to 12 years Time: 9.30 AM to 4PM Point of Contact: Aishwarya G / AISHWARYAG5@hexaware.com Venue: HEXAWARE TECHNOLOGIES H-5, Sipcot It Park, Post, Navalur, Siruseri, Tamil Nadu 603103 Work Location: Open (Bangalore/ Pune/ Mumbai/ Dehradun/ Chennai/ Coimbatore) Key Skills and Experience: Deep Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, or Keras. Custom Model Training: Ability to fine-tune and train models on specific datasets, understand overfitting, and apply regularization techniques. Integration Skills: Proficiency in integrating AI functionalities into applications, web services, or mobile apps. Optimization: Knowledge of optimizing model performance and reducing latency for real-time applications. Version Control and Collaboration Tools: Proficiency with tools like Git, which are essential for collaborative development. What to Bring: Updated resume Photo ID, Passport size photo Mention "Aishwarya G" at the top of your resume. How to Register: To express your interest and confirm your participation, please reply to this email with your updated resume attached. Walk-ins are also welcome on the day of the event. This is an excellent opportunity to showcase your skills, network with industry professionals, and explore the exciting possibilities that await you at Hexaware Technologies. If you have any questions or require further information, please feel free to reach out to me at AISHWARYAG5@hexaware.com We look forward to meeting you and exploring the potential of having you as a valuable member of our team.

Roles and Responsibilities Design, develop, and deploy advanced AI models with a focus on generative AI, including transformer architectures (e.g., GPT, BERT, T5) and other deep learning models used for text, image, or multimodal generation. Work with extensive and complex datasets, performing tasks such as cleaning, preprocessing, and transforming data to meet quality and relevance standards for generative model training. Collaborate with cross-functional teams (e.g., product, engineering, data science) to identify project objectives and create solutions using generative AI tailored to business needs. Implement, fine-tune, and scale generative AI models in production environments, ensuring robust model performance and efficient resource utilization. Develop pipelines and frameworks for efficient data ingestion, model training, evaluation, and deployment, including A/B testing and monitoring of generative models in production. Stay informed about the latest advancements in generative AI research, techniques, and tools, applying new findings to improve model performance, usability, and scalability. Documentandcommunicatetechnicalspecifications, algorithms, and project outcomes to technical and non-technical stakeholders, with an emphasis on explainability and responsible AI practices. Qualifications Required Educational Background: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. Relevant Ph.D. or research experience in generative AI is a plus. Experience: 8-12 years of experience in machine learning, with 2+ years in designing and implementing generative AI models or working specifically with transformer-based models. Skills and Experience Required GenerativeAI: Transformer Models, GANs, VAEs, Text Generation, Image Generation Machine Learning: Algorithms, Deep Learning, Neural Networks Programming: Python, SQL; familiarity with libraries such as Hugging Face Transformers, PyTorch, Tensor Flow MLOps: Docker, Kubernetes, MLflow, Cloud Platforms (AWS, GCP, Azure) Data Engineering: Data Preprocessing, Feature Engineering, Data Cleaning

Required Skills: AWS Services: Proficiency in AWS services such as Lambda, API Gateway, ECS, EKS, DynamoDB, S3, and RDS, Glue, Redshift, EMR. Backend: Python (multithreading, Flask, FastAPI), NodeJS, ExpressJS, REST APIs Frontend: Angular, ReactJS, TypeScript Cloud Engineering : Development with AWS (Lambda, EC2, S3, API Gateway, DynamoDB), Docker, Git, etc. Proven experience in developing and deploying AI solutions with Python, JavaScript Strong background in machine learning, deep learning, and data modelling. Good to have: CI/CD pipelines, full-stack architecture, unit testing, API integration Security: Understanding of AWS security best practices, including IAM, KMS, and encryption. Observability Tools: Proficiency in using observability tools like AWS CloudWatch, AWS X-Ray, Prometheus, Grafana, and ELK Stack. Container Orchestration: Knowledge of container orchestration concepts and tools, including Kubernetes and Docker Swarm. Monitoring: Experience with monitoring and logging tools such as AWS CloudWatch, CloudTrail, or ELK Stack. Collaboration: Strong teamwork and communication skills with the ability to work effectively with cross-functional teams. Preferred Qualifications: Certifications: AWS Certified Solutions Architect Associate or Professional, AWS Certified Developer Associate, or similar certifications. Experience: At least 5 Years of experience in an application engineering role with a focus on AWS technologies. Agile Methodologies: Familiarity with Agile development practices and methodologies. Problem-Solving: Strong analytical skills with the ability to troubleshoot and resolve complex issues. Education: Degree: Bachelors degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience Your key responsibilities: Application Development: Design and develop cloud-native applications and services using AWS services such as Lambda, API Gateway, ECS, EKS, and DynamoDB, Glue, Redshift, EMR. Deployment and Automation: Implement CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy to automate application deployment and updates. Architecture Design: Collaborate with architects and other engineers to design scalable and secure application architectures on AWS. Performance Tuning: Monitor application performance and implement optimizations to enhance reliability, scalability, and efficiency. Security: Implement security best practices for AWS applications, including identity and access management (IAM), encryption, and secure coding practices. Container Services Management: Design and deploy containerized applications using AWS services such as Amazon ECS (Elastic Container Service), Amazon EKS (Elastic Kubernetes Service), and AWS Fargate. Configure and manage container orchestration, scaling, and deployment strategies. Optimize container performance and resource utilization by tuning settings and configurations. Application Observability: Implement and manage application observability tools such as AWS CloudWatch, AWS X-Ray, Prometheus, Grafana, and ELK Stack (Elasticsearch, Logstash, Kibana). Develop and configure monitoring, logging, and alerting systems to provide insights into application performance and health. Create dashboards and reports to visualize application metrics and logs for proactive monitoring and troubleshooting. Integration: Integrate AWS services with application components and external systems, ensuring smooth and efficient data flow. Troubleshooting: Diagnose and resolve issues related to application performance, availability, and reliability. Documentation: Create and maintain comprehensive documentation for application design, deployment processes, and configuration. What we offer EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations Argentina, China, India, the Philippines, Poland and the UK and with teams from all EY service lines, geographies and sectors, playing a vital role in the delivery of the EY growth strategy. From accountants to coders to advisory consultants, we offer a wide variety of fulfilling career opportunities that span all business disciplines. In GDS, you will collaborate with EY teams on exciting projects and work with well-known brands from across the globe. Well introduce you to an ever-expanding ecosystem of people, learning, skills and insights that will stay with you throughout your career. Continuous learning : Youll develop the mindset and skills to navigate whatever comes next. Success as defined by you: Well provide the tools and flexibility, so you can make a meaningful impact, your way. Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs. Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.

Position - AI Engineer As an AI Engineer, you will design, implement, and optimize machine learning models and AI systems to solve complex problems. You will work closely with cross-functional teams to integrate AI solutions into our products and services, ensuring scalability and efficiency. Key Responsibilities: Application Development: Design and develop AI-powered applications using state-of-the-art LLM models and generative AI techniques. Implement scalable solutions that integrate LLM-powered tools into existing workflows or standalone products. Model Optimization: Fine-tune pre-trained LLM models to meet specific application requirements. Optimize model performance for real-time and high-throughput environments. LLMOps Implementation: Develop and maintain pipelines for model deployment, monitoring, and retraining. Set up robust systems for model performance monitoring and diagnostics. Ensure reliable operations through analytics and insights into model behavior. Vector Databases and Data Management: Utilize vector databases for efficient storage and retrieval of embeddings. Integrate databases with LLM applications to enhance query and recommendation systems. Collaboration and Innovation: Work closely with cross-functional teams, including product managers, data scientists, and software engineers. Stay up-to-date with advancements in generative AI and LLM technologies to drive innovation. Skills and Experience 3+ years of experience in AI/ML development, with a focus on generative AI and LLMs. Proficiency in programming languages such as Python and frameworks like PyTorch or TensorFlow. Hands-on experience in fine-tuning and deploying LLM models (e.g., GPT, BERT, etc.). Familiarity with LLMOps practices, including pipeline automation, monitoring, and analytics. Experience with vector databases (e.g., Pinecone, Weaviate, or similar). Strong knowledge of natural language processing (NLP) and machine learning principles. You should certainly apply if: Understanding of MLOps principles and cloud platforms (AWS, GCP, Azure). Familiarity with prompt engineering and reinforcement learning from human feedback (RLHF). Experience in building real-time applications powered by generative AI. Knowledge of distributed systems and scalable architectures.

A senior developer having python exp, who has also worked as a Gen AI developer – 2-5 yrs exp and should have exp in production related deployments and Node.js is a plus.

Job Description : We are seeking a highly motivated and experienced ML Engineer/Data Scientist to join our growing ML/GenAI team. You will play a key role in designing, developing and productionalizing ML applications by evaluating models, training and/or fine tuning them. You will play a crucial role in developing Gen AI based solutions for our customers. As a senior member of the team, you will take ownership of projects, collaborating with engineers and stakeholders to ensure successful project delivery. What we're looking for: At least 3 years of experience in designing & building AI applications for customer and deploying them into production At least 5 years of Software engineering experience in building Secure, scalable and performant applications for customers. Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI. Design, develop, and operationalize existing ML models by fine tuning, personalizing it. Evaluate machine learning models and perform necessary tuning. Develop prompts that instruct LLM to generate relevant and accurate responses. Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation. Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance. Hands on customer experience with RAG solution or fine tuning of LLM model. Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools. Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment. Proven experience building and deploying machine learning models in production environments for real life applications Good understanding of natural language processing, computer vision or other deep learning techniques. Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain). Familiarity with Google Cloud or any other Cloud Platform and its machine learning services. Excellent communication, collaboration, and problem-solving skills.

Lead AI Engineer About the Role: We are seeking an experienced AI specialist with a strong Computer Science/Engineering background to design, develop, and deploy advanced Generative AI-based solutions. In this role, you will build intelligent AI agents, leverage graph-based RAG techniques, and ensure robust production deployments to solve complex challenges in the Architecture, Engineering, and Construction (AEC) domain. Key Responsibilities Collaborate with stakeholders to align AI initiatives with business goals. Lead and mentor a team of ML engineers and data scientists. Design, develop, and deploy enterprise-grade RAG systems that deliver accurate, context-aware responses in production environments. Incorporate AI agents and graph-based techniques (e.g., GraphRAG) to enable enhanced contextual data retrieval and support complex query relationships. Implement robust evaluation frameworks to measure and enhance RAG system effectiveness. Create scalable pipelines for document processing, embedding generation, and knowledge base management. Build monitoring systems to track performance, detect issues, and ensure RAG system reliability. Architect cloud-native solutions that can scale to handle enterprise document volumes and query loads. Explore and integrate cutting-edge techniques in Generative AI, including but not limited to model fine-tuning. Qualifications & Skills A strong foundation in Computer Science or Engineering with 5-10 years' experience in NLP, Computer Vision, Deep Learning, Machine Learning, or related field. Extensive experience with LLMs and related technologies (e.g., embedding models, vector databases, etc.). Proven expertise in developing production-grade RAG systems. Knowledge of graph-based RAG techniques (e.g., Graph RAG or alternatives). Proficiency in Python and familiarity with Generative AI frameworks such as Hugging Face, Lang Chain, Llama Index, Prompt flow, Auto Gen, etc. Hands-on experience with cloud-based AI deployments (Azure preferred). Experience in LLM fine-tuning and optimization (e.g., LoRA) is a plus. Exposure to multi-modal RAG systems and LLMOps frameworks. Familiarity with deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Tensorflow, etc.).

Education : Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related field. Experience : Minimum of 5-8 years of experience as a Solution Architect or in a similar technical leadership role. Proven expertise in Power Apps and Power BI with hands-on experience in building applications, dashboards, and reports. Strong experience in .NET Development (C#, ASP.NET) and designing enterprise-level solutions. In-depth knowledge of SharePoint (development, configuration, and customization). Solid understanding and hands-on experience with Generative AI technologies (ChatGPT, large language models, or AI-driven solutions). Proven experience in presales activities, including preparing and presenting proposals, responding to RFPs, and engaging with clients to understand their technical needs. Skills: Strong problem-solving and analytical skills with the ability to architect complex systems and solutions. Excellent understanding of system integration, APIs, cloud platforms (Azure preferred), and software development life cycles. Experience with enterprise-grade applications and scalability requirements. Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders. Ability to design and implement secure, high-performance solutions. Strong leadership and mentoring skills. Exceptional proposal writing and presentation skills. Certifications (Preferred): Microsoft Certified: Power Platform Solution Architect Expert Microsoft Certified: Azure Solutions Architect Expert Generative AI-related certifications (desirable) Location : - Bengaluru , Pune , Chennai , Mumbai , Remote

Job Summary: We are seeking a highly skilled Knowledge Engineer to join our team and play a key role in developing and implementing advanced knowledge management frameworks and solutions, enhanced with Generative AI (GenAI) capabilities The successful candidate will create, maintain, and evolve a robust knowledge infrastructure, leveraging AI to drive smarter knowledge solutions across our organization This role requires a strong foundation in knowledge management, a deep understanding of AI technologies, and an ability to innovate in solution delivery Key Responsibilities : Develop Knowledge Management Frameworks: Design, build, and implement comprehensive frameworks that capture, organize, and facilitate the sharing of knowledge across teams and departments Enable Knowledge Evolution with GenAI: Drive the evolution of knowledge repositories and management systems with generative AI capabilities, ensuring the system continuously learns and improves in response to user inputs and new information Create and Maintain Solution Banks: Establish and manage a repository of solution banks that can be utilized by teams to solve recurring challenges efficiently Develop processes to update and evolve these solution banks as knowledge and technology advance Collaborate with Cross-functional Teams: Work closely with stakeholders, including engineers, data scientists, and domain experts, to understand knowledge requirements, identify gaps, and continuously improve knowledge management solutions Ensure High-Quality Knowledge Assets: Create and maintain high standards for knowledge assets, ensuring they are accurate, accessible, and aligned with organizational goals Leverage Advanced AI Techniques: Apply AI/ML techniques, particularly GenAI, to enhance knowledge retrieval, classification, and recommendation processes, making knowledge systems more intuitive and user-centric Measure and Report on Knowledge System Effectiveness: Develop metrics to measure the effectiveness of knowledge systems and GenAI implementations, using these insights to drive improvements and maximize impact Qualifications : Educational Background: Bachelors degree in Engineering, Computer Science, or a related field Experience: Proven experience in knowledge engineering or knowledge management Expertise in designing and implementing knowledge management frameworks Strong understanding of AI, specifically GenAI technologies, and their application to knowledge evolution and management Familiarity with solution bank creation and maintenance processes Experience : Minimum of 3 years in a similar role is required; overall 5 years Skills : Proficiency in knowledge management tools and systems Strong analytical and problem-solving skills, with the ability to translate complex requirements into actionable solutions Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders Knowledge of AI and ML frameworks, libraries, and best practices Knowledge Engineer, Knowledge Management, Knowledge Frameworks, Generative AI, GenAI, Knowledge Infrastructure, AI Solutions, Solution Banks, Knowledge Repositories, AI/ML Techniques, Cross-functional Collaboration, Knowledge Assets, AI Technologies, Knowledge Retrieval, Knowledge Classification, Knowledge Recommendation, AI-driven Systems, Engineering, Computer Science, Knowledge Engineering, Knowledge Management Frameworks, GenAI Implementation, Solution Bank Maintenance, Analytical Skills, Problem-solving, Communication Skills, AI Frameworks, ML Frameworks, AI Libraries, Machine Learning, Knowledge Systems, Metrics Development, Continuous Improvement, User-centric Design, Knowledge Sharing, Technical Translation, Stakeholder Engagement, Innovation in AI Solutions, Knowledge Evolution

Role & responsibilities A Fraud Strategist focuses on defining the overall fraud prevention framework, policies, and strategies. Instead of building models, they use insights from data scientists to develop rules and strategies for approving or declining transactions. Key Responsibilities: Create fraud detection strategies based on insights from fraud models. Define policies to minimize fraud while maintaining a good customer experience. Decide on approval or decline criteria for transactions based on risk scores. Work closely with Data Scientists to improve fraud detection models. Defines fraud prevention policies Rule-based decision-making Decision Engines, Risk Frameworks Approves or declines transactions