525 Generative Ai Jobs - Page 21

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

Key Responsibilities: AI Research & Optimization: Stay updated with the latest AI models, optimize cloud/custom AI engines, and enhance model efficiency using techniques like quantization and pruning. Model Development & Deployment: Train, fine-tune, and deploy AI models using TensorFlow, PyTorch, and cloud AI services (AWS SageMaker, Azure ML, Google Vertex AI). Programming & Performance Tuning: Strong coding skills in Python, CUDA, and TensorRT for AI acceleration; experience with distributed computing (Spark, Ray). Cloud & MLOps Expertise: Hands-on with AI infrastructure, containerization (Docker, Kubernetes), and performance optimization for AI workloads. Problem-Solving & Research: Strong analytical skills, ability to explore emerging AI technologies, drive innovative AI-driven solutions, and publish research papers in AI/ML conferences or journals

ML/AL Gen AI Expert - Vertex AI on Google Cloud and MLOps . • GenAI tools & APIs with PaLM, Gemini, LLM ,Vertex Ai • Python Scripting scikit-learn, TensorFlow, PyTorch, LangChain. • GCP services •media domain (OTT, DTH, Web)

Greetings from idexcel technologies: Role & responsibilities We are seeking a Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT/Llama/Claude/Grok Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools – PyTorch, Sci-kit, NumPy, Gen AI tools like Lang chain/llama Index Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines

This role is for one of Weekday's clients Min Experience: 8 years Location: Bengaluru JobType: full-time About the Role As a Lead Gen AI Engineer in our Team, youll work closely with the Automation Delivery Director, Architects, Technical Lead and delivery squads in Designing and Building world class AI solutions within Automation Centre. You will be responsible for Solution Design, Development, Testing and deployment of AI initiatives by partnering with Operations, Technology and Vendor partners. Responsibilities: System Design and Architecture: Design optimised architectures for Gen AI and agent-based solutions at scale Develop and Integrate AI Models: Design, implement, and deploy generative AI models and Machine Learning solutions to meet specific business needs. Web API Development: Build, maintain, and document RESTful and GraphQL APIs for seamless integration of AI services with web and mobile applications using fastapi, Flask, etc Model Deployment and Monitoring: Implement, deploy, and monitor ML models on cloud platforms or on-premise environments using frameworks like TensorFlow, PyTorch, or Hugging Face. Experienced in Kubernetes Data Processing and Management: Preprocess large datasets, manage data pipelines, and optimize data storage for AI/ML applications. Collaborate with Cross-functional Teams: Work closely with data scientists, software engineers, and product managers to design scalable solutions and deploy AI-driven features. Optimize Code for Performance: Write clean, maintainable, and efficient Python code with an emphasis on scalability and performance. Research and Experimentation: Stay up-to-date with the latest trends in Generative AI, LLMs, and ML, and proactively experiment with new technologies to improve current processes. Mentorship and Leadership: Mentor junior engineers and provide guidance on best practices in AI/ML development. Must Haves: Education: Bachelors degree in computer science, Engineering, Mathematics, or a related field. A masters degree is a plus. Experience: 8+ years of professional experience 6+ years of Python experience Proven experience with productionising Generative AI based solutions Proven experience with Machine Learning frameworks like TensorFlow, PyTorch, or Hugging Face. Experience with Web APIs: RESTful API design, FastAPI, Flask/Django, and best practices for security and scalability. Cloud Platforms: Familiarity with AWS, GCP, or Azure for deploying and scaling ML models. Experience in Docker and containerised platforms Experience in RAG and finetuning of foundational models Skills Python: Advanced proficiency in Python, with a strong understanding of libraries such as NumPy, Pandas, and Scikit-Learn. ML/AI Tools: Hands-on experience with popular machine learning and deep learning frameworks like TensorFlow, PyTorch, and Keras. Generative AI: Solid understanding of generative model concepts like (e.g., GPT, GANs, VAEs, and transformers). Knowledge of text and image generation models, fine-tuning, and prompt engineering. Experience in langchain. API Development: Skilled in designing, developing, and consuming APIs for real-time data processing and integration with other services. Data Engineering: Proficiency in data preprocessing, feature engineering, and working with large datasets. Deployment: Experience with Docker, Kubernetes, or serverless architectures for model deployment and scalability. Version Control: Git, GitHub, or Bitbucket.

Role: Lead Engineer Exp.: 3-4 Years Education: BE/B.Tech in Computer Science/IT/ Electronics from reputed Institute Job Details: We are seeking a talented and driven AI Engineer with 3-4 years of experience to lead the development of cutting-edge AI solutions. In this role, you will work on solving complex NLP problems, building AI-powered applications like chatbots, ranking systems, and recommendation engines, and driving end-to-end machine learning projects. You will collaborate with cross-functional teams to deliver scalable, production-ready AI systems that address real-world challenges. Requirements: Strong programming skills in Python, Spark. 3-4 years of experience in Machine Learning, Generative AI, and NLP. Hands-on experience with Generative AI, Machine Learning, and NLP Expertise in prompt engineering, result evaluation, and iterative model fine-tuning. Experience building microservices powered by databases like MySQL or MongoDB. Familiarity with RAG pipelines and deploying AI models in production environments. Proven ability to analyze and refine AI/ML approaches based on performance metrics. Responsibilities: Solve real-world NLP problems using Generative AI and traditional Machine Learning techniques. Build AI-powered applications such as chatbots, ranking systems, and recommendation engines. Design and deploy end-to-end ML pipelines, including prototyping, prompt tuning, result analysis, and iterative fine-tuning. Develop and deploy microservices integrated with databases (e.g., MySQL, MongoDB) to support AI-driven solutions. Implement and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced AI capabilities. Collaborate with product and application teams to understand use cases and deliver tailored solutions. • Ensure seamless integration of AI/ML models into production systems with scalability and reliability. Desired Skills: Experience with Elasticsearch and building search systems (not mandatory). Experience with cloud platforms such as AWS, GCP, or Azure. • Familiarity with containerization tools like Docker and orchestration tools like Kubernetes. Strong understanding of software engineering best practices and scalable system design. Why Join us: This is a unique opportunity to work on innovative and disruptive technologies that are shaping the future of the industry. We are looking for candidates who are willing to work passionately in a fast- paced environment and are ready to enhance their skills by learning something new. Being a part of the InfoEdge team, you will be engaged in innovations, product development, integration with mobile and social media, technology, research and development, quality assurance, sales and marketing. To learn more about Info Edge visit http://www.infoedge.in/ Connect with me: Prince Narag (https://www.linkedin.com/in/princenarang/)

Job purpose: Work on machine learning and generative AI models that power Rootle's voice and chat platforms. Who You Are: A passionate Machine Learning Engineer with 1-2 years of experience to help us build cutting-edge AI systems. Strong Python programming skills with experience in ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) Hands-on experience in NLP techniques and frameworks like Hugging Face Transformers. Understanding of model evaluation techniques and ML fundamentals. Familiarity with version control (Git) and collaborative workflows Key Responsibilities: Develop and fine-tune machine learning and generative AI models (including LLMs) for NLP and conversation tasks. Design scalable training and inference pipelines using modern ML frameworks. Collaborate with product and engineering teams to integrate models into customer-facing systems. Conduct experiments, evaluate model performance, and iterate based on feedback and metrics. Stay current with the latest research in Gen AI, NLP, and ML, and apply innovations to production. What will excite us: Experience working with Large Language Models (e.g., GPT, LLaMA, Mistral) and prompt engineering. Exposure to vector stores (FAISS, Pinecone) and embeddings. Familiarity with tools like LangChain, FastAPI, or Docker. Experience with model deployment and serving on cloud platforms (AWS, GCP, etc.). Background in conversational AI, voice bots, or chatbot platforms is a plus. What will excite you: In-office opportunity in Ahmedabad with a collaborative and AI-focused team. Work on innovative Gen AI projects with real-world impact. Mentorship, growth opportunities, and hands-on exposure to production-scale AI systems. Location: Ahmedabad

Significant experience in Python programming, machine learning, deep learning, generative AI and hands-on in latest Gen AI models. Deep understanding of OCR technologies will be highly advantageous. Familiarity with AWS cloud services is recommended.

Dear Candidate, Greetings from IDEXCEL Technologies!! Please find the employment opportunity with I dexcel, Designation: GenAI Engineer Company Name: IDEXCEL technologies, Full Time. Experience: 5+ Years Notice Period: immediate to 20 Days Work Mode: Work From Office( 5 Days in a week) Interview Mode: Only one Round (F2F) Work Locations: Bengaluru, Hyderabad (Yellareddy Guda) Please go through the attachment for job description. Generative AI Engineer Idexcel is seeking a Senior Engineer to join our Enterprise GenAI Engineering Organization and be a key part of the Enterprise GenAI tech team. As a GenAI engineer, you will lead the development cutting-edge generative artificial intelligence solutions using large language models, agentic frameworks, retrieval augmented generation and other innovative technologies. The ideal candidate will have experience in designing, developing, and deploying applications leveraging LLM models and systems, with a strong focus on prompt engineering, RAG implementations, evaluations and agentic frameworks. In this role, you will: Design, develop, deploy GenAI applications using LM's, agent framework and related technologies Collaborate with and/or embed with line of business team teams to create reusable components and frameworks to accelerate the delivery of GenAI solutions Develop and maintain large-scale applications using Java, Python and other relevant technologies (e.g., cloud technologies, containerization, etc) Develop reference services that can be leveraged enterprise-wide such as document parsing, synthetic data generation, summarization and deep research Stay up to date with the latest advancements in GenAI, LLM, agentic frameworks and drive innovation to improve existing systems and develop new ones Troubleshoot and resolve complex technical issues related to applicationsand models Develop GenAI observability solutions to ensure systems are monitored to increase operational efficiency and managed to mitigate risk Resolve coding, testing and escalated platform issues of a technically challenging nature Collaborate with the team to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives Collaborate and influence all levels of professionals including managers Required Qualifications: 5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 5+ years of experience in software development 5+ years of Python, JavaScript or Java and other relevant technologies 1+ years of Experience with SDLC and Agile tools such as JIRA, GitHub, Jenkins, Confluence etc. Desired Qualifications: 1+ year of GenAI and ML concepts, including Evaluations, Fine Tuning and Prompt engineering Knowledge agentic design patterns Prompt Engineering concepts such as Zero-Shot, Few-shot, self-consistency and chain of thought prompting Note : We are looking for Immediate Joiners and if interested please share your updated Cv following mail ID : blikhith@idexcel.com

Senior Generative AI Engineer We are seeking a highly skilled and motivated Senior Generative AI Engineer to join our growing AI team. In this role, you will be instrumental in designing, developing, fine-tuning, and deploying cutting-edge generative AI models and applications. You will work on challenging projects, leveraging state-of-the-art techniques like Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal approaches to solve real-world problems. If you have a passion for building intelligent systems and staying at the forefront of AI advancements, we want to hear from you. Responsibilities : • Design, implement, and optimize sophisticated generative AI models (LLMs, diffusion models, transformers, etc.) for various applications. • Develop and refine techniques for fine-tuning pre-trained models on domain-specific datasets to enhance performance and relevance. • Implement and iterate on advanced Retrieval-Augmented Generation (RAG) systems, including selecting appropriate vector databases, optimizing embedding strategies, and refining retrieval/generation pipelines. • Engineer effective prompts and interaction strategies for maximizing the capabilities of generative models. • Process and prepare large datasets for training and fine-tuning generative models. • Evaluate model performance rigorously using appropriate metrics and benchmarks, focusing on accuracy, relevance, safety, and efficiency. • Collaborate with data scientists, software engineers, MLOps engineers, and product managers to integrate generative AI capabilities into products and services. • Optimize models and algorithms for efficient training and inference on cloud platforms (AWS, GCP, Azure). Job Opening • Contribute to the team's MLOps practices by versioning models/data, containerizing applications (e.g., Docker), and deploying models via established CI/CD pipelines. • Stay current with the latest research papers, open-source projects, and industry trends in generative AI, RAG, and related fields. • Troubleshoot and debug complex issues in AI models and systems. • Potentially mentor junior engineers and contribute to internal knowledge sharing. Qualifications : • Typically, 5+ years of professional experience in software engineering or machine learning, with at least 2-3 years of focused, hands-on experience building and implementing Generative AI models and systems. • Strong understanding of the fundamentals of deep learning, natural language processing (NLP), and machine learning principles. • Proven experience working with major generative AI model architectures (e.g., Transformers, GANs, VAEs, Diffusion Models) and foundational models (e.g., GPT series, Llama series, Stable Diffusion). • Hands-on experience with fine-tuning large pre-trained models. • Practical experience implementing RAG pipelines, including familiarity with vector databases (e.g., Pinecone, Weaviate, Milvus, ChromaDB, FAISS) and embedding techniques. • Expert-level programming skills in Python. • Proficiency with major AI/ML frameworks such as PyTorch or TensorFlow/Keras, and libraries within the ecosystem (e.g., Hugging Face Transformers, LangChain, LlamaIndex). • Experience using cloud platforms (AWS, GCP, or Azure) for developing, training, and deploying machine learning models (e.g., using services like SageMaker, Vertex AI, Azure ML). • Strong analytical and problem-solving skills. • Excellent communication and collaboration skills. Preferred Qualifications : • • Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. • • Experience with multimodal generative models (text-to-image, image-to-text, etc.). • • Familiarity with Reinforcement Learning from Human Feedback (RLHF) concepts or implementation. • • Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, DVC). • • Experience with distributed training frameworks (e.g., DeepSpeed, PyTorch Distributed). • • Experience deploying models into production using containerization (Docker, Kubernetes) and API frameworks (e.g., FastAPI, Flask). • • Contributions to open-source AI/ML projects or publications in relevant conferences/journals

Role & responsibilities Urgent Hiring for one of the reputed MNC Immediate joiners Only Females Bang / Pune / Hyd Exp - 4 - 12 Years Job Description: Senior Data Scientist - Multi-Agent AI Systems About the Role We are seeking an exceptional Data Scientist with specialized expertise in developing multi-agent AI systems. In this role, you will design, implement, and optimize complex AI ecosystems where multiple intelligent agents collaborate to solve sophisticated problems. You will leverage your deep understanding of generative AI, retrieval-augmented generation (RAG), and prompt engineering to create cutting-edge solutions that push the boundaries of artificial intelligence. Key Responsibilities Design and develop generative AI-based multi-agent systems that can collaborate, communicate, and coordinate to achieve complex objectives Architect and implement RAG-based chatbot solutions that effectively leverage knowledge bases and external data sources Create sophisticated prompt engineering strategies to optimize AI agent behavior and inter-agent communication Build, train, and fine-tune generative AI models for various applications within multi-agent systems Develop robust evaluation frameworks to measure and improve multi-agent system performance Implement efficient knowledge sharing mechanisms between AI agents Write clean, efficient, and well-documented Python code for production-ready AI systems Collaborate with cross-functional teams to integrate multi-agent systems into broader product ecosystems Stay at the forefront of AI research and incorporate state-of-the-art techniques into our solutions Required Qualifications Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field 4+ years of professional experience in data science or machine learning engineering Extensive experience with Python programming and related data science/ML libraries Demonstrated expertise in developing and deploying generative AI models (e.g., LLMs, diffusion models) Proven experience building RAG-based systems and implementing vector databases Strong background in prompt engineering for large language models Experience designing and implementing generative AI-based multi-agent architectures Excellent problem-solving skills and ability to optimize complex AI systems Preferred candidate profile Experience with LangChain, AutoGPT, CrewAI, or similar frameworks for building agent-based systems Familiarity with orchestration tools for managing complex AI workflows Knowledge of agent communication protocols and collaborative problem-solving frameworks Experience with distributed systems and cloud computing platforms (AWS, GCP, Azure) Contributions to open-source AI projects or research publications in relevant fields Experience with knowledge graphs and semantic reasoning systems Familiarity with MLOps practices and deployment of AI systems at scale

Job purpose: Design, evaluate, and refine prompts to guide LLMs in producing accurate, relevant, and high-quality outputs for real-world applications such as voice bots, chatbots, and automation flows. Who You Are: Minimum of 2-4 years of experience working with or around Large Language Models or similar Generative AI technologies. Hands-on experience working with LLMs using OpenAI, Hugging Face, or similar platforms. Basic understanding of Python and ability to write prompt-related scripts. Familiarity with prompt evaluation frameworks and performance metrics. Key Responsibilities: Design and engineer effective prompts for use with LLMs (e.g., GPT, Claude, Mistral). Analyze model behavior and refine prompts for accuracy, relevance, and efficiency. Collaborate with product, engineering, and ML teams to integrate prompt logic into production systems. Conduct testing and evaluation of prompts across multiple tasks and domains. Research and experiment with techniques such as few-shot, zero-shot, and chain-of-thought prompting. What will excite us: Experience using LangChain or other LLM orchestration tools. Understanding of embeddings, vector databases, and semantic search. Prior experience building chatbot or GenAI applications. Awareness of model behavior limitations, hallucination risks, and mitigation strategies. What will excite you: In-office opportunity in Ahmedabad with a collaborative and AI-focused team. Work on innovative Gen AI projects with real-world impact. Exposure to production-level LLM deployment and prompt optimization at scale. Location: Ahmedabad

Dear Candidates, We are currently seeking passionate and talented BTech freshers specializing in Computer Science (CSc(Any)) to join our team as Generative AI Trainee & Developer position . This is an excellent opportunity to work at the forefront of artificial intelligence and contribute to cutting-edge projects. Eligibility Criteria: Academic qualification: BTech (CSc) with a minimum of 70% aggregate . Strong communication skills are essential. Knowledge or interest in AI and related technologies is a plus. Role Highlights: Hands-on training in generative AI technologies. Exposure to real-world AI development projects. Opportunity to learn, grow, and innovate in a dynamic and supportive environment. If you are interested or know someone who meets the criteria and is eager to embark on an exciting journey in the AI domain, please send your updated CV to Suneeta.m@aciinfotech.com with the subject line Application for Generative AI Trainee & Developer.” We look forward to welcoming aspiring professionals into our team and shaping the future of AI together!

Job Title: Director, Analytics Experience: 10+ Yrs Job Location: Remote, India Company Overview: At Ensemble Health Partners, we're at the forefront of innovation, leveraging cutting-edge technology to drive meaningful impact in the Revenue Cycle Management landscape. Our commitment to excellence is unwavering, and we're seeking a seasoned Principal Azure Cloud Architect to join our dynamic team. As a leading player in the industry, we offer an environment that fosters growth, creativity, and collaboration, where your expertise will be valued and your contributions will make a difference. Position Overview: The AI solutions architect is responsible for building AI and Machine learning models and pipelines, with a focus on generative AI, LLMs and predictive modeling. The successful candidate will work closely with business owners to understand their data requirements and product specifications to help them make data-related decisions and product design choices. The role will also require close work with data scientists, software engineers and developers to deliver solutions. Another crucial part will be defining the strategic priorities for AI and GenAI development across the company and educating both technical and business teams about the latest developments in AI. The job role may also require you to learn new tools and technologies fast, which will be well supported by in-depth ML/AI knowledge as well as basic programming and scripting skills. You should have expertise in the design, development, management, and maintenance of systems and handling of large datasets. You should have hands-on experience with common machine learning and AI frameworks, and a good knowledge of AI and machine learning fundamentals (deep learning, regression, classification and clustering algorithms), retrieval augmented generation pipelines, as well as a good grasp of the design and evaluation of LLM-supported use cases. Roles & Responsibilities Design, develop, and oversee the implementation of end-to-end AI solutions, including LLM-based and general machine learning use cases. Define AI solution objectives and ensure alignment with business outcomes Develop and ensure Interoperability between client systems, internal teams and other third-party vendors. Educate team members and bring both technical staff and business stakeholders up to speed with recent AI trends. Present key findings, recommend enhancements, and work with business owners to enhance product development. Evaluate predictive models as well as LLM-based technologies at scale. Act as primary respondent to questions regarding AI and Machine Learning applications. Build, enhance and maintain the data models, interfaces and application integration required to support growing and changing business needs. Collaborate with internal and external clients to respond to growing needs of the business, troubleshoot issues, and expand capabilities of the product. Meaningfully contribute to the strategic direction of AI initiatives within the company Required Skills Overall 12+ Years out of which 5+ years' experience leading a data science/machine learning team with clear deployment experience. PhD or MSc in Computer Science/Machine Learning/AI, or related work experience with the design, building and evaluation of Machine Learning systems. 5+ years experience with Machine Learning ecosystem tools, including pytorch/tensorflow, scikit-learn, xgboost or equivalents. Proven ability to research and execute solutions based on novel algorithms and machine learning tooling. Ability to design, implement, test and deploy Machine Learning models. Experience working with and evaluating LLM-based pipeline, with an emphasis on retrieval augmented generation and prompting techniques is a plus. Familiarity with langchain/llamaindex/haystack/Azure AI studio, vector databases and retrieval techniques, or equivalent common tools in the emerging LLM-enabled tech stack is a plus. Proficiency in accessing and handling databases via SQL, Azure Data Factory or similar. Alternatively, familiarity with data storage/management systems or Big Data frameworks (like Hadoop, Spark) expected to be known or used. Proficiency in Software Development best practices such as Continuous Integration, Unit/Integration Testing, Code Reviews. Understanding of MLOps fundamentals, including orchestration tools, cloud compute, and observability tools. Proven ability to read research papers, critique and execute based on them. Knowledge of Revenue Cycle Management, Collections, or financial industries is desirable but not necessary. Ability to work both independently and in a team-based, fast-paced environment. Excellent communication skills, both written and verbal. Why Join US? We adapt emerging technologies to practical uses to deliver concrete solutions that bring maximum impact to providers bottom line. We currently have 10 Technology Patents in our name. We offer you a great organization to work for, where you will get to do best work of your career and grow with the team that is shaping the future of Revenue Cycle Management. We have our strong focus on Learning and development. We have the best Industry standard professional development policies to support the learning goals of our associates. We have flexible/ remote working/ working from home options Perks Health Benefits and Insurance Coverage for family and parents. Accidental Insurance for the associate. Compliant with all Labor Laws- Maternity benefits, Paternity Leaves. Company Swags- Welcome Packages, Work Anniversary Kits Exclusive Referral Policy Professional Development Program and Reimbursements. Remote work flexibility to work from home. Join Our Team: If you're passionate about cloud technology and eager to make a meaningful impact in a dynamic and collaborative environment, we want to hear from you! Join us at Ensemble Health Partners and be part of a team that's shaping the future of Revenue Cycle Management. Apply now and embark on a rewarding journey of innovation and growth.

Role & responsibilities Data Science Exp Exp in Machine Learning - 3 - 4 projects Excellent in Python Coding Exp in Time series forecasting Mandate Gen AI - 6 month exp mandate Only Bangalore based candidates to reply as this will be F2F Interview. Preferred candidate profile

Exp - 6- 10 Years Level - Senior Consultant Skill - ML OPS with Gen AI Location - Bengaluru Event on 9th May in Bangalore location Hybrid Mode (2 days WFO in a week) Education - B.Tech/B.E/MS/MBA ML OPs Engineer Required: 6-10 years of Consulting, Data, and Analytics experience Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production. Strong knowledge of Python or R Programming experience with Node.js, SQL, Java, JavaScript OR PERL Experience in cloud-based data platforms on AWS, GCP and Azure Understanding of multi-tier application architectures Ability to develop, test and maintain programming environments and architectural standards Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket) Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo Experience on code quality assessment tools and integration with CI tool Strong logical structuring and problem-solving skills Strong verbal, written and presentation skills Preferred Additional Experience in using Spark either with Scala or Python Experience with different database types like RDS and NoSQL Experience in cloud deployments Knowledge of working in a Linux environment Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS Experience in Docker /Swarm / Kubernetes Experience or exposure to Test Driven Development Experience (Junit / TestNG) Experience on Behavior Driven Development Experience (Cucumber / Selenium) Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI Experience with real time data movement solutions that use security and encryption protocols while data is in transit

Role & responsibilities Java SpringBoot + Automation architect 10-14 yrs of IT experience - Worked on Java / J2EE architecture & design - especially on Springboot, microservices, Cloud Exposure to Automation / GenAI as well Needs exposure to automation either RPA or script based (Python, etc). Good-to-have: Know-how / exposure to GenAI in their own areas of work would . Worked on DevOps CI/CD tooling Good at learning new concepts & doing POCs/pilots, ready to learn and experiment on cutting-edge technology Good at logical & lateral thinking Good at communication & presentation skills Preferred candidate profile 10+ Years exp in Java ava / J2EE architecture & design, Springboot, Microservices, Cloud and experience in Gen AI/Python/RPA