217 Llms Jobs - Page 5

Job Title: Data Engineer & Gen AI Engineer Project Duration- 6 months Exp- 4-7 yrs Location : Bangalore (Hybrid) Budget : upto 19 LPA Required Skills & Qualifications: python, Lang chain, Azure Databricks, data quality, PySpark, SQL, & Delta Lake

About us Exotel is one of Asias largest cloud telephony companies. Our aim is to change the way enterprises look at customer communication. We build the best-in-class communication products that power the companies of today and tomorrow. Our technology enables customer communication for our clients such as Uber, Ola, Go-Jek, ICICI, IDFC, Redbus, Flipkart, Quikr, Practo, Lazada, Redmart, etc. to name a few. We are a 9-year-old company with humble beginnings. We started as a 3-member team. Currently, we are a 120-member team catering to over 3000 customers across the globe. Our technology has connected over 400 million people across the world and powered over 10 billion conversations. Read our growth story here. Tech @ Exotel Exotel Engineering solves some really cool infrastructure-level problems with the goal of ensuring no one misses a call or an SMS. Our focus is on building a very fault-tolerant, loosely coupled, scalable and real-time distributed system We are generally agnostic of language, technology or tools. Currently, our tech stack is built on Golang, Node.js, Ruby, Java and PHP. We use Aerospike, and MySQL as data stores, ElasticSearch for search and Beanstalkd for queuing We emphasize a lot on clean abstractions of code, loosely coupled services and good coding practices We are very strong believers in "you built it, you own it!". And running a distributed system is very different from just building one! We are crazy about high availability What are we looking for? We are looking for candidates with strong programming skills, and a strong understanding of computer/distributed systems. We want people who love designing and building infrastructure components and large complex services. Being a Software Engineer at Exotel takes a bit more than the following Must-haves Bachelor's or Master's degree in computer science or equivalent. Experience working with major cloud solutions AWS (preferred), Azure, and GCP. Familiarity with 3-Tier, microservices architecture and distributed systems Experience with the design & development of RESTful services Experience with developing Linux-based applications, networking and scripting. Experience with different data stores, data modelling and scaling them Familiarity with data stores such as Aerospike, MySQL, Mongo-db etc. 3 to 5 years of experience with Python, Gen AI, Agentic AI, building dedicated chatbots, RAG, LLMs Good understanding of data structures, multi-threading and concurrency concepts. Experience with DevOps tools like Jenkins, Ansible, Kubernetes, Git is a plus. Familiarity with elasticsearch queries and visualization tools like grafana, kibana Strong networking fundamentals: Firewalls, Proxies, DNS, Loadbalancing, etc. Strong analytical and problem-solving skills. Excellent written and verbal communication skills. Team player, flexible, and able to work in a fast-paced environment. A "devops" mindset. You own what you will develop. Other expectations: Willingness to explore and learn new technologies on the Job Take end-to-end ownership of software development lifecycle in a DevOps as a culture setting: Design, Development, Deployment and Monitoring Independently deliver software work products by working with stakeholders(PMs, Architects and team leads)

We are urgently looking for an experienced Generative AI Trainer to join our institute and drive excellence in training. Require solid expertise in AI/ML, NLP, and Generative AI (LLMs, LangChain, Transformers, RAG, etc) Send CV at rathij91@gmail.com Required Candidate profile Conduct online & offline classes. Provide proxy interviews & technical support to help students get placed. Prepare assessments, track performance & guide for certifications.

Hiring a Senior GenAI Engineer with 7-12 years of experience in Python, Machine Learning, and Large Language Models (LLMs) for a 6-month engagement based in Gurugram This hands-on role involves building intelligent systems using Langchain and RAG, developing agent workflows, and defining technical roadmaps The ideal candidate will be proficient in LLM architecture, prompt engineering, vector databases, and cloud platforms (AWS, Azure, GCP) The position demands strong collaboration skills, a system design mindset, and a focus on production-grade AI/ML solutions

Job Description: Data Science Trainer We're seeking a committed Technical Data Science Trainer to join us in delivering the next generation of AI technical training. This is not just a job - it's an opportunity to play a key role in empowering the next generation of AI/ML professionals, influencing their careers and contributing to the growing AI ecosystem. The role also helps get recognized as a leader in the AI training space while expanding your personal and professional brand This role is ideal for someone passionate about both teaching and technology, capable of helping learners become skilled professionals in AI and related fields. Skills: AI, Machine Learning, Python, Numpy, Pandas, R Programming, Statistics, Computer Vision, Natural Language Processing, LLMs, Tableau, Power BI Essential Qualifications: B.Tech., M.Tech., MCA or equivalent experience 2 - 6 years' of experience Expertise Required: Technical Expertise: Proficient in AI, ML, Deep Learning, LLMs, Computer Vision, and Python. Tools and Frameworks: Hands-on experience with TensorFlow, PyTorch, Scikit-learn, OpenCV, Hugging Face, NumPy, Pandas, Matplotlib, Seaborn, and R Programming. Communication: Strong ability to explain technical concepts in simple terms and provide clear instructions. Problem-Solving: Ability to debug code, identify errors, and explain solutions effectively. Key Responsibilities: Training Delivery: Design and deliver training programs and workshops for individuals and teams on AI, ML, Deep Learning, LLMs, Computer Vision, and Python programming. Adapt training methods to suit varying levels of expertise, from beginner to advanced learners. Curriculum Development: Develop structured, up-to-date course materials, including slide decks, coding exercises, case studies, and hands-on projects. Incorporate real-world applications and industry best practices into the curriculum for a practical learning experience. Regularly update course content to align with advancements in technology and industry trends. Hands-On Learning: Guide learners through practical exercises, coding labs, and project-based learning to ensure hands-on experience with tools, frameworks, and algorithms. Provide training on key frameworks and tools such as TensorFlow, PyTorch, OpenCV, Hugging Face, Scikit-learn, and Pandas. Mentorship and Support: Offer one-on-one mentorship to learners, addressing individual doubts and helping them troubleshoot complex problems. Monitor learners progress, provide constructive feedback, and suggest improvement strategies. Assessment and Evaluation: Develop and administer assessments to evaluate learners understanding and skill levels. Analyze test results and provide detailed performance feedback. Domain-Specific Expertise: Explain and demonstrate key AI/ML concepts, such as supervised and unsupervised learning, reinforcement learning, natural language processing (NLP), and computer vision techniques. Guide learners in working with large language models (LLMs) like GPT and BERT, focusing on fine-tuning and deployment. Train learners on deep learning topics, including neural networks, CNNs, RNNs, and transformers. Stay Updated on Trends: Continuously research advancements in AI, ML, Deep Learning, and Python, incorporating cutting-edge techniques into the training materials. Maintain familiarity with emerging technologies like generative AI and explainable AI. Soft Skills and Collaboration: Communicate complex concepts clearly to learners from diverse technical and non-technical backgrounds. Foster an engaging and interactive learning environment, encouraging collaboration among participants. What We Offer Be part of cutting-edge AI projects and work on real-world applications of Machine Learning, Deep Learning, Large Language Models (LLMs), and Computer Vision. Opportunity to stay ahead in the AI revolution by working with the latest tools and technologies like TensorFlow, PyTorch, OpenCV, and Hugging Face. Access to continuous learning resources and mentorship programs to sharpen your expertise and stay updated with emerging trends. Build leadership and communication skills by mentoring learners and engaging with professionals across various industries. Connect with industry experts, aspiring AI professionals, and innovators, giving you a strong professional network. Grow with the company! Be part of our exciting journey as we expand and make an impact in the AI training industry. Enjoy early access to leadership opportunities and the chance to shape the companys future direction. Our Culture & Values Startup Culture - Fast-Paced, Collaborative, and Innovative A place for growth. We believe in nurturing talent and giving everyone the chance to grow professionally and personally We work as a team, supporting and learning from each other. Every voice matters here We trust our team to take ownership of their work and make meaningful contributions. Dynamic startup energy Collaborative leadership Continuous learning

We Advantum Health Pvt. Ltd - US Healthcare MNC looking for Senior AI/ML Engineer. We Advantum Health Private Limited is a leading RCM and Medical Coding company, operating since 2013. Our Head Office is located in Hyderabad, with branch operations in Chennai and Noida. We are proud to be a Great Place to Work certified organization and a recipient of the Telangana Best Employer Award. Our office spans 35,000 sq. ft. in Cyber Gateway, Hitech City, Hyderabad Job Title: Senior AI/ML Engineer Location: Hitech City, Hyderabad, India Work from office Ph: 9177078628, 7382307530, 9059683624 Address: Advantum Health Private Limited, Cyber gateway, Block C, 4th floor Hitech City, Hyderabad. Location: https://www.google.com/maps/place/Advantum+Health+India/@17.4469674,78.3747158,289m/data=!3m2!1e3!5s0x3bcb93e01f1bbe71:0x694a7f60f2062a1!4m6!3m5!1s0x3bcb930059ea66d1:0x5f2dcd85862cf8be!8m2!3d17.4467126!4d78.3767566!16s%2Fg%2F11whflplxg?entry=ttu&g_ep=EgoyMDI1MDMxNi4wIKXMDSoASAFQAw%3D%3D Job Summary: We are seeking an experienced and innovative AI Technical Lead to drive the design, development, and deployment of AI-powered solutions across our organization. You will be responsible for leading a team of machine learning engineers, data scientists, and software developers, while collaborating with cross-functional teams to build scalable and intelligent products. Your role will blend hands-on technical expertise with leadership and strategic thinking Key Responsibilities: Lead the end-to-end technical delivery of AI/ML projects, from data ingestion to model deployment. Design robust machine learning and deep learning models tailored to business needs. Collaborate with product managers, stakeholders, and engineering teams to identify opportunities for AI applications. Guide and mentor AI/ML engineers and developers; provide architectural and technical direction. Establish best practices for model training, validation, versioning, and monitoring. Ensure scalability, performance, and security of AI solutions in production environments. Stay up to date with the latest AI trends, tools, and research; apply innovations where appropriate. Review and approve technical design documents, code, and model performance metrics. Required Skills and Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 5+ years of experience in software development, with at least 2+ years in leading AI/ML teams or projects. Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience deploying models in production using platforms like AWS SageMaker, Azure ML, or Google Vertex AI. Solid understanding of data structures, algorithms, and software design principles. Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). Excellent communication skills with the ability to articulate complex concepts to non-technical stakeholders. Preferred Qualifications: Experience with LLMs, generative AI, or computer vision. Background in big data technologies (e.g., Spark, Hadoop). Published research or contributions to open-source AI projects. Experience in regulated industries (e.g., healthcare, finance) is a plus. Follow us on LinkedIn, Facebook, Instagram, Youtube and Threads for all updates: Advantum Health Linkedin Page: https://www.linkedin.com/showcase/advantum-health-india/ Advantum Health Facebook Page: https://www.facebook.com/profile.php?id=61564435551477 Advantum Health Instagram Page: https://www.instagram.com/reel/DCXISlIO2os/?igsh=dHd3czVtc3Fyb2hk Advantum Health India Youtube link: https://youtube.com/@advantumhealthindia-rcmandcodi?si=265M1T2IF0gF-oF1 Advantum Health Threads link: https://www.threads.net/@advantum.health.india HR Dept, Advantum Health Pvt Ltd Cybergateway, Block C, Hitech City, Hyderabad Ph: 9177078628, 7382307530, 9059683624

Role Overview: We are looking for a ML/AI Gen AI Expert with 4-7 years of experience for executing AI/GenAI use cases as POCs . Media domain experience (OTT, DTH, Web) is a plus. Key Responsibilities: Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders. Design, develop, and deploy models (ML and GenAI) using Google Clouds Vertex AI platform. Fine-tune and evaluate LLMs for domain-specific applications, ensuring responsible AI practices. Collaborate with data engineers and architects to ensure robust, scalable, and secure data pipelines feeding ML models. Document solutions, workflows, and experiments to support reproducibility, transparency, and handover readiness. Core Skills: Strong foundation in machine learning and deep learning, including supervised, unsupervised, and reinforcement learning. Hands-on experience with Vertex AI, including AutoML, Pipelines, Model Registry, and Generative AI Studio. Experience with LLMs and GenAI workflows, including prompt engineering, tuning, and evaluation. Python and ML frameworks proficiency (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). Strong collaboration and communication skills to work cross-functionally with data, product, and business teams. Technical Skills: Vertex AI on Google Cloud Model training, deployment, endpoint management, and MLOps tooling. GenAI tools and APIs Hands-on with PaLM, Gemini, or other large language models via Vertex AI or open source. Python Proficient in scripting ML pipelines, data preprocessing, and model evaluation. ML/GenAI Libraries scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain. Cloud & DevOps Experience with GCP services (BigQuery, Cloud Functions, Cloud Storage), CI/CD for ML, and containerization (Docker/Kubernetes) Experience in the media domain (OTT, DTH, Web) and handling large-scale media datasets. Immediate Joiners.

We are looking for Immediate Joiner for below position AI Engineer Exp 4 to 6 Location -Pune Primary Skill – Python Design and build AI-powered applications such as intelligent agents, chatbots, and domain-specific copilots using LLMs. Work with LLMs (OpenAI, Cohere, Hugging Face, etc.) and integrate them via APIs or custom pipelines. Create semantic search experiences using embedding generation and chunking strategies for enterprise documents. Implement RAG (Retrieval-Augmented Generation) pipelines using Vector Databases like Pinecone , Weaviate , FAISS , or Chroma . Build and expose REST APIs using FastAPI , Flask , or Django , integrating LLM and retrieval components. Manage and optimize backend systems using PostgreSQL , MongoDB , and Redis . Collaborate with AI/ML engineers, data engineers, and product teams to translate BFSI requirements into working solutions. Apply best practices in API security, caching, observability, and scaling for AI apps. Required Skills & Experience: 4–6 years of backend development experience with Python 3.x . Proficiency with web frameworks like FastAPI , Django , or Flask . Strong experience with PostgreSQL , MongoDB , and Redis . Solid understanding of LLM-based applications – prompt engineering, chat workflows, and model fine-tuning/inference (preferred). Experience with creating embeddings , chunking text, and building semantic search pipelines. Familiarity with Vector DBs like Pinecone , Weaviate , Chroma , or FAISS . Ability to implement or contribute to RAG pipelines . Experience with API integration and orchestration for hybrid AI systems. Good understanding of version control (Git) and containerization using Docker . Nice to Have: Prior experience delivering AI/ML or chatbot solutions for BFSI use cases. Exposure to tools like LangChain , Haystack , or LlamaIndex . Working knowledge of cloud platforms (AWS/GCP/Azure) and AI-specific services. Familiarity with CI/CD pipelines and DevOps processes.

About the Role We are seeking a Generative AI Engineer with 69 years of experience who can independently explore, prototype, and present the art of the possible using LLMs, agentic frameworks, and emerging Gen AI techniques. This role combines deep technical hands-on development with non-technical influence and presentation skills. You will contribute to key Gen AI innovation initiatives, help define new protocols (like MCP and A2A) and deliver fully functional prototypes that push the boundaries of enterprise AI not just in Jupyter notebooks, but as real applications ready for production exploration. Key Responsibilities LLM Applications Agentic Frameworks Design and implement end-to-end LLM applications using OpenAI, Claude, Mistral, Gemini, or LLaMA on AWS, Databricks, Azure or GCP. Build intelligent, autonomous agents using LangGraph, AutoGen, LlamaIndex, Crew.ai, or custom frameworks. Develop Multi Model, Multi Agent, Retrieval-Augmented Generation (RAG) applications with secure context embedding and tracing with reports. Rapidly explore and showcase the art of the possible through functional, demonstrable POCs Advanced AI Experimentation Fine-tune LLMs and Small Language Models (SLMs) for domain-specific use. Create and leverage synthetic datasets to simulate edge cases and scale training. Evaluate agents using custom agent evaluation frameworks (success rates, latency, reliability) Evaluate emerging agent communication standards A2A (Agent-to-Agent) and MCP (Model Context Protocol) Business Alignment Cross-Team Collaboration Translate ambiguous requirements into structured, AI-enabled solutions. Clearly communicate and present ideas, outcomes, and system behaviors to technical and non-technical stakeholders Good-To-Have Microsoft Copilot Studio DevRev Codium Cursor Atlassian AI Databricks Mosaic AI Qualifications 6-9 years of experience in software development or AI/ML engineering At least 3 years working with LLMs, GenAI applications, or agentic frameworks. Proficient in AI/ML, MLOps concepts, Python, embeddings, prompt engineering, and model orchestration Proven track record of developing functional AI prototypes beyond notebooks. Strong presentation and storytelling skills to clearly convey GenAI concepts and value. Ability to independently drive AI experiments from Location: Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Role Overview: We are looking for a Lead Data Scientist / AI Solution Architect to join our growing AI & Data team. The ideal candidate will have hands-on experience designing and deploying AI/ML solutions with Azure Cloud , LLMOps , Containerized environments , and Generative AI technologies. This is an onsite role based in Pune , offering you the opportunity to collaborate closely with cross-functional teams on impactful projects. Key Responsibilities: Architect and implement end-to-end AI/ML solutions using Azure AI/ML services Lead the design and development of LLMOps pipelines for deploying and managing large language models (LLMs) Work with containerized deployments using Docker and orchestration tools like Kubernetes Integrate and fine-tune Generative AI models for various real-world applications (text, vision, conversation, etc.) Collaborate with data engineers, product teams, and business stakeholders to deliver scalable AI systems Drive model monitoring, versioning, and responsible AI practices Document technical architecture, decision-making, and knowledge transfer Required Skills & Qualifications: 5 to 7 years of experience in Data Science / AI / ML solution development Strong hands-on experience with Azure AI services (ML Studio, Azure OpenAI, AI Foundry etc.) Experience working with LLMs , prompt engineering, and fine-tuning techniques Proven experience with containerized environments (Docker, Kubernetes) Strong programming skills in Python with relevant ML/AI libraries (TensorFlow, PyTorch, Transformers, etc.) Solid understanding of LLMOps/MLOps lifecycle and best practices Excellent communication, stakeholder management, and team collaboration skills Must Have: Hands-On LangChain, Hugging Face APIs, or Azure OpenAI APIs Strong knowledge of Azure Cognitive Services, Machine Learning Studio, Azure AI Search, AI Foundry Strong Knowledge of basic hygiene principles Git, Clean Code, Unit Testing, Jira, DevOps etc. Good to Have: Experience with Databricks Familiarity with Azure CI/CD pipelines Prior experience working in a startup or fast-paced product environmentRole & responsibilities

Job Summary: We are looking for an innovative and technically skilled Generative AI Developer with 2 - 4 years of experience to join our team, focusing on the development and deployment of intelligent agents using Agentforce, Salesforces GenAI platform, or similar frameworks. The ideal candidate will be passionate about applying large language models (LLMs) to real-world business workflows, building conversational agents, and delivering high-impact AI-powered solutions within the Salesforce ecosystem and beyond. Key Responsibilities: • Design, develop, and deploy Generative AI agents using Agentforce, LLMs (like GPT-4), and related frameworks. • Build and integrate intelligent, context-aware workflows into CRM, support, and operational systems. • Collaborate with cross-functional teams (Product, Engineering, Data, and Business) to understand business challenges and deliver scalable AI solutions. • Fine-tune and prompt LLMs for specific use cases such as market outreach, sales assistance, document summarization, and automation tasks. • Maintain and optimize agent performance through evaluation, prompt engineering, and feedback loops. • Stay up-to-date with the latest in generative AI, Salesforce AI tools (Einstein Copilot, Agentforce), and open-source frameworks. • Create technical documentation and provide support for production deployments and ongoing enhancements. Qualifications Required : • 2 - 4 years of experience in AI/ML or Software Development, with at least 1 year working directly with LLMs or GenAI applications. • Hands-on experience with Agentforce, OpenAI, LangChain, or other GenAI frameworks. • Proficiency in Python, JavaScript, or relevant programming languages for AI agent development. • Experience integrating GenAI capabilities into Salesforce, web apps, or enterprise systems. • Strong understanding of prompt engineering, vector databases, and agent orchestration. Preferred : • Experience with Salesforce Einstein Copilot, Salesforce Data Cloud, or MuleSoft integration. • Familiarity with LLMOps, model evaluation, or responsible AI best practices. • Knowledge of REST APIs, OAuth, and cloud platforms (AWS, GCP, Azure). Preferred candidate profile

Key Responsibilities: Collaborate closely with Machine Learning and Engineering teams on advanced data extraction technologies (e.g., no-OCR, VLM-based extraction) Translate business needs into epics and user stories for development teams Align product goals with company strategy in coordination with Product Management Maintain a well-prioritized product backlog based on business value Work with stakeholders and data analysts to ensure data-driven product decisions Track product progress, performance, and deliverables across sprints Communicate effectively with globally distributed teams and stakeholders Stay updated with agile practices, ML/AI trends, and industry standards Required Experience & Qualifications: 3+ years as a Product Owner in an agile environment Familiarity with AI/ML patterns (e.g., VLM, LLMs) and experience working with ML-driven teams Technical aptitude with a fast-learning mindset Strong data orientation and analytical thinking Agile and/or SAFe framework knowledge Excellent attention to detail and communication skills Comfortable working in international, cross-functional environments Proficient in spoken and written English Nice to Have: Exposure to Regulatory Compliance Product Marketing experience Strong cross-cultural communication Advanced data analysis capabilities Knowledge of Biometric Security Standards

Job Description Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with open-source LLMs and tools like TensorFlow/PyTorch and Hugging Face. Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years Experience) Machine Learning (ML) & Deep Learning: Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, sentiment analysis. Familiarity with NLP tasks like text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality. Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system/user prompts. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience with SQL, NoSQL, and vector databases. APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models.

Job Description Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with open-source LLMs and tools like TensorFlow/PyTorch and Hugging Face. Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years Experience) Machine Learning (ML) & Deep Learning: Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, sentiment analysis. Familiarity with NLP tasks like text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality. Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system/user prompts. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience with SQL, NoSQL, and vector databases. APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models.

Job Description Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs including Langchain, Llama Index, vector databases, prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with open-source LLMs and tools like TensorFlow/PyTorch and Hugging Face. Techniques such as quantization, LLM fine-tuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years Experience) Machine Learning (ML) & Deep Learning: Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT-4, Anthropic Claude, LLama, etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, sentiment analysis. Familiarity with NLP tasks like text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines and knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience building or integrating search and retrieval systems using Elasticsearch, AI Search, ChromaDB, PGVector, etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality. Knowledge of prompt formats, strategies, constraints, including few-shot, zero-shot, one-shot prompting, and using system/user prompts. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience with SQL, NoSQL, and vector databases. APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos AI Gigafactory, our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Senior Principal Consultant - AI Senior Engineer! In this role you&rsquoll be leveraging Azure&rsquos advanced AI capabilities or AWS Advance Ai capability, including Azure Machine Learning , Azure OpenAI, PrompFlow, Azure Cognitive Search, Azure AI Document Intelligence,AWS Sage Maker, AWS Bedrocks to deliver scalable and efficient solutions. You will also ensure seamless integration into enterprise workflows and operationalize models with robust monitoring and optimization. Responsibilities . AI Orchestration - Design and manage AI Orchestration flow using tools such as: Prompt Flow, Or LangChain Continuously evaluate and refine models to ensure optimal accuracy, latency, and robustness in production. . Document AI and Data Extraction, Build AI-driven workflows for extracting structured and unstructured data fromLearning, receipts, reports, and other documents using Azure AI Document Intelligence, and Azure Cognitive Services. . RAG Systems - Design and implement retrieval-augmented generation (RAG) systems using vector embeddings and LLMs for intelligent and efficient document retrieval Optimize RAG workflows for large datasets and low-latency operations. . Monitoring and Optimization - Implement advanced monitoring systems using Azure Monitor, Application Insights, and Log Analytics to track model performance and system health Continuously evaluate and refine models and workflows to meet enterprise-grade SLAs for performance and reliability. . Collaboration and Documentation - Collaborate with data engineers, software developers, and DevOps teams to deliver robust and scalable AI-driven solutions Document best practices, workflows, and troubleshooting guides for knowledge sharing and scalability. Qualifications we seek in you Minimum Qualifications . Proven experience with Machine Learning, Azure OpenAI, PrompFlow, Azure Cognitive Search, Azure AI Document Intelligence, AWS Bedrock, SageMaker Proficiency in building and optimizing RAG systems for document retrieval and comparison. . Strong understanding of AI/ML concepts, including natural language processing (NLP), embeddings, model fine-tuning, and evaluation Experience in applying machine learning algorithms and techniques to solve complex problems in real-world applications Familiarity with state-of-the-art LLM architectures and their practical implementation in production environments Expertise in designing and managing Prompt Flow pipelines for task-specific customization of LLM outputs. . Hands-on experience in training LLMs and evaluating their performance using appropriate metrics for accuracy, latency, and robustness Proven ability to iteratively refine models to meet specific business needs and optimize them for production environments. . Knowledge of ethical AI practices and responsible AI frameworks. . Experience with CI/CD pipelines using Azure DevOps or equivalent tools Familiarity with containerized environments managed through Docker and Kubernetes. . Knowledge of Azure Key Vault, Managed Identities, and Azure Active Directory (AAD) for secure authentication. . Experience with PyTorch or TensorFlow. . Proven track record of developing and deploying Azure-based AI solutions for large-scale, enterprise-grade environments. . Strong analytical and problem-solving skills, with a results-driven approach to building scalable and secure systems. Why join Genpact . Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation . Make an impact - Drive change for global enterprises and solve business challenges that matter . Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities . Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day . Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Contractual (Project-Based) Notice Period: Immediate - 15 Days Fill this form: https://forms.office.com/Pages/ResponsePage.aspx?id=hLjynUM4c0C8vhY4bzh6ZJ5WkWrYFoFOu2ZF3Vr0DXVUQlpCTURUVlJNS0c1VUlPNEI3UVlZUFZMMC4u Resume- shweta.soni@panthsoftech.com

( Immediate Joiners ) Role Overview: We are looking for a ML/AI Gen AI Expert with 4-7 years of experience for executing AI/GenAI use cases as POCs . Media domain experience (OTT, DTH, Web) is a plus. Key Responsibilities: Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders. Design, develop, and deploy models (ML and GenAI) using Google Clouds Vertex AI platform. Fine-tune and evaluate LLMs for domain-specific applications, ensuring responsible AI practices. Collaborate with data engineers and architects to ensure robust, scalable, and secure data pipelines feeding ML models. Document solutions, workflows, and experiments to support reproducibility, transparency, and handover readiness. Core Skills: Strong foundation in machine learning and deep learning, including supervised, unsupervised, and reinforcement learning. Hands-on experience with Vertex AI, including AutoML, Pipelines, Model Registry, and Generative AI Studio. Experience with LLMs and GenAI workflows, including prompt engineering, tuning, and evaluation. Python and ML frameworks proficiency (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). Strong collaboration and communication skills to work cross-functionally with data, product, and business teams. Technical Skills: Vertex AI on Google Cloud Model training, deployment, endpoint management, and MLOps tooling. GenAI tools and APIs Hands-on with PaLM, Gemini, or other large language models via Vertex AI or open source. Python Proficient in scripting ML pipelines, data preprocessing, and model evaluation. ML/GenAI Libraries scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain. Cloud & DevOps Experience with GCP services (BigQuery, Cloud Functions, Cloud Storage), CI/CD for ML, and containerization (Docker/Kubernetes) Experience in the media domain (OTT, DTH, Web) and handling large-scale media datasets.

Role Overview: As an Engineering Manager in the AI team, you will lead and mentor a team of 10+ software engineers working on a wide range of AI/ML/GenAI-driven initiatives. You will be responsible for the end-to-end delivery of AI solutions, guiding your team through the full software and machine learning lifecycle, from ideation and design to deployment and continuous improvement. In this hands-on leadership role, you will collaborate closely with engineering leaders, data scientists, product managers, and other stakeholders to deliver high-quality AI applications that power our products and services. Responsibilities: Leadership and Mentorship: Lead, mentor, and develop a team of 10+ AI/ML software engineers, fostering a culture of growth, collaboration, and technical excellence. Ensure high performance by providing regular feedback, coaching, and career development opportunities. AI/GenAI Architecture and Delivery: Oversee the design and delivery of AI and generative AI systems, ensuring that all solutions are scalable, robust, and high-quality. Guide your team to implement innovative AI models, tools, and infrastructure that drive business outcomes. Cross-Functional Collaboration: Partner with other engineering leaders, data scientists, product managers, and directors to align on strategic goals and deliverables. Collaborate closely with cross-functional teams to break down complex engineering tasks and drive the execution of the AI roadmap. Agile Leadership: Lead your team in an agile environment, participating in sprint planning, daily stand-ups, code reviews, and retrospectives. Help the team manage competing priorities while maintaining focus on delivering high-quality AI solutions. Technical Excellence: Promote best practices in software development, code quality, testing, and deployment. Drive the adoption of modern engineering practices like CI/CD, automated testing, and cloud-based AI/ML solutions to ensure the delivery of secure, scalable AI applications. Innovation: Stay up to date with the latest advancements in Generative AI and machine learning. Foster a culture of continuous learning, encouraging engineers to grow their technical skills and experiment with emerging technologies to contribute to the company's thought leadership in AI. Stakeholder Communication: Act as a liaison between the AI team and other stakeholders, effectively communicating progress, risks, and technical insights to non-technical leadership and product teams. Qualifications: Experience: 7-10 years of experience in software engineering, with at least 2-4 years in a leadership or management role, overseeing AI or machine learning teams. Proven track record of leading and delivering AI/ML and Generative AI initiatives at scale in fast-paced, dynamic environments. Technical Skills: Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. Strong experience with AI, machine learning, and deep learning technologies as well as solid understanding of the software development lifecycle, object-oriented programming, concurrency, design patterns, RESTful services, and microservice architecture. AI Tools and Cloud Technologies: Experience with cloud platforms (AWS, Google Cloud, Azure), with a focus on AI/ML deployment (e.g., VertexAI, GKE, BigQuery, Kubeflow, TensorFlow Serving). Familiarity with MLOps practices and tools for model deployment and monitoring (e.g., Terraform, GitHub Actions, Concourse). Leadership and Collaboration: Strong people management and leadership skills, with experience leading cross-functional teams. Proven ability to mentor engineers, manage competing priorities, and align team efforts with business objectives. Agile Experience: Strong understanding of agile methodologies, with experience leading teams in an agile environment. Knowledge of best practices for managing sprints, tasks, and project timelines. Communication: Excellent verbal and written communication skills. Ability to communicate complex technical concepts to non-technical stakeholders and build strong working relationships across the organization. Preferred Qualifications: Experience working with large language models (LLMs) or fine-tuning open-source models like GPT. Familiarity with modern AI development tools, such as Jupyter notebooks, Kubernetes, Docker, and CI/CD pipelines. Experience in high-compliance or enterprise-grade environments with a focus on AI ethics, privacy, and security. Education: Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field. Ph.D. is a plus.

Job Description: Python Training, Internship and Job Assistance Position: Python Intern Location: Pune, Maharashtra, India Duration: 6 months Mode: Offline Stipend: Unpaid Training Program: Free Training with Job Assistance upon Successful Completion Pre-Placement Offer (PPO) Opportunity: 2.5 LPA CTC (Based on performance) Note: CANDIDATES SHOULD BE READY TO LEARN NEW TECHNOLOGIES About the Role: We are seeking a motivated and detail-oriented Python Intern to join our team. The ideal candidate will have a foundational understanding of API development using frameworks like Flask and FastAPI, a strong grasp of Python libraries such as Pandas and NumPy, and a knack for problem-solving. Knowledge of data analytics tools and Large Language Models (LLMs) will be considered a plus. Key Responsibilities: Develop and maintain RESTful APIs using Flask and FastAPI. Work with data manipulation and analysis libraries like Pandas and NumPy. Assist in building scalable and efficient back-end solutions. Solve real-world problems with logical and analytical thinking. Support data analytics efforts using tools like Power BI (preferred). Collaborate with cross-functional teams to understand requirements and deliver solutions. Explore and implement applications of LLMs and other advanced technologies (as needed). Requirements: Proficiency in Python programming. Hands-on experience or knowledge of Flask and FastAPI frameworks. Familiarity with data analysis libraries such as Pandas and NumPy. Strong problem-solving and logical thinking skills. Good understanding of RESTful API design principles. Knowledge of data analytics tools like Power BI is a plus. Awareness of Large Language Models (LLMs) and their potential applications is a bonus. Eagerness to learn and work in a collaborative environment. What We Offer: Hands-on experience in API development and data analytics projects. Mentorship from experienced professionals. Opportunity to explore cutting-edge technologies like LLMs. A learning-focused environment to develop both technical and analytical skills. Potential for full-time opportunities based on performance.

Role & responsibilities We are seeking an enthusiastic and highly skilled Senior AI ML Developer to join our team and work on exciting AI initiatives. The ideal candidate should have worked in CRM Domain like Zoho CRM/ Fresh works and have expert knowledge in AI/ML models, LLMS, Vector database and RAG techniques to automate workflows, create conversational analytics assistants and create similarity models by clustering/ embeddings. 1. Develop CRM Agentic AI Design and implement AI agents using frameworks like Lang Chain, AutoGPT, or ReAct. Automate CRM processes by enabling agents to handle emails, generate follow-ups, update pipelines, and classify tickets. Integrate models for sentiment analysis, intent recognition, entity extraction, and summarization. Connect agents to external APIs, calendars, and CRM tools (e.g., Salesforce, HubSpot). Manage agent memory and context via vector databases like FAISS or Pinecone. 2. Conversational KPI Dashboard Assistant Build a chatbot interface that allows users to query CRM KPIs via natural language. Use Python, LangChain, and OpenAI APIs to parse queries and trigger backend data retrieval tools. Render results in both dashboard format (e.g., Recharts/Chart.js) and tabular views. Support queries like "Whats the total expected revenue this quarter?" or "Show me the lead-to-win ratio by region." 3. Similarity and Recommendation Engines Extract features from existing AI/ML libraries. Build and manage an embedding database for semantic similarity search. Implement clustering algorithms (e.g., K-Means) to group songs based on genre. Develop a scoring system to compare new tracks to a database of existing songs. Required Experience and Qualifications: 4+ years of experience in AI/ML Model development. Should have expert knowledge in CRM Domain including workflows, Forms, Dashboards/reports and data import/export as done. Proficient in Python, with strong experience in TensorFlow, PyTorch, and Scikit-learn . Working knowledge of LangChain, AutoGPT and LLM integration. Expertise in developing Agents for CRM, Dashboards in Leading organisation. Expertise in implementing Agentic AI solutions using LLM models, RAG and Vector database. Proven experience in vector similarity, embedding models and clustering techniques. Passionate about AI innovation and solving real-world challenges with automation and intelligence Proven experience in designing platform architecture and managing API integrations. Strong background in microservices architecture and REST API design. Demonstrated experience with scalability and performance optimization for cloud-based platforms. Experience with Agile methodologies and leading cross-functional teams in a fast-paced environment. Excellent communication and presentation skills for delivering product demos and gathering customer feedback. Proven ability to manage a product roadmap and deliver on tight deadlines . Experience with data security , compliance, and industry best practices. A bachelors degree in computer science, engineering, or a related field.

Responsibilities: * Design, develop, test & maintain software solutions using Python, React, AWS, Kubernetes, LLMs, Langchain & Crewai. * Collaborate with cross-functional teams on project delivery & technical strategy.

Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Your role in our mission Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation. What we're looking for Bachelor's/Master’s degree in computer science, Engineering, or related fields. Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, SageMaker, etc.). Experience with LLM-specific tools and frameworks (LangChain,Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. Proficient in containerization (Docker, Kubernetes) and CI/CD practices. Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. Strong skills in Giskard, Deepeval etc. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. Role Description Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation.

Gainwell Technologies LLC Summary Gainwell Technologies is seeking a highly skilled AI Engineer to design, develop, and deploy advanced AI and Generative AI (Gen AI) solutions, across our healthcare technology platforms. This role involves building and optimizing AI / GEN AI technologies, integrating them into existing systems, and ensuring their effectiveness in improving healthcare outcomes and operational efficiency while maintaining compliance with industry standards. Your role in our mission AI/ GEN AI Model Development – Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. Experienced in multiple LLM fine tuning techniques. Experienced in building GEN AI solutions using RAG architecture. Skilled in both Lang Chain and Lang Graph. Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. Experienced in multiple Vector Databases as well as Graph Database Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. Front End Development – Streamlit is a must. Good to have React, Angular or Vue.js What we're looking for Master’s or Ph.D in Computer Science, AI, Data Science, or a related field. 4+ years of experience in AI/ML engineering, with a focus on developing and deploying AI solutions. Hands-on expertise in machine learning, deep learning, Gen AI ( multi modal LLMs), NLP, and computer vision. Strong programming skills in Python, TensorFlow, PyTorch, and other AI frameworks. Experience developing, deploying and finetuning LLMs (GPT, Gemini, Claude or similar) for real world applications including prompt engineering, model optimization and inference efficiency. Experience with cloud platforms (AWS, Azure, or GCP) and MLOps for scalable AI deployments. Proficiency in working with big data technologies (Spark, Hadoop, SQL, NoSQL databases). Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. AI/ GEN AI Model Development – Design, build, and train machine learning, deep learning, time series models, Gen AI (Multi modal LLMs), predictive analytics, Natural Language Processing, Image Processing solutions for healthcare applications. Experienced in multiple LLM fine tuning techniques. Experienced in building GEN AI solutions using RAG architecture. Skilled in both Lang Chain and Lang Graph. Experience in Agentic AI Frameworks and Workflow using Lang Chain, Lang Graph or Crew AI or Open AI Swarm. Experienced in multiple Vector Databases as well as Graph Database Skilled in Agentic AI Framework and has built at least one solution using Agentic AI. End-to-End AI Solution Deployment – Develop, test, and deploy AI solutions in cloud and on-premises environments, ensuring reliability, scalability, and real-world impact. Data Processing – Work with large healthcare datasets, performing data preprocessing, feature engineering, and model training while ensuring compliance with HIPAA and other regulatory standards. System Integration – Skilled in API development and integrations. Implement and optimize AI models within Gain well’s existing technology stack, collaborating with software engineers to ensure seamless integration. Experienced in ML Ops and LLM Ops. Experienced in evaluating models and continuous performance monitoring of both ML/DL and LLMs. Experienced in applying security measures in GEN AI solutions, implementing guard rails. Performance Optimization – Continuously monitor, refine, and optimize AI / GEN AI models for accuracy, efficiency, and speed, leveraging ML Ops and LLM Ops best practices. AI Research & Innovation – Stay updated with the latest AI/ML/ GEN AI advancements, exploring new technologies and methodologies to enhance solution effectiveness. Compliance & Security – Ensure AI implementations adhere to healthcare industry regulations, ethical AI principles, and data privacy standards. Automation & Workflow Enhancement – Identify opportunities to automate workflows and optimize business processes using AI-driven solutions. Front End Development – Streamlit is a must. Good to have React, Angular or Vue.js

Experience 9-13 years Location: Gurgaon/Noida Education: BE/B. Tech./Master of Computer Application Work Experience: Overall 9+ years of quality engineering experience with DWH/ETL for enterprise grade applications Hands on experience with functional, non-functional and automation of products Hands on experience with leverage LLMs/GenAI for improving efficiency & effectiveness of overall delivery process Role & Responsibilities: Leading end-to-end QE for product suite Authoring QE test strategy for a release and executing it for a release Driving quality releases by closely working with development, PMs, DevOps, support and business teams Achieving automation coverage for product suite with good line coverage Manage risks and resolves issues that affect release scope, schedule and quality Work with product teams to understand impacts of branches and code merges, etc. Lead and co-ordinate the release activities including the execution of overall Ability to lead team of SDETs and help them in addressing their issues Mentoring and coaching members in the team Technical Skills: Experience in ETL / BI Testing, using any ETL and Reporting Tool with Oracle / SQL Server / as Database Exposure to Data Warehousing and Dimensional Modelling Concepts Hands-on with coding preferably Python Extensive experience in writing and troubleshooting SQL Queries Ability to achieve good functional coverage of product suite Hands on experience with automation tools (Selenium, TestNg, etc.) Experience with CI/CD tools e.g., Jenkins Experience with tools like JIRA, Confluence, SharePoint, TestRails, Zephyr etc. Experience with performance, volume and stress testing Solid understanding of cloud services platforms e.g., AWS, GCP, Azure etc. Well versed with DBs and SQLs Hand-on experience with GenAI/LLMs/RAGs/Agents Soft Skills: Excellent communication skills. Ability to convey hard/sensitive messages without any apprehensions as well as avoid creating frictions. Ability to navigate through organization independently. About AXTRIA (www.axtria.com) Axtria is a global provider of cloud software and data analytics to the Life Sciences industry. We help Life Sciences companies transform the product commercialization journey to drive sales growth and improve healthcare outcomes for patients. We are acutely aware that our work impacts millions of patients and lead passionately to improve their lives.