560 Mistral Jobs

Job Title: AI Research Engineer – Private LLM & Cognitive Systems Location: Delhi Type: Full-Time Experience Level: Senior / Expert Start Date: Immediate About Brainwave Science: Brainwave Science is a leader in cognitive technologies, specializing in solutions for the security and intelligence sectors. Our flagship product, iCognative™ , leverages real-time cognitive response analysis using Artificial Intelligence and Machine Learning techniques to redefine the future of investigations, defense, counterterrorism, and counterintelligence operations. Beyond security, Brainwave Science is at the forefront of healthcare innovation, applying our cutting-edge technology to identifying diseases, various neurological conditions, and mental health challenges in advance and identification of stress and anxiety in real time and providing non-medical, science-backed interventions. Together, we are shaping a future where advanced technology strengthens security, promotes wellness, and creates a healthier, safer world for individuals and communities worldwide. About the Role We are seeking an experienced and forward-thinking AI/ML Engineer – LLM & Deep Learning Expert to design, develop, and deploy Large Language Models (LLMs) and intelligent AI systems. You will work on cutting-edge projects at the intersection of natural language processing , edge AI , and biosignal intelligence , helping drive innovation across defense, security, and healthcare use cases. This role is ideal for someone who thrives in experimental environments, understands private and local LLM deployments, and is passionate about solving real-world challenges using advanced AI. Responsibilities Design, train, fine-tune, and deploy Large Language Models using frameworks like PyTorch , TensorFlow , or Hugging Face Transformers Integrate LLMs for local/edge deployment using tools like Ollama , LangChain , LM Studio , or llama.cpp Build NLP applications for intelligent automation , investigative analytics , and biometric interpretation Optimize models for low-latency , token efficiency , and on-device performance Work on prompt engineering , embedding tuning , and vector search integration (FAISS, Qdrant, Weaviate) Collaborate with technical and research teams to deliver scalable AI-driven features Stay current with developments in open-source and closed-source LLM ecosystems (e.g., Meta, OpenAI, Mistral) Must-Have Requirements B.Tech/M.Tech in Computer Science (CSE) , Electronics & Communication (ECE) , or Electrical & Electronics (EEE) from IIT, NIT, or BITS Minimum 3 - 4 years of hands-on experience in AI/ML, deep learning , and LLM development Deep experience with Transformer models (e.g., GPT, LLaMA, Mistral, Falcon, Claude) Hands-on with tools like LangChain , Hugging Face , Ollama , Docker , or Kubernetes Proficiency in Python , and strong knowledge of Linux environments Strong understanding of NLP , attention mechanisms , and model fine-tuning Preferred Qualifications Experience with biosignals , especially EEG or time-series data Experience deploying custom-trained LLMs on proprietary datasets Familiarity with RAG pipelines and multi-modal models (e.g., CLIP, LLaVA) Knowledge of cloud platforms (AWS, GCP, Azure) for scalable model training and serving Published research, patents, or open-source contributions in AI/ML communities Excellent communication, analytical, and problem-solving skills What We Offer Competitive compensation based on experience Flexible working hours and remote-friendly culture Access to high-performance compute infrastructure Opportunities to work on groundbreaking AI projects in healthcare, security, and defense

About The Role We are seeking a highly motivated and creative Platform Engineer with a true research mindset. This is a unique opportunity to move beyond traditional development and step into a role where you will ideate, prototype, and build production-grade applications powered by Generative AI. You will be a core member of a platform team, responsible for developing both internal and customer-facing solutions that are not just functional but intelligent. If you are passionate about the MERN stack, Python, and the limitless possibilities of Large Language Models (LLMs), and you thrive on building things from the ground up, this role is for you. Core Responsibilities - Full-Stack Engineering : Write clean, scalable, and robust code across the MERN stack (MongoDB, Express.js, React, Node.js) and Python. AI-Powered Product Development : Create and enhance key products such as : Intelligent chatbots for customer service and internal support. Automated quality analysis and call auditing systems using LLMs for transcription and sentiment analysis. AI-driven internal portals and dashboards to surface insights and streamline workflows. Gen AI Integration & Optimization : Work hands-on with foundation LLMs, fine-tuning custom models, and implementing advanced prompting techniques (zero-shot, few-shot) to solve specific business problems. Research & Prototyping : Explore and implement cutting-edge AI techniques, including setting up systems for offline LLM inference to ensure privacy and performance. Collaboration : Partner closely with product managers, designers, and business stakeholders to transform ideas into tangible, high-impact technical solutions. Required Skills & Experience Experience : 2-5 years of professional experience in a software engineering role. Full-Stack Proficiency : Strong command of the MERN stack (MongoDB, Express.js, React, Node.js) for building modern web applications. Python Expertise : Solid programming skills in Python, especially for backend services and AI/ML workloads. Generative AI & LLM Experience (Must-Have) Demonstrable experience integrating with foundation LLMs (e.g., OpenAI API, Llama, Mistral, etc.). Hands-on experience building complex AI systems and implementing architectures such as Retrieval-Augmented Generation (RAG) to ground models with external knowledge. Practical experience with AI application frameworks like LangChain and LangGraph to create agentic, multi-step workflows. Deep understanding of prompt engineering techniques (zero-shot, few-shot prompting). Experience or strong theoretical understanding of fine-tuning custom models for specific domains. Familiarity with concepts or practical experience in deploying LLMs for offline inference. R&D Mindset : A natural curiosity and passion for learning, experimenting with new technologies, and solving problems in novel ways. Bonus Points (Nice-to-Haves) Cloud Knowledge : Hands-on experience with AWS services (e.g., EC2, S3, Lambda, SageMaker). (ref:hirist.tech)

Job Location : Noida Job Role : Sr. AI/ML/ Data Scientist Overview We are seeking a highly skilled and experienced AI/ML Expert to spearhead the design, development, and deployment of advanced artificial intelligence and machine learning models. This role requires a strategic thinker with a deep understanding of ML algorithms, model optimization, and production-level AI systems. You will guide cross-functional teams, mentor junior data scientists, and help shape the AI roadmap to drive innovation and business impact. This role involves statistical analysis, data modeling, and interpreting large sets of data. An AI/ML expert with experience in creating AI models for data intelligence companies who specializes in developing and deploying artificial intelligence and machine learning solutions tailored for data-driven businesses. This expert should possess a strong background in data analysis, statistics, programming, and machine learning algorithms, enabling them to design innovative AI models that can extract valuable insights and patterns from vast amounts of data. About The Role The design and development of a cutting-edge application powered by large language models (LLMs). This tool will provide market analysis and generate high-quality, data-driven periodic insights. You will play a critical role in building a scalable and intelligent system that integrates structured data, NLP capabilities, and domain-specific knowledge to produce analyst-grade content. Key Responsibilities Design and develop LLM-based systems for automated market analysis. Build data pipelines to ingest, clean, and structure data from multiple sources (e.g., market feeds, news articles, technical reports, internal datasets). Fine-tune or prompt-engineer LLMs (e.g., GPT-4.5, Llama, Mistral) to generate concise, insightful reports. Collaborate closely with domain experts to integrate industry-specific context and validation into model outputs. Implement robust evaluation metrics and monitoring systems to ensure quality, relevance, and accuracy of generated insights. Develop and maintain APIs and/or user interfaces to enable analysts or clients to interact with the LLM system. Stay up to date with advancements in the GenAI ecosystem and recommend relevant improvements or integrations. Participate in code reviews, experimentation pipelines, and collaborative research Required : Strong fundamentals in machine learning, deep learning, and natural language processing (NLP). Proficiency in Python, with hands-on experience using libraries such as NumPy, Pandas, and Matplotlib/Seaborn for data analysis and visualization. Experience developing applications using LLMs (both closedand open-source models). Familiarity with frameworks like Hugging Face Transformers, LangChain, LlamaIndex, etc. Experience building ML models (e.g., Random Forest, XGBoost, LightGBM, SVMs), along with familiarity in training and validating models. Practical understanding of deep learning frameworks: TensorFlow or PyTorch. Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), and LLM evaluation strategies. Experience working with REST APIs, data ingestion pipelines, and automation workflows. Strong analytical thinking, problem-solving skills, and the ability to convert complex technical work into business-relevant insights. Preferred Familiarity with the chemical or energy industry, or prior experience in market research/analyst workflows. Exposure to frameworks such as OpenAI Agentic SDK, CrewAI, AutoGen, SmolAgent, etc. Experience deploying ML/LLM solutions to production environments (Docker, CI/CD). Hands-on experience with vector databases such as FAISS, Weaviate, Pinecone, or ChromaDB. Experience with dashboarding tools and visualization libraries (e.g., Streamlit, Plotly, Dash, or Tableau). Exposure to cloud platforms (AWS, GCP, or Azure), including usage of GPU instances and model hosting services. About ChemAnalyst ChemAnalyst is a digital platform, which keeps a real-time eye on the chemicals and petrochemicals market fluctuations, thus, enabling its customers to make wise business decisions. With over 450 chemical products traded globally, we bring detailed market information and pricing data at your fingertips. Our real-time pricing and commentary updates enable users to stay acquainted with new commercial opportunities. Each day, we flash the major happenings around the globe in our news section. Our market analysis section takes it a step further, offering an in-depth evaluation of over 15 parameters including capacity, production, supply, demand gap, company share and among others. Our team of experts analyse the factors influencing the market and forecast the market data for up to the next 10 years. We are a trusted source of information for our international clients, ensuring user-friendly and customized deliveries on time. (ref:hirist.tech)

We are looking for a backend developer with hands-on experience integrating open-source LLMs (e.g., Mistral, LLaMA) and vector databases (like FAISS, Qdrant, Weaviate, Milvus) in offline or edge environments. You will help develop core APIs and infrastructure to support embedding pipelines, retrieval-augmented generation (RAG), and LLM inference on local or mobile hardware. Selected Intern's Day-to-day Responsibilities Include Design and implement backend services that interface with local LLMs and vector databases Develop APIs to support prompt engineering, retrieval, and inference Integrate embedding models (e.g., BGE, MiniLM) and manage chunking/processing pipelines Optimize performance for offline or constrained environments (mobile, embedded devices, etc.) Package and deploy models via frameworks like Ollama, llama.cpp, gguf, or on-device runtimes Handle local file I/O, document ingestion, metadata tagging, and indexing About Company: Infoware is a process-driven software solutions provider specializing in bespoke software solutions. We work with several enterprises and startups and provide them with end-to-end solutions. You may visit the company website at https://www.infowareindia.com/

We are looking for a backend developer with hands-on experience integrating open-source LLMs (e.g., Mistral, LLaMA) and vector databases (like FAISS, Qdrant, Weaviate, Milvus) in offline or edge environments. You will help develop core APIs and infrastructure to support embedding pipelines, retrieval-augmented generation (RAG), and LLM inference on local or mobile hardware. Selected Intern's Day-to-day Responsibilities Include Design and implement backend services that interface with local LLMs and vector databases Develop APIs to support prompt engineering, retrieval, and inference Integrate embedding models (e.g., BGE, MiniLM) and manage chunking/processing pipelines Optimize performance for offline or constrained environments (mobile, embedded devices, etc.) Package and deploy models via frameworks like Ollama, llama.cpp, gguf, or on-device runtimes Handle local file I/O, document ingestion, metadata tagging, and indexing About Company: Infoware is a process-driven software solutions provider specializing in bespoke software solutions. We work with several enterprises and startups and provide them with end-to-end solutions. You may visit the company website at https://www.infowareindia.com/

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : Microsoft Azure OpenAI Service Good to have skills : NA Minimum 7.5 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: As an Application Lead, you will be responsible for leading the effort to design, build, and configure applications using Azure AI Services, Microsoft Azure OpenAI Service and Azure PaaS components. Your typical day will involve collaborating with cross-functional teams, managing project timelines, and ensuring the successful delivery of high-quality applications. Roles & Responsibilities: - Lead the design, development, and deployment of applications using Microsoft Azure OpenAI Service, Azure AI Search (Cognitive Search), Azure Language Services (CLU), Microsoft Bot Framework/ Microsoft Power Virtual Agents (Microsoft Copilot Studio) and Azure PaaS. - Act as the primary point of contact for the project, collaborating with cross-functional teams to ensure project timelines are met. - Ensure the successful delivery of high-quality applications, adhering to best practices and industry standards. - Provide technical guidance and mentorship to team members, fostering a culture of continuous learning and growth. - Stay updated with the latest advancements in Microsoft Azure OpenAI Service, Azure AI Search (Cognitive Search) and Azure Language Services (CLU) integrating innovative approaches for sustained competitive advantage. Professional & Technical Skills: - Must To Have Skills: Strong experience with Microsoft Azure OpenAI Service, Azure AI Search (Cognitive Search), Azure Language Services (CLU) and Azure PaaS including API Management, Key Vault and Application Insights. - Must To Have Skills: At least 1+ year hands on experience in Azure based LLMs with knowledge in embeddings/vectorization and semantic/vector based indexing and search. Strong experience in LLM frameworks such as Langchain and Semantic Kernel. -Must to Have Skills: Experience with conversational AI with Microsoft Bot Framework or Power Virtual Agents (Microsoft Copilot Studio). Should have experience in integrating chatbot solutions with multiple channels. - Must To Have Skills: Strong understanding of software development best practices including Agile methodologies and industry standards with special focus on API, function app and logic app building. Experience with Python programming language, using Visual Studio Code IDE and Azure AI Studio. - Good To Have Skills: Knowledge of other vector databases, Knowledge Graphs and other programming languages such as C#. Experience with different LLMs such as Llama, Mistral etc. - Good To Have Skills: Experience with deployment of applications and containerization technologies such as Docker or Kubernetes. Good To Have Skills: Experience with all Azure AI services like Video Indexer, Computer Vision, Custom Vision, Document Intelligence. - Experience with database technologies such as SQL Server and Cosmos DB. - Solid grasp of software testing and quality assurance principles. - Knowledge of DevOps practices. Additional Information: - The candidate should have a minimum of years of experience in software development. - The ideal candidate will possess a strong educational background in computer science or a related field, along with a proven track record of delivering impactful solutions. - This position is based at our Bengaluru office.

Job Description: The AI/ML engineer role requires a blend of expertise in machine learning operations (MLOps), ML Engineering, Data Science, Large Language Models (LLMs), and software engineering principles. Skills you'll need to bring: Experience building production-quality ML and AI systems. Experience in MLOps and real-time ML and LLM model deployment and evaluation. Experience with RAG frameworks and Agentic workflows valuable. Proven experience deploying and monitoring large language models (e.g., Llama, Mistral, etc.). Improve evaluation accuracy and relevancy using creative, cutting-edge techniques from both industry and new research Solid understanding of real-time data processing and monitoring tools for model drift and data validation. Knowledge of observability best practices specific to LLM outputs, including semantic similarity, compliance, and output quality. Strong programming skills in Python and familiarity with API-based model serving. Experience with LLM management and optimization platforms (e.g., LangChain, Hugging Face). Familiarity with data engineering pipelines for real-time input-output logging and analysis. Qualifications: Experience working with common AI-related models, frameworks and toolsets like LLMs, Vector Databases, NLP, prompt engineering and agent architectures. Experience in building AI and ML solutions. Strong software engineering skills for the rapid and accurate development of AI models and systems. Prominent in programming language like Python. Hands-on experience with technologies like Databricks, and Delta Tables. Broad understanding of data engineering (SQL, NoSQL, Big Data), Agile, UX, Cloud, software architecture, and ModelOps/MLOps. Experience in CI/CD and testing, with experience building container-based stand-alone applications using tools like GitHub, Jenkins, Docker and Kubernetes Responsibilities: Participate in research and innovation of data science projects that have impact to our products and customers globally. Apply ML expertise to train models, validates the accuracy of the models, and deploys the models at scale to production. Apply best practices in MLOps, LLMOps, Data Science, and software engineering to ensure the delivery of clean, efficient, and reliable code. Aggregate huge amounts of data from disparate sources to discover patterns and features necessary to automate the analytical models. About Company Improva is a global IT solution provider and outsourcing company with contributions across several domains including FinTech, Healthcare, Insurance, Airline, Ecommerce & Retail, Logistics, Education, Insurance, Startups, Government & Semi-Government, and more.

Key Responsibilities Advanced Model Development: Design and implement cutting-edge deep learning models using frameworks like PyTorch and TensorFlow to address specific business challenges. AI Agent and Chatbot Development: Create conversational AI agents capable of delivering seamless, human-like interactions, from foundational models to fine-tuning chatbots tailored to client needs. Retrieval-Augmented Generation (RAG): Develop and optimize RAG models, enhancing AI’s ability to retrieve and synthesize relevant information for accurate responses. Framework Expertise: Leverage LLAMAIndex and LangChain frameworks for building agent-driven applications that interact with large language models (LLMs). Data Infrastructure: Expertise in managing and utilizing data lakes, data warehouses (including Snowflake), and Databricks for large-scale data storage and processing. Machine Learning Operations (MLOps): Manage the full lifecycle of machine learning projects, from data preprocessing and feature engineering through model training, evaluation, and deployment, with a solid understanding of MLOps practices. Data Analysis & Insights: Conduct advanced data analysis to uncover actionable insights and support data-driven strategies across the organization. Cross-Functional Collaboration: Partner with cross-departmental stakeholders to align AI initiatives with business needs, developing scalable AI-driven solutions. Mentorship & Leadership: Guide junior data scientists and engineers, fostering innovation, skill growth, and continuous learning within the team. Research & Innovation: Stay at the forefront of AI and deep learning advancements, experimenting with new techniques to improve model performance and enhance business value. Reporting & Visualization: Develop and present reports, dashboards, and visualizations to effectively communicate findings to both technical and non-technical audiences. Cloud-Based AI Deployment: Utilize AWS Bedrock, including tools like Mistral and Anthropic Claude, to deploy and manage AI models at scale, ensuring optimal performance and reliability. Web Framework Integration: Build and deploy AI-powered applications using web frameworks such as Django and Flask, enabling seamless API integration and scalable backend services. Technical Skills Deep Learning & Machine Learning: Extensive hands-on experience with PyTorch, TensorFlow, and scikit-learn, along with large-scale data processing. Programming & Data Engineering: Strong programming skills in Python or R, with knowledge of big data technologies such as Hadoop, Spark, and advanced SQL. Data Infrastructure: Proficiency in managing and utilising data lakes, data warehouses, and Databricks for large-scale data processing and storage. MLOps & Data Handling: Familiar with MLOps and experienced in data handling tools like pandas and dask for efficient data manipulation. Cloud Computing: Advanced understanding of cloud platforms, especially AWS, for scalable AI/ML model deployment. AWS Bedrock: Expertise in deploying models on AWS Bedrock, with tools such as Mistral and Anthropic Claude. AI Frameworks: Skilled in LLAMAIndex and LangChain, with practical experience in agent-based applications. Data Visualization: Proficient in visualization tools like Tableau, Power BI for clear data presentation. Analytical & Communication Skills: Strong problem-solving abilities with the capability to convey complex technical concepts to diverse audiences. Team Collaboration & Leadership: Proven success in collaborative team environments, with experience in mentorship and leading innovative data science projects. Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. Experience: Specializing in deep learning, including extensive experience in PyTorch and TensorFlow. Advanced AI Knowledge: Familiarity with reinforcement learning, NLP, and generative models. Benefits: Friendly Work Environment Work-Life Balance Company-Sponsored Medical Insurance 5-Day Work Week with Flexible Timings Frequent Team Outings Yearly Leave Encashment Location: Ahmedabad

Key Responsibilities: Lead a cross-functional engineering team building AI-powered call center solutions. Oversee the deployment and tuning of STT, TTS, and LLM models. Translate expert agent feedback into model tuning strategies. Manage prompt engineering, RAG/CAG integration, and action workflows. Customize models rapidly for new enterprise clients. Ensure the team can: Understand speech-to-text and text-to-speech models Analyze feedback from expert call agents Develop and refine prompts for LLM tuning Create reliable, scalable workhorse models Optimize model operations to reduce cost Integrate LLMs with Retrieval-Augmented Generation (RAG) and Context-Augmented Generation (CAG) systems Build custom action workflows linked with enterprise data systems Enable rapid customization for customer-specific use cases and data environments Requirements: Strong background in NLP and LLMs (GPT, Mistral, Claude, etc.). Experience in leading AI/ML teams or mentoring. Exposure to distributed teams across time zones. Familiar with cloud platforms (AWS/GCP), vector DBs, LangChain, etc. Deep understanding of NLP, speech technologies, and generative AI stacks Strong systems architecture and cloud deployment skills Experience leading technical teams, ideally in a fast-paced environment

Experience: 3 to 10 Location : Coimbatore Notice Period: Immediate Joiners are Preferred. Note: Minimum 2 years experience into core Gen AI 𝗞𝗲𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: Design, develop, and fine-tune Large Language Models (LLMs) for various in-house applications. Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Build and manage data pipelines for processing, transforming, and feeding structured/unstructured data into AI models. Ensure scalability, performance, and security of AI-driven solutions in production environments. Collaborate with cross-functional teams, including data engineers, software developers, and product managers. Conduct experiments and evaluations to improve AI system accuracy and efficiency. Stay updated with the latest advancements in AI/ML research, open-source models, and industry best practices. 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 Strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases (e.g., Pinecone, ChromaDB, Weaviate, OpenSearch, FAISS). Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Experience in Python web frameworks such as FastAPI, Django, or Flask. Experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes). Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications. Strong understanding of vector search, embedding models, and hybrid retrieval techniques. Experience with optimizing inference and serving AI models in real-time production systems. 𝗡𝗶𝗰𝗲-𝘁𝗼-𝗛𝗮𝘃𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 Experience with multi-modal AI (text, image, audio). Familiarity with privacy-preserving AI techniques and responsible AI frameworks. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation. Skills: pytorch,rag architectures,opensearch,weaviate,docker,llm fine-tuning,chromadb,apache airflow,lora,python,hybrid retrieval techniques,django,gcp,crewai,opean ai,hugging face,gen ai,pinecone,faiss,aws,autogpt,embedding models,flask,fastapi,llm apis,deepspeed,vector search,peft,langchain,azure,spark,kubernetes,ai gen,tensorflow,real-time production systems,langgraph,kafka

About the Job As a Lead AI/ML Engineer, you spearhead the design, development, and implementation of advanced AI and machine learning models. Your role involves guiding a team of engineers ensuring the successful deployment of projects that leverage AI/ML technologies to solve complex problems. You collaborate closely with stakeholders to understand business needs, translate them into technical requirements, and drive innovation. Your responsibilities include optimizing model performance, conducting rigorous testing, and maintaining up-to-date knowledge of the latest industry trends. Additionally, you mentor team members, promote best practices, and contribute to strategic decision-making within the organization. Core Responsibilities Client Interaction: Discuss client requirements and develop proposals tailored to their needs. Demonstrations and Workshops: Conduct solution/product demonstrations, POC/Proof of Technology workshops, and prepare effort estimates in line with customer budgets and organizational financial guidelines. Model Oversight: Oversee the development and deployment of AI models, especially those generating content such as text, images, or other media. AI Solutions: Engage in coding, designing, developing, implementing, and deploying advanced AI solutions. Expertise Utilization: Utilize your expertise in NLP, Python programming, LLMs, Deep Learning, and AI principles to drive the development of transformative technologies. Leadership and Initiative: Actively lead projects and contribute to both unit-level and organizational initiatives to provide high-quality, value-adding solutions to customers. Strategic Development: Develop value-creating strategies and models to help clients innovate, drive growth, and increase profitability. Technology Awareness: Stay informed about the latest technologies and industry trends. Problem-Solving and Collaboration: Employ logical thinking and problem-solving skills, and collaborate effectively. Client Interfacing: Demonstrate strong client interfacing skills. Project and Team Management: Manage projects and teams efficiently. Required Skills Skills: Hands-on expertise in NLP, Computer Vision, programming, and related concepts. Leadership: Capable of leading and mentoring a team of AI engineers and researchers, setting strategies for AI model development and deployment, and ensuring these align with business goals. Technical Proficiency: Proficient in implementing and optimizing advanced AI solutions using Deep Learning and NLP, with tools such as TensorFlow, PyTorch, Spark, and Keras. LLM Experience: Experience with Large language Models like GPT 3.5, GPT 4, Llama, Gemini, Mistral, etc. along with experience in LLM integration frameworks like LangChain, Llamaindex, AgentGPT, etc. Deep Learning OCR: Extensive experience implementing solutions using Deep Learning OCR algorithms. Neural Networks: Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). Python Expertise: Strong coding skills in Python, including related frameworks, best practices, and design patterns. Preferred Knowledge: Familiarity with word embeddings, transformer models, and image/text generation and processing. Deployment: Experience deploying AI/ML solutions as a service or REST API endpoints on Cloud or Kubernetes. Development Methodologies: Proficient in development methodologies and writing unit tests in Python. Cloud: Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud. Experience with information security and secure development best practices. Qualifications Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field. 8+ years in IT with a focus on AI/ML practices and background.

Job Title: AI/ML Engineer Location : Hyderabad Onsite Experience : 5+ years Role Overview We are hiring a Mid-Level AI/ML Engineer with 5+ years of experience in designing, developing, and deploying AI/ML solutions. The role involves integrating LLMs , Agentic AI , RAG pipelines , and anomaly detection into cloud/on-prem platforms, enabling natural language interfaces and intelligent automation. Candidates must be hands-on with Python ML stack, own MLOps lifecycle, and be capable of translating cybersecurity problems into scalable ML solutions. Key Responsibilities LLM & Chatbot Integration : Build conversational AI using LLMs with context-awareness, domain adaptation, and natural language interaction. Retrieval-Augmented Generation (RAG) : Implement vector search with semantic retrieval to ground LLM responses with internal data. Agentic AI : Create autonomous agents to execute multi-step actions using APIs, tools, or reasoning chains for automated workflows. Anomaly Detection & UEBA : Develop ML models for user behaviour analytics, threat detection, and alert tuning. NLP & Insights Generation : Transform user queries into actionable security insights, reports, and policy recommendations. MLOps Ownership : Manage end-to-end model lifecycle – training, validation, deployment, monitoring, versioning. Required Skills Strong Python experience with ML frameworks: TensorFlow, PyTorch, scikit-learn . Hands-on with LLMs (OpenAI, HuggingFace, etc.), prompt engineering, fine-tuning, and inference optimization. Experience implementing RAG using FAISS , Pinecone , or similar. Familiarity with LangChain , agentic frameworks , and multi-agent orchestration. Solid understanding of MLOps : Docker, CI/CD, deployment on cloud/on-prem infra. Security-conscious development practices and ability to work with structured/unstructured security data. Preferred Bachelor’s degree in computer science and more preferably Data Science or AI related fields. Experience with cybersecurity use cases: CVE analysis, behaviour analytics, compliance, log processing. Knowledge of open-source LLMs (LLaMA, Mistral, etc.) and cost-efficient deployment methods. Background in chatbots, Rasa, or custom NLP-driven assistants. Exposure to agent tools (LangChain Agents, AutoGPT-style flows) and plugin integration.

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI, and autonomous intelligent systems. We create intelligent, user-first digital products that redefine industries through the power of AI and engineering excellence. We are looking for a Senior Software Engineer-AI with 4-6 years of hands-on experience in Artificial Intelligence/ML and a passion for innovation. This role is ideal for someone who thrives in a startup environment, fast-paced, product-driven, and full of opportunities to make a real impact. You will contribute to building intelligent, scalable, and production-grade AI systems, with a strong focus on Generative AI and Agentic AI technologies. As a Senior Software Engineer-AI at Techvantage.ai, you will be responsible for building and deploying AI-driven applications and services, focusing on Generative AI and Large Language Models (LLMs). You will design and implement Agentic AI systemsautonomous agents capable of planning and executing multi-step tasks. Collaborate with cross-functional teams including product, design, and engineering to integrate AI capabilities into products. Write clean, scalable code and build robust APIs and services to support AI model deployment. Own feature delivery end-to-endfrom research and experimentation to deployment and monitoring. Stay current with emerging AI frameworks, tools, and best practices and apply them in product development. Contribute to a high-performing team culture and mentor junior team members as needed. In order to excel in this role, we are seeking candidates with 3-6 years of overall software development experience, with at least 3 years specifically in AI/ML engineering. Strong proficiency in Python is required, along with hands-on experience in PyTorch, TensorFlow, and Transformers (Hugging Face). Proven experience working with LLMs (e.g., GPT, Claude, Mistral) and Generative AI models (text, image, or audio) is highly desirable. Practical knowledge of Agentic AI frameworks (e.g., LangChain, AutoGPT, Semantic Kernel) is a plus. Experience building and deploying ML models to production environments is essential. Familiarity with vector databases (Pinecone, Weaviate, FAISS) and prompt engineering concepts is beneficial. Comfortable working in a startup-like environment is crucialself-motivated, adaptable, and willing to take ownership. A solid understanding of API development, version control, and modern DevOps/MLOps practices is expected from the ideal candidate.,

Job Summary Job Description: Generative AI Engineer 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 and 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 5–9 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 ideation to working demo. Work Location : Bangalore (Mandatory to go to office daily) Experience : 5 to 9 years

Job Summary We are looking for a hands-on Data Scientist with deep expertise in NLP and Generative AI to help build and refine the intelligence behind our agentic AI systems. You will be responsible for fine- tuning, prompt engineering, and evaluating LLMs that power our digital workers across real-world workflows. Years of Experience 3 - 6 Years Budget 18 LPA to 24 LPA Location Chennai Immediate to 30 days Key Responsibilities · Fine-tune and evaluate LLMs (e.g., Mistral, LLaMA, Qwen) using frameworks like Unsloth, HuggingFace, and DeepSpeed · Develop high-quality prompts and RAG pipelines for few-shot and zero-shot performance · Analyze and curate domain-specific text datasets for training and evaluation · Conduct performance and safety evaluation of fine-tuned models · Collaborate with engineering teams to integrate models into agentic workflows · Stay up to date with the latest in open-source LLMs and GenAI tools, and rapidly prototype experiments · Apply efficient training and inference techniques (LoRA, QLoRA, quantization, etc.) Requirements · 3+ years of experience in Natural Language Processing (NLP) and machine learning applied to text · Strong coding skills in python · Hands-on experience fine-tuning LLMs (e.g., LLaMA, Mistral, Falcon, Qwen) using frameworks like Unsloth, HuggingFace Transformers, PEFT, LoRA, QLoRA, bitsandbytes · Proficient in PyTorch (preferred) or TensorFlow, with experience in writing custom training/evaluation loops · Experience in dataset preparation, tokenization (e.g., Tokenizer, tokenizers), and formatting for instruction tuning (ChatML, Alpaca, ShareGPT formats) · Familiarity with retrieval-augmented generation (RAG) using FAISS, Chroma, Weaviate, or Qdrant · Strong knowledge of prompt engineering, few-shot/zero-shot learning, chain-of-thought prompting, and function-calling patterns · Exposure to agentic AI frameworks like CrewAI, Phidata, LangChain, LlamaIndex, or AutoGen · Experience with GPU-accelerated training/inference and libraries like DeepSpeed, Accelerate, Flash Attention, Transformers v2, etc. · Solid understanding of LLM evaluation metrics (BLEU, ROUGE, perplexity, pass@k) and safety- related metrics (toxicity, bias) · Ability to work with open-source checkpoints and formats (e.g., safetensors, GGUF, HF Hub, GPTQ, ExLlama) · Comfortable with containerized environments (Docker) and scripting for training pipelines, data curation, or evaluation workflows Nice to Haves · Experience in Linux (Ubuntu) · Terminal/Bash Scripting

FinDocGPT Internship Opportunity – AI/ML & GenAI Developer Intern Company : ArgyleEnigma Tech Labs Product : FinDocGPT – India’s first AI-powered assistant that decodes complex financial documents in simple, regional language Stipend : ₹8,000 – ₹12,000/month Duration : 6 months Start Date : Immediate About Us At FinDocGPT, we are building a revolutionary product that empowers millions of Indians to understand financial documents like health insurance, loans, and mutual fund T&Cs in their own language – using cutting-edge AI/ML and GenAI technologies . We’re backed by Google for Startups, supported by Reserve Bank Innovation Hub and on a mission to bridge the financial literacy gap in India. Intern Role – AI/ML & Generative AI Developer We are looking for highly motivated interns who want to gain hands-on experience in deploying GenAI models, NLP pipelines, and ML-based document processing. Responsibilities Work on document classification , NER , and summarization using LLMs like LLaMA, Mistral, Groq, and open-source models. Fine-tune or use APIs like LangChain, HuggingFace, OpenAI, and Google Vertex AI Preprocess, clean, and structure financial documents (PDFs, scans, emails, etc.) Implement prompt engineering & RAG-based workflows Collaborate with product & design to build smart, user-friendly interfaces Requirements Strong understanding of Python , NLP , and basic ML concepts Familiarity with transformers, BERT, T5, or GPT architectures Experience (even academic) with HuggingFace , LangChain , or LLM APIs Bonus: Exposure to Google Cloud, AWS , or Docker Hunger to learn, experiment fast, and make real impact What You’ll Gain Direct mentorship from industry experts (ex-Morgan Stanley, PIMCO, Google) Real-world exposure to India-first AI use cases Opportunity to convert into full-time role based on performance Work that will directly impact financial inclusion in India How to Apply? Send your CV, GitHub/portfolio, and 2–3 lines on why you want this role to info@arglyeenigma.com or https://tinyurl.com/hr-aetl with subject: “Internship Application – FinDocGPT” Job Type: Internship Contract length: 6 months Pay: ₹8,000.00 - ₹12,000.00 per month Ability to commute/relocate: Gandhinagar, Gujarat: Reliably commute or planning to relocate before starting work (Required) Work Location: In person Expected Start Date: 01/08/2025

About the Role We are seeking a dynamic and experienced Manager – AI to lead the design, development, and deployment of next-generation AI solutions, with a strong focus on Generative AI , Natural Language Processing (NLP) , and Machine Learning (ML) within the pharmaceutical industry. As an AI Manager, you will guide a team of engineers and data scientists, drive project execution, and collaborate closely with product and domain teams. You will be responsible for architecting production-grade systems, mentoring technical talent, and spearheading innovation through applied GenAI. This role combines strategic leadership, technical depth, and hands-on execution—ideal for a candidate passionate about operationalizing cutting-edge AI technologies for real-world impact in life sciences. Key Responsibilities Lead and manage the end-to-end lifecycle of AI/GenAI projects, from scoping and architecture to development, testing, deployment, and optimization. Guide the development of intelligent agents , LLM-powered chatbots , and voice-enabled systems tailored to pharmaceutical and enterprise use cases. Architect context-aware GenAI solutions using RAG (Retrieval-Augmented Generation), embeddings, vector databases, and multimodal models. Oversee fine-tuning of LLMs (e.g., GPT, Claude, LLaMA, Mistral, Phi 4) and drive responsible AI evaluation practices (e.g., hallucination mitigation, prompt robustness). Collaborate with cross-functional stakeholders including product owners, regulatory teams, and business leads to align AI solutions with strategic goals. Lead and mentor a team of AI/ML engineers and researchers, fostering technical growth and high performance. Stay current with emerging trends in GenAI, open-source models, agent frameworks, and voice tech; translate advancements into practical applications. Ensure projects adhere to regulatory , compliance , and data governance standards , particularly in a GxP or HIPAA-compliant environment. Drive innovation culture by piloting proofs-of-concept and scaling successful initiatives across the organization. Requirements Minimum 6+ years of experience in AI/ML/NLP, including at least 3 years in GenAI technologies and team leadership or technical program management. Deep expertise in LLMs/SLMs , including prompt engineering, fine-tuning, and building production-ready GenAI applications. Experience with RAG pipelines , vector search (FAISS, Pinecone, Weaviate), and embedding models. Strong coding skills in Python and experience with frameworks like Hugging Face, LangChain, LanGraph, OpenAI/Anthropic SDKs. Experience with API development , MLOps , and deploying models using containers or cloud-native tools. Proven ability to lead cross-functional teams and translate business needs into scalable AI systems. Strong analytical thinking, problem-solving, and architectural design capabilities. Nice to Have Experience building or integrating voice assistants , speech-to-text APIs , or multimodal GenAI interfaces . Familiarity with agent frameworks (e.g., CrewAI, AutoGen, LangGraph) for autonomous AI workflows. Understanding of regulatory frameworks in life sciences (GxP, HIPAA, GDPR, etc.). Prior exposure to enterprise IT systems in the pharmaceutical or healthcare domain. Educational Qualifications Bachelor’s in Engineering (B.E./B.Tech.) or Master’s in Computer Applications/Technology (MCA/M.Tech.). Certifications or specialization in AI/ML/Data Science are highly desirable. Benefits We Offer Free in-house gym for employee wellness. Exposure to high-impact projects Inclusive, innovation-driven culture with opportunities for career growth and leadership.

AI Engineer Position: 1 Job Title: AI Engineer (Multimodal RAG, Vector Database, and LLM Implementation) Experience Level: Mid to Senior-Level (5-7 Years) Job Overview: We are seeking a highly skilled AI Engineer with expertise in Multimodal Retrieval-Augmented Generation (RAG), Vector databases, and Large Language Model (LLM) implementation. The ideal candidate will have a strong background in integrating structured and unstructured data into AI models and deploying these models in real-world applications. This role involves working on cutting-edge AI solutions, including the development and optimization of multimodal systems that leverage both text and visual data. Key Responsibilities: · Multimodal RAG Implementation: o Design, develop, and deploy Multimodal Retrieval-Augmented Generation (RAG) systems that integrate both structured (e.g., databases, tables) and unstructured data (e.g., text, images, videos). o Work with large-scale datasets, combining different data types to enhance the performance and accuracy of AI models. o Implement and fine-tune LLMs (e.g., GPT, BERT) to work effectively with multimodal inputs and outputs. · Vector Database Integration: o Develop and optimize AI models using vector databases to efficiently manage and retrieve high-dimensional data. o Implement vector search techniques to improve information retrieval from structured and unstructured data sources. o Ensure the scalability and performance of vector-based retrieval systems in production environments. · LLM Implementation and Optimization: o Implement and fine-tune large language models to handle complex queries involving multimodal data. o Optimize LLMs for specific tasks, such as text generation, question answering, and content summarization, using both structured and unstructured data. o Integrate LLMs with vector databases and RAG systems to enhance AI capabilities. · Data Integration and Processing: o Work with data engineers and data scientists to preprocess and integrate structured and unstructured data for AI model training and inference. o Develop data pipelines that handle the ingestion, transformation, and storage of diverse data types. o Ensure data quality and consistency across different data sources and formats. · Model Evaluation and Testing: o Evaluate the performance of multimodal AI models using various metrics, ensuring they meet accuracy, speed, and robustness requirements. o Conduct A/B testing and model validation to continuously improve AI system performance. o Implement automated testing and monitoring tools to ensure model reliability in production. · Collaboration and Communication: o Collaborate with cross-functional teams, including data engineers, data scientists, and software developers, to deliver AI-driven solutions. o Communicate complex technical concepts to non-technical stakeholders and provide insights on the impact of AI models on business outcomes. o Stay up to date with the latest advancements in AI, LLMs, vector databases, and multimodal systems, and share knowledge with the team. Qualifications: · Technical Skills: o Strong expertise in Multimodal Retrieval-Augmented Generation (RAG) systems. o Proficiency in vector databases (e.g., Pinecone, Milvus, Weaviate, Chroma) and vector search techniques with recommender systems, vector search capabilities. o Experience with LLMs (e.g., GPT, BERT) and their implementation in real-world applications. Experience with Mistral AI is a plus. o Solid understanding of machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, MLflow etc). o Experience working with structured data (e.g., SQL databases) and unstructured data (e.g., text, images, videos). o Proficiency in programming languages such as Python, with experience in relevant libraries and tools. · Experience: o 2+ years of experience in AI/ML engineering, with a focus on multimodal systems and LLMs. o Proven track record of deploying AI models in production environments. o Experience with cloud platforms preferably Azure, and MLOps practices is preferred.

FinDocGPT Internship Opportunity – AI/ML & GenAI Developer Intern Company : ArgyleEnigma Tech Labs Product : FinDocGPT – India’s first AI-powered assistant that decodes complex financial documents in simple, regional language Stipend : ₹8,000 – ₹12,000/month Duration : 6 months Start Date : Immediate About Us At FinDocGPT, we are building a revolutionary product that empowers millions of Indians to understand financial documents like health insurance, loans, and mutual fund T&Cs in their own language – using cutting-edge AI/ML and GenAI technologies . We’re backed by Google for Startups, supported by Reserve Bank Innovation Hub and on a mission to bridge the financial literacy gap in India. Intern Role – AI/ML & Generative AI Developer We are looking for highly motivated interns who want to gain hands-on experience in deploying GenAI models, NLP pipelines, and ML-based document processing. Responsibilities Work on document classification , NER , and summarization using LLMs like LLaMA, Mistral, Groq, and open-source models. Fine-tune or use APIs like LangChain, HuggingFace, OpenAI, and Google Vertex AI Preprocess, clean, and structure financial documents (PDFs, scans, emails, etc.) Implement prompt engineering & RAG-based workflows Collaborate with product & design to build smart, user-friendly interfaces Requirements Strong understanding of Python , NLP , and basic ML concepts Familiarity with transformers, BERT, T5, or GPT architectures Experience (even academic) with HuggingFace , LangChain , or LLM APIs Bonus: Exposure to Google Cloud, AWS , or Docker Hunger to learn, experiment fast, and make real impact What You’ll Gain Direct mentorship from industry experts (ex-Morgan Stanley, PIMCO, Google) Real-world exposure to India-first AI use cases Opportunity to convert into full-time role based on performance Work that will directly impact financial inclusion in India How to Apply? Send your CV, GitHub/portfolio, and 2–3 lines on why you want this role to info@arglyeenigma.com or https://tinyurl.com/hr-aetl with subject: “Internship Application – FinDocGPT” Job Type: Internship Contract length: 6 months Pay: ₹8,000.00 - ₹12,000.00 per month Ability to commute/relocate: Gandhinagar, Gujarat: Reliably commute or planning to relocate before starting work (Required) Work Location: In person Expected Start Date: 01/08/2025

Hello, Hope you are doing well. We are Hiring for the role of Sr. AI/ML/ Data Scientist role. Please revert me back with your updated resume at astha.jaiswal@techsciresearch.com if you are interested. Below are the details: Job Location: Noida Job Role: S r. AI/ML/ Data Scientist Overview: We are seeking a highly skilled and experienced AI/ML Expert to spearhead the design, development, and deployment of advanced artificial intelligence and machine learning models. This role requires a strategic thinker with a deep understanding of ML algorithms, model optimization, and production-level AI systems. You will guide cross-functional teams, mentor junior data scientists, and help shape the AI roadmap to drive innovation and business impact. This role involves statistical analysis, data modeling, and interpreting large sets of data. An AI/ML expert with experience in creating AI models for data intelligence companies who specializes in developing and deploying artificial intelligence and machine learning solutions tailored for data-driven businesses. This expert should possess a strong background in data analysis, statistics, programming, and machine learning algorithms, enabling them to design innovative AI models that can extract valuable insights and patterns from vast amounts of data. About the Role The design and development of a cutting-edge application powered by large language models (LLMs). This tool will provide market analysis and generate high-quality, data-driven periodic insights. You will play a critical role in building a scalable and intelligent system that integrates structured data, NLP capabilities, and domain-specific knowledge to produce analyst-grade content. Key Responsibilities Design and develop LLM-based systems for automated market analysis. Build data pipelines to ingest, clean, and structure data from multiple sources (e.g., market feeds, news articles, technical reports, internal datasets). Fine-tune or prompt-engineer LLMs (e.g., GPT-4.5, Llama, Mistral) to generate concise, insightful reports. Collaborate closely with domain experts to integrate industry-specific context and validation into model outputs. Implement robust evaluation metrics and monitoring systems to ensure quality, relevance, and accuracy of generated insights. Develop and maintain APIs and/or user interfaces to enable analysts or clients to interact with the LLM system. Stay up to date with advancements in the GenAI ecosystem and recommend relevant improvements or integrations. Participate in code reviews, experimentation pipelines, and collaborative research discussions. Qualifications Required: Strong fundamentals in machine learning, deep learning, and natural language processing (NLP) . Proficiency in Python , with hands-on experience using libraries such as NumPy, Pandas, and Matplotlib/Seaborn for data analysis and visualization. Experience developing applications using LLMs (both closed- and open-source models) . Familiarity with frameworks like Hugging Face Transformers, LangChain, LlamaIndex , etc. Experience building ML models (e.g., Random Forest, XGBoost, LightGBM, SVMs ), along with familiarity in training and validating models. Practical understanding of deep learning frameworks: TensorFlow or PyTorch . Knowledge of prompt engineering , Retrieval-Augmented Generation (RAG) , and LLM evaluation strategies. Experience working with REST APIs , data ingestion pipelines, and automation workflows. Strong analytical thinking, problem-solving skills, and the ability to convert complex technical work into business-relevant insights. Preferred: Familiarity with the chemical or energy industry , or prior experience in market research/analyst workflows . Exposure to frameworks such as OpenAI Agentic SDK, CrewAI, AutoGen, SmolAgent, etc. Experience deploying ML/LLM solutions to production environments (Docker, CI/CD) . Hands-on experience with vector databases such as FAISS, Weaviate, Pinecone , or ChromaDB . Experience with dashboarding tools and visualization libraries (e.g., Streamlit, Plotly, Dash, or Tableau). Exposure to cloud platforms (AWS, GCP, or Azure), including usage of GPU instances and model hosting services. About ChemAnalyst : ChemAnalyst is a digital platform, which keeps a real-time eye on the chemicals and petrochemicals market fluctuations, thus, enabling its customers to make wise business decisions. With over 450 chemical products traded globally, we bring detailed market information and pricing data at your fingertips. Our real-time pricing and commentary updates enable users to stay acquainted with new commercial opportunities. Each day, we flash the major happenings around the globe in our news section. Our market analysis section takes it a step further, offering an in-depth evaluation of over 15 parameters including capacity, production, supply, demand gap, company share and among others. Our team of experts analyse the factors influencing the market and forecast the market data for up to the next 10 years. We are a trusted source of information for our international clients, ensuring user-friendly and customized deliveries on time. Website : https://www.chemanalyst.com/

We are seeking a highly skilled and experienced Senior Data Scientist with deep expertise in Large Language Models (LLMs) and a strong background in healthcare AI applications. You'll work on building intelligent, scalable solutions that enhance patient care, streamline systems, and shape the future of healthcare technology. Key Responsibilities LLM Application Development Design, develop, and deploy robust LLM-based healthcare applications. Ensure seamless integration with healthcare systems and clinical workflows. Model Expertise Work with open-source models such as LLaMA 2, Mistral, etc. Fine-tune and customize models for domain-specific healthcare use cases. Tool Proficiency Use LangChain, LlamaIndex, and similar frameworks to build intelligent solutions. Implement RAG (retrieval-augmented generation) and knowledge-graph strategies as needed. Problem Solving & Innovation Tackle real-world healthcare challenges using cutting-edge NLP and AI techniques. Deliver measurable outcomes in patient care and operational Collaboration : Partner with engineering, product, and clinical teams to ensure alignment with business goals. Communicate technical insights clearly to both technical and non-technical Learning : Stay up to date with the latest developments in LLMs and healthcare AI. Experiment with new models, methodologies, and tools. Required Skills & Qualifications 8+ years of experience in data science or AI development. Proven work with LLMs in healthcare-related projects. Hands-on experience with LLaMA 2, Mistral, LangChain, LlamaIndex, etc. Familiarity with EMR/EHR systems, healthcare datasets, and APIs. Proficient in Python and experienced with AI/LLM integration pipelines. Strong analytical, documentation, and communication skills. Preferred Qualifications Built or contributed to clinical decision support, patient engagement, or medical research tools. Experience with MIMIC-III, HL7 FHIR, or other clinical datasets. Knowledge of healthcare compliance (e.g., HIPAA, FDA). Cloud experience (AWS, GCP, Azure) and model deployment pipelines. Understanding of prompt engineering, RAG pipelines, and evaluation frameworks. Benefits Competitive salary + performance-based bonuses Remote-first culture with flexible working hours Health insurance and paid time off Access to AI/LLM learning resources and certifications Opportunities to work on impactful, real-world healthcare projects Collaborative and mission-driven team environment (ref:hirist.tech)

Title : GenAI Engineer Location : Bengaluru, Chennai, Hyderabad, Pune, Vadodara, Gujarat Years of Exp : 7 to 12 Years Employment Type : Full-time Key Responsibilities Architect and develop Generative AI-based applications using Azure OpenAI, Azure ML Studio, Azure Cognitive Search, and Azure Document Intelligence. Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise search, knowledge management, and domain-specific Q&A systems. Integrate Large Language Models (LLMs) into production applications with attention to performance, scalability, and governance. Design intelligent workflows using LangChain, LlamaIndex, and Semantic Kernel for orchestrating multi-step AI interactions and agent behaviors. Collaborate with data scientists, ML engineers, and DevOps to deploy, monitor, and manage cloud-native AI solutions. Incorporate OCR capabilities and document understanding pipelines using Azure Form Recognizer and Document Intelligence. Ensure AI models and pipelines comply with enterprise standards, data privacy, and responsible AI principles. Lead proof-of-concepts (PoCs), rapid prototypes, and solution demos to validate GenAI use cases across departments. Maintain a strong understanding of evolving LLM architectures, foundation models, and emerging GenAI techniques. Contribute to technical documentation, best practices, and reusable solution accelerators. Required Qualifications Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proven Experience With Azure AI Services, Including Azure OpenAI Azure Machine Learning Studio Azure Cognitive Search Azure Form Recognizer / Document Intelligence Strong Python development skills, especially in the context of LLM pipelines and prompt engineering. Expertise with GenAI libraries and tools such as: LangChain LlamaIndex Semantic Kernel Familiarity with RAG architecture, vector databases (e.g., FAISS, Redis, Azure Cognitive Search), and embedding models. Experience with containerization (Docker) and cloud-native deployment pipelines using Azure DevOps, Kubernetes, or Terraform. Understanding of Responsible AI principles, including bias mitigation, explainability, and model monitoring. Excellent problem-solving and communication skills; ability to work in cross-functional agile teams. Preferred Qualifications Experience integrating agent-based frameworks for autonomous task execution and multi-agent collaboration. Knowledge of other GenAI ecosystems like Hugging Face Transformers, Anthropic Claude, or Mistral models. Background in enterprise content management, knowledge graphs, or intelligent document processing (IDP). Azure Certifications Such As Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Azure Solutions Architect Expert What We Offer Opportunity to work on groundbreaking AI initiatives at enterprise scale. Collaborative, fast-paced, and innovation-driven team culture. Flexible work arrangements (remote/hybrid). Competitive compensation, equity options, and comprehensive benefits. (ref:hirist.tech)

We’re building an Agentic AI Platform that lets enterprises solve real business problems using Agentic AI workflows. From utility operations to legal document review; our mission is to let AI agents think, act, and deliver; fast, secure and locally. We’re looking for an Agentic AI Engineer who’s hungry to learn and ship. If you’re ready to build with cutting-edge frameworks like Lang Chain, CrewAI, Lang Graph, Google ADK and more and can translate real enterprise problems into intelligent multi-agent workflows, this role is for you. What You’ll Do Build and deploy AI agents using open-source agentic frameworks Explore and integrate models from OpenAI, Mistral, Gemini, Llama, Claude, etc. Use tools like Retrieval-Augmented Generation (RAG), knowledge graphs, and vector stores Work with product managers and domain experts to solve real problems (not just prototypes) Continuously test and refine agent behavior across different enterprise domains (utilities, legal, marketing, supply chain) Actively contribute to evolving our proprietary DataInsightAI platform Must-Have Skills At least 1+ years of hands-on experience implementing a enterprise level Gen AI project that has gone live. Strong Python skills (Async, FastAPI, LangChain/CrewAI or similar) Experience working with LLMs (OpenAI, Llama, Claude, Gemini, etc.) Familiar with agentic AI workflows, prompt chaining, and tool use Understanding of RAG, vector databases (like FAISS, Qdrant, Weaviate) Curiosity-driven mindset, fast learner, hands-on coder Ability to simplify complex problems and build MVPs fast Nice to Have Worked on multi-agent architectures or fine-tuned LLMs Used graph databases (Neo4j) or custom knowledge stores Experience deploying on Azure/AWS/GCP Familiarity with LangGraph or Google ADK Why Join Us? Work on cutting-edge agentic AI every day Be part of a lean team with real ownership Ship fast and solve real enterprise challenges Backed by InTimeTec, with a strong AI/ML engineering culture

Analytics Posted on Jul 22, 2025 Vadodara-Gujarat Minimum Required Experience : 3 years Full Time Skills Machine Learning TensorFlow Pytorch NLP Description Designation/Role Name Machine Learning Engineer Org Structure Data Science & AI Team Work Schedule According to the business needs Job Description With excellent analytical and problem-solving skills, you should understand business problems of the customers, translate them into scope of work and technical specifications for developing into Data Science projects. Efficiently utilize cutting edge technologies in AI areas (Machine Learning, NLP, Computer Vision) and development of solutions for business problems. Good exposure technology platforms for Data Science, AI, Gen AI, cloud with implementation experience. Ability to understand data, requirements, design and develop a Machine Learning Model for the requirements. This Job requires the following: Designing, developing, and implementing end-to-end machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation) Experience in predictive analytics and statistical modeling Experience in successfully making use of the following: Logistic Regression Multivariate Regression, Support Vector Machines, Stochastic Processes, Decision Trees, Lifetime analysis, common clustering algorithms, Optimization, CNN Essential Qualifications B-Tech or BE - computer / IT or MCA or MSC- Computer Science along with necessary certifications is preferred Technical Qualifications (Essential) Hands-on programming experience Hands-on technical design experience Hands-on prompt engineering experience Design and Development of at least 3 Data Science, AI Projects with design and development of Machine Learning models 1 Generative AI Project designed, developed and delivered to production is desirable Primary Skills Hands-on coding experience in Python, PyTorch, Spark/PySpark, SQL, TensorFlow, NLP Frameworks and similar tools/frameworks Good understanding of business and domain of the applications Hands-on experience in design and development of Gen AI applications using Open Source LLMs and cloud platforms Hands-on experience in design and development of API based applications for AI and Data Science Projects Understanding in GenAI concepts, RAG and Models fine-tuning techniques is desirable Understand the concepts of major AI models such as OpenAI, Llama, Hugging Face, Mistral AI etc., Understanding of DevOps pipelines for deployment Good understanding of Data Engineering lifecycle – data pipelines, data warehouse, data lake Secondary Skills Experience using Databricks and Azure Data platform Knowledge of any configuration management tools is desirable Familiarity with containerization and container orchestration services like Docker and Kubernetes Experience 3+ years in Machine Learning Model development in Data Science/AI Projects. Awareness of LLM integrations / development is desirable. Description of Responsibility Understand customer’s requirements (Business, Functional, Non-Functional etc.,), design and develop Machine Learning Models Design and implement Machine Learning Models using major technology and computing platforms (open source and cloud) Possess excellent analytical and problem-solving skills and be able to understand various forms of data, patterns and derive insights. Collaborate internal and external stakeholders for deriving solution that requires cross functional teams and smoother execution of the projects Knowledge of data modeling and understanding of different data structures Experience with design of AI/ML solutions either as standalone or integrated with other applications Experience in Generative AI solutions for the business/automation requirements using open source LLMs (Open AI, LLama, Mistral etc.,) is desirable Sills / Competencies requirement Research Orientation Proactive & Clear Communication Collaboration Solution Orientation Solution Articulation Accountability Adaptability / Flexibility Analytical Skills Listening Skills Customer Service Orientation

Job Description Experience in SonarQube, CICD, Tekton, terraform, GCS, GCP Looker, Google cloud build, cloud run, Vertex AI, Airflow, TensorFlow, etc., Experience in Train, Build and Deploy ML, DL Models Experience in HuggingFace, Chainlit, React Ability to understand technical, functional, non-functional, security aspects of business requirements and delivering them end-to-end. Ability to adapt quickly with opensource products & tools to integrate with ML Platforms Building and deploying Models (Scikit learn, DataRobots, TensorFlow PyTorch, etc.) Developing and deploying On-Prem & Cloud environments Kubernetes, Tekton, OpenShift, Terraform, Vertex AI Experience in LLM models like PaLM, GPT4, Mistral (open-source models), Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring. Developing and maintaining AI pipelines with multimodalities like text, image, audio etc. Have implemented in real-world Chat bots or conversational agents at scale handling different data sources. Experience in developing Image generation/translation tools using any of the latent diffusion models like stable diffusion, Instruct pix2pix. Expertise in handling large scale structured and unstructured data. Efficiently handled large-scale generative AI datasets and outputs. Familiarity in the use of Docker tools, pipenv/conda/poetry env Comfort level in following Python project management best practices (use of cxzsetup.py, logging, pytests, relative module imports,sphinx docs,etc.,) Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.,) High familiarity in the use of DL theory/practices in NLP applications Comfort level to code in Huggingface, LangChain, Chainlit, Tensorflow and/or Pytorch, Scikit-learn, Numpy and Pandas Comfort level to use two/more of open source NLP modules like SpaCy, TorchText, fastai.text, farm-haystack, and others Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, segmenting noisy unfamiliar sentences/phrases at right places, deriving insights from clustering, etc.,) Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification, NER or QA) from data preparation, model creation and inference till deployment Use of GCP services like BigQuery, Cloud function, Cloud run, Cloud Build, VertexAI, Good working knowledge on other open source packages to benchmark and derive summary Experience in using GPU/CPU of cloud and on-prem infrastructures Skillset to leverage cloud platform for Data Engineering, Big Data and ML needs. Use of Dockers (experience in experimental docker features, docker-compose, etc.,) Familiarity with orchestration tools such as airflow, Kubeflow Experience in CI/CD, infrastructure as code tools like terraform etc. Kubernetes or any other containerization tool with experience in Helm, Argoworkflow, etc., Ability to develop APIs with compliance, ethical, secure and safe AI tools. Good UI skills to visualize and build better applications using Gradio, Dash, Streamlit, React, Django, etc., Deeper understanding of javascript, css, angular, html, etc., is a plus. Responsibilities Design NLP/LLM/GenAI applications/products by following robust coding practices, Explore SoTA models/techniques so that they can be applied for automotive industry usecases Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions, Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.,) Converge multibots into super apps using LLMs with multimodalities Develop agentic workflow using Autogen, Agentbuilder, langgraph Build modular AI/ML products that could be consumed at scale. Qualifications Education : Bachelor’s or Master’s Degree in Computer Science, Engineering, Maths or Science Performed any modern NLP/LLM courses/open competitions is also welcomed.