653 Mistral Jobs - Page 12

Remote What We Offer: Canteen Subsidy Night Shift allowance as per process Health Insurance Tuition Reimbursement Work-Life Balance Initiatives Rewards & Recognition What You’ll Be Doing: Design, build, and deploy LLM-driven applications (e.g., document summarization, RAG-based QA, chatbots). Work with open-source LLMs using platforms like Ollama and Hugging Face. Implement Lang Chain and Lang Graph workflows for multi-step, multi-agent task resolution. Build and optimize RAG (Retrieval-Augmented Generation) systems using vector databases. Collaborate with cross-functional teams to ship features to production. Stay up to date with the latest in open-source LLMs, model optimization (LoRA, quantization), and multi-modal AI. What We Expect You To Have: 3–5 years of hands-on experience in AI/ML engineering. Proficient in Python, PyTorch, and Hugging Face Transformers. Proven experience with Lang Chain and Lang Graph for LLM workflows. Familiarity with Ollama, Mistral, LLaMA, or similar open-source LLMs. Experience working with vector stores (Qdrant, Pinecone, Weaviate, FAISS). Skilled in backend integration using FastAPI, Docker, and cloud platforms. Solid grasp of NLP, LLM reasoning, prompt engineering, and document parsing. Experience with LangServe, OpenAI tool/function calling, or agent orchestration. Background in multi-modal AI (e.g., image + text analysis). Familiarity with MLOps tools (MLflow, Weights & Biases, Airflow). Contributions to open-source GenAI projects. Understanding LLM safety, security, and alignment principles. Job Title : AI Engineer Location : Gandhinagar Schedule & Shift : 2:30 PM to 11:30 PM IST

Key Responsibilities: Fine-tune and deploy LLMs (e.g., GPT, LLaMA, Mistral) using frameworks like Hugging Face Transformers and LangChain. Build and optimize RAG pipelines with vector databases (e.g., Pinecone, FAISS, Weaviate). Engineer prompts for structured and reliable outputs across diverse use cases such as chatbots, summarization tools, and coding assistants. Implement scalable inference pipelines; optimize for latency, throughput, and cost using quantization, distillation, and other model optimization techniques. Collaborate with product, design, and engineering teams to integrate generative AI capabilities into user-facing features. Monitor and improve model performance, accuracy, safety, and compliance in production. Ensure responsible AI practices through content filtering, output sanitization, and ethical deployment. Required Skills: Proficiency in Python and familiarity with modern machine learning tools and libraries. Hands-on experience with LLM development using Hugging Face Transformers, LangChain, or LlamaIndex. Experience building and deploying RAG pipelines, including managing embeddings and vector search. Strong understanding of transformer architectures, tokenization, and prompt engineering techniques. Comfortable working with LLM APIs (e.g., OpenAI, Anthropic, Cohere) and serving models with FastAPI, Flask, or similar frameworks. Familiarity with deploying ML systems using Docker, Kubernetes, and cloud services (AWS, GCP, Azure). Experience with model evaluation, logging, and inference pipeline troubleshooting. Nice to Have: Exposure to multimodal models (e.g., text-to-image, video generation, TTS). Experience with reinforcement learning from human feedback (RLHF) or alignment techniques. Familiarity with open-source LLMs (e.g., Mistral, Mixtral, LLaMA, Falcon) and optimization tools (LoRA, quantization, PEFT). Knowledge of LangChain agents, tool integration, and memory management. Contributions to open-source GenAI projects, public demos, or blogs in the generative AI space. Basic proficiency in frontend development (e.g., React, Next.js) for rapid prototyping.

Hi all , we are looking for a role AI Engineer experience : 3 - 6 years notice period : Immediate - 15 days location : Bengaluru Generative AI Engineer Position Overview: We are looking for a Generative AI Engineer with expertise in Azure OpenAI and hands-on experience with models such as GPT-4o, GPT-o1, and open source LLMs like Llama, mistral. You will work on GenAI solutions development, RAG, fine-tuning, and deploying resources in Azure environment. Proficiency in prompt engineering, Python, PostgreSQL, FastAPI, Streamlit, Django and Angular is essential. This role also requires strong skills in AI models orchestration using intent mapping, Semantic Kernel or function calling, along with proficiency in presentation and public speaking. Key Responsibilities: • RAG, fine-tune, and deploy Azure OpenAI models (e.g., GPT-4o, GPT-o1) and other open-source large language models (LLMs). • Build AI-powered applications using frameworks such as FastAPI, Streamlit, Django, and Angular. • Design and execute AI workflows using tools like prompt flow, Semantic Kernel and implement function calling for complex use cases. • Conduct prompt engineering to improve model performance for specific business cases. • Visualize data and create user interaction insights using Power BI. • Ensure smooth deployment and maintenance of models on Azure cloud infrastructure, including scalability and optimization. • Prepare and deliver presentations, demos, and technical documentation to internal and external stakeholders. • Stay updated with advancements in generative AI, NLP, and machine learning to continuously improve models and methodologies. Required Skills & Qualifications: • Bachelors degree in Computer science, Artificial intelligence, Machine learning, or related field. • At least 2+ year of hands-on experience working on generative AI projects. • Strong expertise in Azure OpenAI models (GPT-4o, GPT-3.5, GPT-o1 etc.). • Proficient in Prompt Engineering, Python, Streamlit, Django, FastAPI, and Angular. • Basics of html, css, javascript, typescript and angular. • Basic understanding of neural networks, machine and transformer architectures. • Experience in retrieval-augmented generation (RAG) and fine-tuning Large language models. • Familiarity with AI model orchestration tools such as Semantic Kernel, intent mapping and function calling techniques. • Excellent public speaking and presentation skills to convey technical concepts to business stakeholders. • Azure Certified AZ900 or AI900 Preferred Qualifications: • Masters degree in Artificial Intelligence, Machine Learning, or related field. • At least 3+ years of experience working on generative AI, NLP, and machine learning projects. • Strong understanding of neural networks, machine learning and transformer architectures. • Implemented GenAI solutions in production. • Familiarity with Automotive Industry • Hands on experience in RAG, RAFT and optimized fine-tuning. • Azure Certified AI-102, DP-100, AZ-204 or DP-203

Company Description Quantanite is a customer experience (CX)solutions company that helpsfast-growing companies and leading global brandsto transformand grow. We do thisthrough a collaborative and consultative approach,rethinking business processes and ensuring our clients employ the optimalmix of automationand human intelligence.We are an ambitiousteamof professionals spread acrossfour continents and looking to disrupt ourindustry by delivering seamless customerexperiencesforour clients,backed-upwithexceptionalresults.We havebig dreams, and are constantly looking for new colleaguesto join us who share our values, passion and appreciationfordiversity. Job Description About the Role: We are seeking a highly skilled Senior AI Engineer with deep expertise in Agentic frameworks, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, MLOps/LLMOps, and end-to-end GenAI application development. In this role, you will design, develop, fine-tune, deploy, and optimize state-of-the-art AI solutions across diverse enterprise use cases including AI Copilots, Summarization, Enterprise Search, and Intelligent Tool Orchestration. Key Responsibilities: Develop and Fine-Tune LLMs (e.g., GPT-4, Claude, LLaMA, Mistral, Gemini) using instruction tuning, prompt engineering, chain-of-thought prompting, and fine-tuning techniques. Build RAG Pipelines: Implement Retrieval-Augmented Generation solutions leveraging embeddings, chunking strategies, and vector databases like FAISS, Pinecone, Weaviate, and Qdrant. Implement and Orchestrate Agents: Utilize frameworks like MCP, OpenAI Agent SDK, LangChain, LlamaIndex, Haystack, and DSPy to build dynamic multi-agent systems and serverless GenAI applications. Deploy Models at Scale: Manage model deployment using HuggingFace, Azure Web Apps, vLLM, and Ollama, including handling local models with GGUF, LoRA/QLoRA, PEFT, and Quantization methods. Integrate APIs: Seamlessly integrate with APIs from OpenAI, Anthropic, Cohere, Azure, and other GenAI providers. Ensure Security and Compliance: Implement guardrails, perform PII redaction, ensure secure deployments, and monitor model performance using advanced observability tools. Optimize and Monitor: Lead LLMOps practices focusing on performance monitoring, cost optimization, and model evaluation. Work with AWS Services: Hands-on usage of AWS Bedrock, SageMaker, S3, Lambda, API Gateway, IAM, CloudWatch, and serverless computing to deploy and manage scalable AI solutions. Contribute to Use Cases: Develop AI-driven solutions like AI copilots, enterprise search engines, summarizers, and intelligent function-calling systems. Cross-functional Collaboration: Work closely with product, data, and DevOps teams to deliver scalable and secure AI products. Qualifications Required Skills and Experience: 3-5 years of experience in AI/ML roles, focusing on LLM agent development, data science workflows, and system deployment. Demonstrated experience in designing domain-specific AI systems and integrating structured/unstructured data into AI models. Proficiency in designing scalable solutions using LangChain and vector databases. Deep knowledge of LLMs and foundational models (GPT-4, Claude, Mistral, LLaMA, Gemini). Strong expertise in Prompt Engineering, Chain-of-Thought reasoning, and Fine-Tuning methods. Proven experience building RAG pipelines and working with modern vector stores (FAISS, Pinecone, Weaviate, Qdrant). Hands-on proficiency in LangChain, LlamaIndex, Haystack, and DSPy frameworks. Model deployment skills using HuggingFace, vLLM, Ollama, and handling LoRA/QLoRA, PEFT, GGUF models. Practical experience with AWS serverless services: Lambda, S3, API Gateway, IAM, CloudWatch. Strong coding ability in Python or similar programming languages. Experience with MLOps/LLMOps for monitoring, evaluation, and cost management. Familiarity with security standards: guardrails, PII protection, secure API interactions. Use Case Delivery Experience: Proven record of delivering AI Copilots, Summarization engines, or Enterprise GenAI applications. Additional Information Preferred Skills: Experience in BPO or IT Outsourcing environments. Knowledge of workforce management tools and CRM integrations. Hands-on experience with AI technologies and their applications in data analytics. Familiarity with Agile/Scrum methodologies. Soft Skills: Strong analytical and problem-solving capabilities. Excellent communication and stakeholder management skills. Ability to thrive in a fast-paced, dynamic environment.

About The Role PubMatic is seeking Data Analytics focused Senior Software Engineers with expertise in building and optimizing AI agents, including strong skills in Hadoop, Spark, Scala, Kafka, Spark Streaming, and cloud-based solutions, with proficiency in programming languages such as Scala and Python. You will be responsible for developing advanced AI agents that enhance our data analytics capabilities, enabling our platform to handle complex information retrieval, contextual understanding, and adaptive interactions, ultimately improving our data-driven insights and analytical workflows What You’ll Do Build, design, and implement our highly scalable, fault-tolerant big data platform to process terabytes of data and provide customers with in-depth analytics. Develop backend services using Java, REST APIs, JDBC, and AWS. Build and maintain Big Data pipelines using technologies like Spark, Hadoop, Kafka, and Snowflake. Architect and implement real-time data processing workflows and automation frameworks. Design and develop GenAI-powered agents for analytics, operations, and data enrichment use cases using frameworks like LangChain, LlamaIndex, or custom orchestration systems. Integrate LLMs (e.g., OpenAI, Claude, Mistral) into existing services for query understanding, summarization, and decision support. Manage end-to-end GenAI workflows including prompt engineering, fine-tuning, vector embeddings, and retrieval-augmented generation (RAG). Working closely with cross-functional teams on improving the availability and scalability of large data platforms and the functionality of PubMatic software. Participate in Agile/Scrum processes such as sprint planning, sprint retrospective, backlog grooming, user story management, and work item prioritization. Frequently discuss with product managers about the software features to include in the PubMatic Data Analytics platform. Support customer issues over email or JIRA (bug tracking system), provide updates, and patches to customers to fix the issues. Perform code and design reviews for code implemented by peers or as per the code review process. We’d Love for You to Have Three plus years of coding experience in Java and backend development. Solid computer science fundamentals, including data structure and algorithm design, and creation of architectural specifications. Expertise in developing the Implementation of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews. Hands-on experience with Big Data tools and systems like Scala Spark, Kafka, Hadoop, Snowflake. Proven expertise in building GenAI applications, including: LLM integration (OpenAI, Anthropic, Cohere, etc.) LangChain, or similar agent orchestration libraries Prompt engineering, embeddings, and retrieval-based generation (RAG) Experience in developing and deploying scalable, production-grade AI or data systems. Ability to lead end-to-end feature development and debug distributed systems. Experience in developing and delivering large-scale big data pipelines, real-time systems & data warehouses would be preferred. Demonstrated ability to achieve stretch goals in a very innovative and fast-paced environment. Demonstrated ability to learn new technologies quickly and independently. Excellent verbal and written communication skills, especially in technical communications. Strong interpersonal skills and a desire to work collaboratively. Qualifications Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities. Additional Information Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

Key Responsibilities: Fine-tune and deploy LLMs (e.g., GPT, LLaMA, Mistral) using frameworks like Hugging Face Transformers and LangChain. Build and optimize RAG pipelines with vector databases (e.g., Pinecone, FAISS, Weaviate). Engineer prompts for structured and reliable outputs across diverse use cases such as chatbots, summarization tools, and coding assistants. Implement scalable inference pipelines; optimize for latency, throughput, and cost using quantization, distillation, and other model optimization techniques. Collaborate with product, design, and engineering teams to integrate generative AI capabilities into user-facing features. Monitor and improve model performance, accuracy, safety, and compliance in production. Ensure responsible AI practices through content filtering, output sanitization, and ethical deployment. Required Skills: Proficiency in Python and familiarity with modern machine learning tools and libraries. Hands-on experience with LLM development using Hugging Face Transformers, LangChain, or LlamaIndex. Experience building and deploying RAG pipelines, including managing embeddings and vector search. Strong understanding of transformer architectures, tokenization, and prompt engineering techniques. Comfortable working with LLM APIs (e.g., OpenAI, Anthropic, Cohere) and serving models with FastAPI, Flask, or similar frameworks. Familiarity with deploying ML systems using Docker, Kubernetes, and cloud services (AWS, GCP, Azure). Experience with model evaluation, logging, and inference pipeline troubleshooting. Nice to Have: Exposure to multimodal models (e.g., text-to-image, video generation, TTS). Experience with reinforcement learning from human feedback (RLHF) or alignment techniques. Familiarity with open-source LLMs (e.g., Mistral, Mixtral, LLaMA, Falcon) and optimization tools (LoRA, quantization, PEFT). Knowledge of LangChain agents, tool integration, and memory management. Contributions to open-source GenAI projects, public demos, or blogs in the generative AI space. Basic proficiency in frontend development (e.g., React, Next.js) for rapid prototyping.

Company Overview We are a fast-growing research firm with a global footprint, addressing major market, strategic, economic, scientific, and technological developments for business leaders in industrial, pharmaceutical, and technology organizations. We provides comprehensive analysis of global market sizing, forecasting, and industry intelligence, covering markets where advances in science and technology are improving the quality, standard, and sustainability of businesses, economies, and lives. We are in the process of retooling the business for next-generation innovative online and AI-powered products. Job Summary We are seeking a skilled Agentic AI Technical Engineer to design, develop, and implement AI-powered solutions that enhance our market research and industry intelligence offerings. This role requires hands-on expertise in agentic AI systems, proficiency in machine learning frameworks, and the ability to collaborate on innovative online platforms. The ideal candidate will build autonomous, goal-oriented AI agents to deliver actionable insights for clients in industrial, pharmaceutical, and technology sectors. Key Responsibilities System Development : Design and develop agentic AI systems, implementing reinforcement learning, natural language processing, and multi-agent coordination to support market analysis and forecasting. Model Implementation : Build, train, and deploy AI models that process complex datasets, delivering accurate and actionable insights for market research applications. Technical Collaboration : Work closely with AI engineers, data scientists, and product teams to integrate AI solutions into client-facing platforms and ensure seamless functionality. Research and Innovation : Apply advancements in agentic AI and machine learning to create cutting-edge tools for market sizing, forecasting, and industry intelligence. Performance Optimization : Optimize AI models for scalability, accuracy, and real-time performance, ensuring efficient data processing in production environments. Data Pipeline Development : Build and maintain data pipelines to support AI-driven analytics, ensuring data quality and compatibility with research objectives. Ethics and Compliance : Implement AI systems that adhere to ethical guidelines, data privacy regulations (e.g., GDPR, CCPA), and industry-specific compliance standards. Technical Support : Provide technical expertise and troubleshooting for AI systems, collaborating with teams to resolve issues and improve system performance. Qualifications Education : Masters or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience : 3–5 years building AI/ML-powered systems with at least one project involving agentic workflows or LLM-based automation Demonstrated experience building with tools like LangChain, LangGraph, or similar frameworks for multi-agent coordination Hands-on use of LLM APIs (e.g., OpenAI, Claude, Mistral), including prompt design, chaining, and tool integration Worked with vector databases (e.g., Pinecone, FAISS, Weaviate) for retrieval-augmented generation tasks Familiarity with deploying or integrating AI solutions in cloud environments (AWS, GCP, or serverless hosting) Technical Skills : Ability to design and optimize multi-step agent workflows using LLMs and external tools Strong Python developer with experience working in async, event-driven systems or streaming architectures Comfortable working with Neo4j or other graph databases to represent and query structured relationships Experience building or integrating lightweight ETL pipelines to ingest and transform structured/unstructured content Understanding of secure multi-tenant context handling and basic MLOps concepts like model versioning or feedback loops Communication and Collaboration Skills : Comfortable working cross-functionally with researchers, engineers, and product leads to turn workflows into agent behavior Able to clearly communicate system logic, capabilities, and limitations to both technical and non-technical stakeholders Experience working in distributed teams or async-first environments is a plus Self-motivated, organized, and able to manage ambiguity while delivering high-leverage contributions Preferred Qualifications : Experience with AI applications in market research, forecasting, or industry intelligence. Knowledge of industrial, pharmaceutical, or technology markets. Contributions to AI research, open-source projects, or publications in relevant fields. Nice to Have: Experience building domain-specific agents (e.g.,for research, finance, regulatory analysis, etc.) Exposure to reinforcement learning, RLHF, or retrieval scoring techniques Familiarity with streaming search, data federation, or client data integration pipelines Contributions to open-source agentic or LLM tooling, or AI writing/thought leadership Background in decision-support, research automation, or SaaS AI platforms ____________________________________________________________________________________ Ideal Candidate Profile Innovative Developer : Passionate about building AI solutions that transform market research and deliver impactful insights. Technical Problem Solver : Skilled at implementing and optimizing complex AI systems for real-world applications. Team Player : Thrives in collaborative environments, contributing to shared goals with a focus on quality and innovation. Client-Focused : Committed to developing AI tools that empower clients with actionable, data-driven insights.

Senior GenAI & Agentic AI Expert (Architect) – Remote (Initial Onsite in Dubai) Location: Remote (Initial 1–2 months in Dubai, and then remote from India) T ype: Full-time | Long-term | Direct Client Hire Client: AWS Consulting Partner with 400+ engineers globally About The Role Our client, a global AWS Consulting Partner with distributed teams across the US, Canada, UAE, India, and Pakistan, is hiring a high-caliber Senior Generative AI Expert with proven hands-on experience in building Agentic AI applications . This role is ideal for someone who has 10 to 15+ years of software engineering and AI/ML experience and is now focused on autonomous AI agents, tool-using LLMs, LangChain, AutoGPT, or similar frameworks . The selected candidate will work remotely, but must be available to relocate to Dubai for the first 4–8 weeks (expenses covered) for onboarding and collaboration. Key Responsibilities Design and develop Agentic AI applications using LLM frameworks (LangChain, AutoGPT, CrewAI, Semantic Kernel, or similar) Architect and implement multi-agent systems for enterprise-grade solutions Integrate AI agents with APIs, databases, internal tools, and external SaaS products Lead and mentor a cross-functional team across global time zones Optimize performance, context retention, tool usage, and cost efficiency Build reusable pipelines and modules to support GenAI use cases at scale Ensure enterprise-grade security, privacy, and compliance standards in deployments Collaborate directly with clients and senior stakeholders Ideal Candidate Profile 10 to 15+ years of professional experience in software engineering and AI/ML 3+ years of practical experience in LLM-based application development Strong track record of delivering Agentic AI systems (not just chatbot interfaces) Hands-on experience with: LangChain, AutoGPT, CrewAI, ReAct, Semantic Kernel OpenAI, Claude, Gemini, Mistral, or Llama2 Embedding models, vector databases (FAISS, Pinecone, Weaviate, etc.) Prompt engineering, RAG, memory/context management Serverless, Python, Node.js, AWS/GCP/Azure cloud Experience leading engineering teams and working with enterprise clients Excellent communication, documentation, and stakeholder management skills Must be open to initial relocation to Dubai for 1–2 months, followed by remote work from Pakistan/India Why Join? Work with a globally recognized AWS Consulting Partner Lead cutting-edge Agentic AI projects at enterprise scale Collaborate with senior teams across US, Canada, UAE, India, and Pakistan Flexible remote work after Dubai onboarding Competitive compensation + long-term career roadmap Skills: agentic ai,artificial intelligence,vector programming,langchain,llm frameworks,language modeling,openai,generative ai,autogpt,llama2,semantic kernel,vector databases,prompt engineering

About the Role We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Type: Full-time Pay: ₹2,000,000.01 - ₹3,002,234.14 per year Benefits: Flexible schedule Health insurance Paid time off Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person

Job Overview & Responsibilities We are looking for a skilled LLM / GenAI Expert who can drive innovative AI/ML solutions, and spearhead the development of advanced GenAI-powered applications. The ideal candidate will be a strong Python programmer with deep, hands-on experience in Large Language Models (LLMs), prompt engineering, and GenAI tools and frameworks. This role requires not only technical proficiency but also excellent communication skills and the ability to guide and upskill junior team members. Exposure to cutting-edge concepts like multi-agent collaboration, Memory-Context-Planning (MCP), and agent-to-agent workflows is highly desirable. ● Lead the design and development of GenAI/LLM-based products and solutions. ● Mentor and support junior engineers in understanding and implementing GenAI/LLM techniques. ● Work on fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and custom LLM workflows. Nice to Have ● Experience with cloud platforms (AWS/GCP/Azure) for deploying LLMs at scale. ● Knowledge of ethical AI practices, bias mitigation, and model interpretability. ● Background in machine learning, natural language processing (NLP), or AI research. ● Publications or contributions to open-source LLM projects are a plus. Perks & Benefits ● Competitive Compensation and Benefits ● Half Yearly Appraisals ● Friendly Environment ● Work-life Balance ● 5 days working ● Flexible office timings ● Employee-friendly leave policies ● Work from Home (with prior approvals) ● Integrate LLMs into production systems using Python and frameworks like LangChain, LlamaIndex, Transformers, etc. ● Explore and apply advanced GenAI paradigms such as MCP, agent2agent collaboration, and autonomous agents. ● Research, prototype, and implement new ideas and stay current with state-of-the-art GenAI trends. ● Collaborate closely with product, design, and engineering teams to align LLM use cases with business goals. Required Skills ● 5+ years of total software development experience with a strong foundation in Python. ● 2–3+ years of hands-on experience working with GenAI / LLMs, including real-world implementation and deployment. ● Deep familiarity with models like GPT-4, Claude, Mistral, LLaMA, etc. ● Strong understanding of prompt engineering, LLM fine-tuning, tokenization, and embedding-based search. ● Experience with Hugging Face, LangChain, OpenAI API, and vector databases (Pinecone, FAISS, Chroma). ● Exposure to agent frameworks and multi-agent orchestration. ● Excellent written and verbal communication skills. ● Proven ability to lead and mentor team members on technical and architectural decisions Job Types: Full-time, Permanent Pay: ₹50,000.00 - ₹1,083,333.00 per month Schedule: Day shift Monday to Friday Work Location: In person

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, 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 Bachelor’s or Master’s Degree in Computer Science, Engineering, Have undergone any modern NLP/LLM courses or participation in open competitions are added advantage.

We're seeking a visionary Enterprise Architect to join our CTO Office and shape cross-portfolio solutions at the intersection of AI, Customer Experience (CX), Cybersecurity, and Digital Skilling technologies. You’ll architect scalable, standardized solutions for global clients, govern complex deals, and collaborate with diverse stakeholders to translate business needs into future-ready technical strategies. As a trusted advisor, you will evangelize solution value, articulating how the right technology mix enables our customers to achieve strategic outcomes. At TeKnowledge , your work makes an impact from day one. We partner with organizations to deliver AI-First Expert Technology Services that drive meaningful impact in AI, Customer Experience, and Cybersecurity. We turn complexity into clarity and potential into progress—in a place where people lead and tech empowers. You’ll be part of a diverse and inclusive team where trust, teamwork, and shared success fuel everything we do. We push boundaries, using advanced technologies to solve complex challenges for clients around the world. Here, your work drives real change, and your ideas help shape the future of technology. We invest in you with top-tier training, mentorship, and career development—ensuring you stay ahead in an ever-evolving world. Why You’ll Enjoy It Here: Be Part of Something Big – A growing company where your contributions matter. Make an Immediate Impact – Support groundbreaking technologies with real-world results. Work on Cutting-Edge Tech – AI, cybersecurity, and next-gen digital solutions. Thrive in an Inclusive Team – A culture built on trust, collaboration, and respect. We Care – Integrity, empathy, and purpose guide every decision. We’re looking for innovators, problem-solvers, and experts ready to drive change and grow with us. We Are TeKnowledge. Where People Lead and Tech Empowers. Responsibilities: Design enterprise-grade architectures integrating structured/unstructured data, analytics, and advanced AI models (GenAI, LLMs, cognitive services). Build scalable data pipelines and lake-centric architectures to power real-time analytics and machine learning. Architect multi-cloud AI/ML platforms using Azure, including deployment of LLMs (Azure OpenAI and open-source models like LLaMA, Mistral, Falcon). Define infrastructure, data, and app requirements to deploy LLMs in customer private data centers. Lead technical reviews for high-value deals, identifying risks and mitigation strategies. Design integrated solutions across AI, CX, Cybersecurity, and Tech Managed Services portfolios. Develop standard design patterns and reusable blueprints for repeatable, low-risk, and scalable solution delivery. Present architectural solutions to C-suite executives, aligning technical outcomes with business value and ROI. Collaborate with sales and pre-sales to scope complex opportunities and develop compelling proposals. Foster innovation across CTO, Sales, and Solution teams. Identify synergy across offerings (e.g., Microsoft Copilot + AI-first CX + Cybersecurity). Support product teams with market feedback and solution evolution. Define architectural best practices ensuring security, compliance, and scalability. Mentor delivery teams on frameworks and emerging tech adoption. Shape and execute the enterprise architecture strategy aligned with business goals. Champion digital transformation and technology innovation. Leverage expertise in Azure and Microsoft D365 to support solution architecture. Drive responsible AI adoption and ensure awareness of privacy, bias, and security in deployments. Ensure all solutions meet IT security and compliance standards. Collaborate with Legal and Procurement for contract negotiations and vendor performance. Lead, mentor, and build a high-performing, collaborative CTO team with a customer-first mindset. Qualifications: Education: Bachelor's or Master’s degree in Computer Science, Information Technology, Cybersecurity, or related field. Experience: 10+ years in enterprise architecture, with 5+ years in customer-facing roles. Certifications: Preferred – TOGAF, Zachman, ITIL, CISSP, Azure certifications or equivalents. Proven experience architecting and delivering AI/ML platforms, data lakes, and intelligent applications at enterprise scale. Demonstrable experience deploying local LLMs in production environments, including integration with LangChain, databases, and private storage. Strong knowledge of enterprise architecture frameworks and multi-cloud platforms (with a focus on Azure). Ability to design and deliver end-to-end solutions including networks (voice and data), microservices, business applications, resilience, disaster recovery, and security. Understanding of On-Prem / Private Cloud workload migration to public or hybrid cloud environments. Commercial acumen with the ability to articulate the business value of cloud-based solutions to executive stakeholders. Strong problem-solving and critical thinking skills with a proactive, outcome-oriented mindset. Experience with cloud computing, data center technologies, virtualization, and enterprise-grade security policies/processes. Proficiency in AI/ML, cybersecurity frameworks, customer experience platforms, and Microsoft Cloud (Azure, M365, D365). Exceptional communication and storytelling abilities for both technical and non-technical audiences. Experience engaging with large enterprise clients across industries such as government, healthcare, banking & finance, travel, and manufacturing. Empowering Leadership and Innovation At TeKnowledge, we are committed to fostering a culture of inspiring leadership and innovation. Our core leadership competencies are integral to our success: Inspire: We prioritize creating an inclusive environment, leading with purpose, and acting with integrity and respect. Build: Our leaders own business growth, drive innovation, and continuously strive for excellence. Deliver: We focus on setting clear priorities, embracing agility and change, and fostering collaboration for growth. We are looking for talented individuals who embody these competencies, are ready to grow, and are eager to contribute to our dynamic team. If you are passionate about making a meaningful impact and excel in a collaborative, forward-thinking environment, we invite you to apply and help us shape the future.

🚨 Hiring: AI/NLP Intern – Clinical Note Generation & LLM Evaluation (Remote) 📅 Start: ASAP | 🕒 Duration: 3–6 months | 💼 Unpaid (Potential for paid extension) We're a healthcare AI startup building agentic tools for medical documentation, patient monitoring, and insurance workflows . Our stack combines LLMs, multimodal AI, and real-time speech processing , backed by talent from NVIDIA, JP Morgan Chase, EY, and UC Health. We’re looking for a sharp AI/NLP intern to help us evaluate and fine-tune language models for SOAP note generation . You’ll work on real-world clinical data, build benchmarks, and integrate models into live systems. Perfect for students or early-career researchers passionate about applied AI in healthcare. 🔍 What You'll Work On: Fine-tune & benchmark LLMs (LLaMA, Mistral, MedAlpaca) Evaluate models using BLEU, ROUGE, BERTScore, and factuality Build NER + entity linking pipelines Deploy APIs (FastAPI) and work with front-end engineers Run error analyses, iterate prompts, explore new ideas ✅ Must-Have Skills: Python + HuggingFace Transformers + basic ML/NLP Understanding of prompting, attention, tokenization Jupyter or Colab for experimentation 💡 Bonus: FastAPI, React, full-stack experience Knowledge of clinical NLP or biomedical informatics 🔬 Evaluation Task: We shortlist candidates via a hands-on task using the ACI-Bench dataset (doctor–patient conversations → SOAP notes). You'll benchmark open-source LLMs and submit a short report or notebook. Details sent after initial screening. But, proactive candidates can already: Understand the Data : https://github.com/wyim/aci-bench/blob/main/data/challenge_data/train.csv Analyze the format of the doctor-patient encounters and how they map to the structured clinical notes. Explore the narrative and SOAP-style elements in the provided notes. Select and Apply LLMs - Choose one or more open-source LLMs (e.g., LLaMA, Mistral, MedAlpaca) that can be used to generate notes from the conversations. Decide whether to use zero-shot prompting, few-shot learning, or fine-tuning approaches. Define Evaluation Metrics - focus on hallucination and faithfulness 🎁 Perks: Work on real AI-for-healthcare systems Mentorship from experts High-impact portfolio project Strong LoR + possible transition to paid contract 📩 Apply by sending your resume + GitHub (if any) + a short blurb on your NLP experience to [founder@saans.ai]. Let’s build the future of clinical care—together. 🚀 #Hiring #AIInternship #NLP #LLM #HealthcareAI #GenerativeAI #RemoteJobs #InternshipOpportunity #MedTech #MachineLearning #TechForGood #DigitalHealth #AIInHealthcare #InternshipOpportunity

We at Arnsoft are looking for an AI Engineer with Full Stack experience (React/Java/Python) to help us design, build, and deploy cutting-edge AI systems. This role involves working at the intersection of software engineering and artificial intelligencecontributing to the development of Co-pilots, AI agents, private GPTs, SLMs, and Virtual Advisors that solve real-world problems. You'll collaborate closely with internal teams and clients, write production-grade AI/ML code, and play a key role in delivering intelligent, scalable solutions. Responsibilities Write clean, efficient, and well-documented code for AI/ML applications. Collaborate with cross-functional teams to understand project requirements and contribute to technical solutions. Help in building and maintaining data pipelines for our AI systems. Ability to write clear documentation. Stay updated with the latest advancements in AI, machine learning, and deep learning. Work directly with clients to understand their needs, communicate progress, and maintain alignment throughout the project lifecycle. Requirements Building Agentic Systems and AI-powered applications. Working with LLMs like OpenAI, Claude, Mistral, or LLaMA. Building and fine-tuning SLMs (Small Language Models) for lightweight, focused use cases. Developing full-stack applications using React, Java, and/or Python. Cloud deployment (AWS, GCP, Azure). Prompt engineering, RAG pipelines, and LLM fine-tuning. Tools like LangChain, LlamaIndex, or similar. Vector databases (Pinecone, Weaviate, FAISS). API integration and backend orchestration. Worked with websockets and tools like VAD. Required Qualifications & Skills Education: A Bachelor's or Master's degree (B. E. /B. Tech/M. E. /M. Tech) in Computer Science, IT, or a related engineering discipline from a Tier 1 institution. Academic Performance: Consistent and strong academic record. Core Concepts: Solid understanding of fundamental AI, Machine Learning, and Deep Learning concepts. Programming: Strong programming skills in Python. Foundations: Excellent knowledge of Data Structures, Algorithms, and Object Oriented Programming (OOP). Problem-Solving: Strong analytical and problem-solving abilities with a keen attention to detail. Communication: Excellent verbal and written communication skills. Teamwork: A collaborative mindset with the ability to work effectively in a team environment. This job was posted by Jeevanlal Bukya from Arnsoft Technologies.

AI Lead – Generative & Agentic AI Systems Experience: 7–10 Years Location: Hyderabad (Hybrid) Employment Type: Full-Time About the Role: We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities: Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise: AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications: 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Types: Full-time, Permanent Pay: ₹2,500,000.00 - ₹3,500,000.00 per year Benefits: Flexible schedule Health insurance Provident Fund Supplemental Pay: Joining bonus Work Location: In person

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY- Assurance – Senior - Digital Position Details As part of EY GDS Assurance Digital, you will be responsible for implementing innovative ideas through AI research to develop high growth & impactful products. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. You will work with multi-disciplinary teams across the entire region to support global clients. This is a core full-time AI developer role, responsible for creating innovative solutions by applying AI based techniques for business problems. As our in-house senior AI engineer, your expertise and skills will be vital in our ability to steer one of our Innovation agenda. Responsibilities Convert business problem into analytical problem and devise a solution approach. Clean, aggregate, analyze and interpret the data to derive business insights from it. Own the AI/ML implementation process: Model Design, Feature Planning, Testing, Production Setup, Monitoring, and release management. Work closely with the Solution Architects in deployment of the AI POC’s and scaling up to production level applications. Should have solid background in Python and has deployed on open-source models- Work on data extraction techniques from complex PDF/Word Doc/Forms- entities extraction, table extraction, information comparison. Key Requirements/Skills & Qualification: Excellent academic background, including at a minimum a bachelor or a master’s degree in data science, Business Analytics, Statistics, Engineering, Operational Research, or other related field with strong focus on modern data architectures, processes, and environments. Solid background in Python with excellent coding skills. 4+ years of core data science experience in one or more below areas: Machine Learning (Regression, Classification, Decision Trees, Random Forests, Timeseries Forecasting and Clustering) Understanding and usage of Large Language Models like Open AI models like ChatGPT, GPT4, frameworks like LangChain and Llama Index. Good understanding of open source LLM framework like Mistral, Llama, etc. and fine tuning on custom datasets. Deep Learning (DNN, RNN, LSTM, Encoder-Decoder Models) Natural Language Processing- Text Summarization, Aspect Mining, Question Answering, Text Classification, NER, Language Translation, NLG, Sentiment Analysis, Sentence Computer Vision- Image Classification, Object Detection, Tracking etc. SQL/NoSQL Databases and its manipulation components Working knowledge of API Deployment (Flask/FastAPI/Azure Function Apps) and webapps creation, Docker, Kubernetes. Additional skills requirements: Excellent written, oral, presentation and facilitation skills Ability to coordinate multiple projects and initiatives simultaneously through effective prioritization, organization, flexibility, and self-discipline. Must have demonstrated project management experience. Knowledge of firm’s reporting tools and processes. Proactive, organized, and self-sufficient with ability to priorities and multitask. Analyses complex or unusual problems and can deliver insightful and pragmatic solutions. Ability to quickly and easily create/ gather/ analyze data from a variety of sources. A robust and resilient disposition able to encourage discipline in team behaviors What We Look For A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY- Assurance – Senior - Digital Position Details As part of EY GDS Assurance Digital, you will be responsible for implementing innovative ideas through AI research to develop high growth & impactful products. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. You will work with multi-disciplinary teams across the entire region to support global clients. This is a core full-time AI developer role, responsible for creating innovative solutions by applying AI based techniques for business problems. As our in-house senior AI engineer, your expertise and skills will be vital in our ability to steer one of our Innovation agenda. Responsibilities Convert business problem into analytical problem and devise a solution approach. Clean, aggregate, analyze and interpret the data to derive business insights from it. Own the AI/ML implementation process: Model Design, Feature Planning, Testing, Production Setup, Monitoring, and release management. Work closely with the Solution Architects in deployment of the AI POC’s and scaling up to production level applications. Should have solid background in Python and has deployed on open-source models- Work on data extraction techniques from complex PDF/Word Doc/Forms- entities extraction, table extraction, information comparison. Key Requirements/Skills & Qualification: Excellent academic background, including at a minimum a bachelor or a master’s degree in data science, Business Analytics, Statistics, Engineering, Operational Research, or other related field with strong focus on modern data architectures, processes, and environments. Solid background in Python with excellent coding skills. 4+ years of core data science experience in one or more below areas: Machine Learning (Regression, Classification, Decision Trees, Random Forests, Timeseries Forecasting and Clustering) Understanding and usage of Large Language Models like Open AI models like ChatGPT, GPT4, frameworks like LangChain and Llama Index. Good understanding of open source LLM framework like Mistral, Llama, etc. and fine tuning on custom datasets. Deep Learning (DNN, RNN, LSTM, Encoder-Decoder Models) Natural Language Processing- Text Summarization, Aspect Mining, Question Answering, Text Classification, NER, Language Translation, NLG, Sentiment Analysis, Sentence Computer Vision- Image Classification, Object Detection, Tracking etc. SQL/NoSQL Databases and its manipulation components Working knowledge of API Deployment (Flask/FastAPI/Azure Function Apps) and webapps creation, Docker, Kubernetes. Additional skills requirements: Excellent written, oral, presentation and facilitation skills Ability to coordinate multiple projects and initiatives simultaneously through effective prioritization, organization, flexibility, and self-discipline. Must have demonstrated project management experience. Knowledge of firm’s reporting tools and processes. Proactive, organized, and self-sufficient with ability to priorities and multitask. Analyses complex or unusual problems and can deliver insightful and pragmatic solutions. Ability to quickly and easily create/ gather/ analyze data from a variety of sources. A robust and resilient disposition able to encourage discipline in team behaviors What We Look For A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What Working At EY Offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

The University of Hong Kong Apply now Ref.: 532151 Work type: Full-time Department: School of Public Health (22400) Categories: Senior Research Staff & Post-doctoral Fellow Hong Kong Applications are invited for appointment as Research Officer (RO)/ Assistant Research Officer (ARO) in Division of Epidemiology and Biostatistics, School of Public Health (Ref.: 532151), to commence on 1 November 2025 for up to one year on temporary basis, or two to three years on fixed-term basis, with the possibility of renewal subject to satisfactory performance and funding availability. Applicants should hold a PhD degree in epidemiology, biostatistics, public health or related disciplines from a leading research institution. A minimum of 5 years of relevant research/postdoctoral experience is required, including proven proficiency in developing artificial intelligence (AI) models using both online and offline large language models (LLMs) such as GPT, Qwen, DeepSeek, Mistral, Llama, and Gemma. Familiarity with Linux environments is essential, along with advanced Python programming skills for processing annotated data, implementing fine-tuning techniques (e.g., Chain-of-Thought, Retrieval Augmented Generation), and optimizing outputs through cross-referencing and ensemble strategies. Experience in developing oncology-focused natural language processing (NLP) models with related publications will be advantageous. Strong quantitative research capabilities are critical, including extracting and analysing large electronic health records from the Hospital Authority using R, STATA, or SAS, and conducting costing/cost-effectiveness analyses. Applicants must have hands-on experience in securing competitive grants as principal investigators or co-investigators, managing patient recruitment, preparing IRB applications, and drafting press releases. Exceptional bilingual communication skills (English and Chinese) and the ability to work both independently and collaboratively in multidisciplinary teams are essential. Those with lower qualifications or less experience may be appointed as ARO. The appointee will implement AI models using diverse LLMs to analyse unstructured clinical notes from public sources and the Hospital Authority. Key responsibilities include supporting the development of AI clinical decision support systems for practical clinical use, participating in territory-wide epidemiological studies to evaluate intervention/vaccine effectiveness using electronic health records, and assisting in project coordination. Operational duties encompass overseeing patient recruitment/follow-up, preparing IRB submissions, drafting manuscripts and press releases, and contributing to grant applications from conception to execution. The role requires active liaison with clinical co-investigators and stakeholders to ensure project alignment. Enquiries about the duties of the post should be sent to Ms Audrey Ho at audreyh@hku.hk. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical/dental benefits. The appointment on fixed terms will attract a contract-end gratuity and University contribution to a retirement benefits scheme at 10% of basic salary for ARO, and 15% for RO. Housing benefits will also be provided to RO on a fixed-term appointment as applicable. The University only accepts online applications for the above post. Applicants should apply online and upload an up-to-date CV. Review of applications will start on June 19, 2025, and continue until September 4, 2025 , or until the post is filled, whichever is earlier. Advertised: Jun 5, 2025 (HK Time) Applications close: Sep 4, 2025 (HK Time) Back to search results Apply now Whatsapp Facebook LinkedIn Email App

load_list_page(event)"> Job listing Job details Job Information Date Opened 06/27/2025 Industry IT Services Job Type Internship City Pune City State/Province Maharashtra Country India Zip/Postal Code 411001 About Us CCTech 's mission is to transform human life by the democratization of technology. We are a well established digital transformation company building the applications in the areas of CAD, CFD, Artificial Intelligence, Machine Learning, 3D Webapps, Augmented Reality, Digital Twin, and other enterprise applications. We have two business divisions: product and consulting. simulationHub is our flagship product and the manifestation of our vision. Currently, thousands of users use our CFD app in their upfront design process. Our consulting division, with its partners such as Autodesk Forge, AWS and Azure, is helping the world's leading engineering organizations, many of which are Fortune 500 list of companies, in achieving digital supremacy. Job Description We are seeking a passionate and skilled AI Intern. The ideal candidate will have an engineering background and a strong grasp of modern AI technologies, especially in Prompt Engineering, Agentic AI models, and production-grade AI workflows . You’ll play a key role in building intelligent systems that augment and automate real-world business processes. Responsibility Design, develop, and deploy AI-powered solutions using LLMs and agentic frameworks. Build and optimize prompt engineering strategies to ensure high-performance language model behavior. Create and maintain autonomous AI agents capable of executing complex multi-step tasks. Develop, test, and iterate on real-world AI workflows integrated into broader applications. Collaborate with product managers, designers, and engineers to translate business problems into scalable AI solutions. Monitor and fine-tune AI models in production for accuracy, performance, and cost-effectiveness. Stay current with emerging trends in generative AI, LLMs, agent-based architectures, and MLOps. Requirements Bachelor’s degree in Computer Science, Engineering, or related field. Proven experience with Prompt Engineering and customizing large language model behavior. Knowledge of developing or integrating Agentic AI frameworks (e.g., LangChain, AutoGPT, etc.). Understanding of LLMs (e.g., GPT-4, Claude, Mistral, Gemini, etc.) and how to apply them in workflow automation. Demonstrated ability to deploy working AI solutions and pipelines in DEV & Production environments. Proficient in Python and relevant AI libraries (Transformers, OpenAI SDK, LangChain, etc.). Familiarity with RESTful APIs, cloud platforms (e.g., Azure, AWS, GCP), and version control tools (e.g., Git) Must Have Must be familiar with frameworks like langchain, llama index, langraph and have used them in project(s). Must be familiar with RAG framework (vector databases). Must be familiar with computer vision tasks like object detection, image processing and OCR Benefits Opportunity to work with a dynamic and fast-paced IT organization. Make a real impact on the company's success by shaping a positive and engaging work culture. Work with a talented and collaborative team. Be part of a company that is passionate about making a difference through technology. check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2185D0;border-color:#2185D0;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered="">

ROLE : Technical Lead & Mentor for AI Agent development • Ability to receive a project request, define a development plan, and identify the necessary tools and technologies. • Experience with LLMs (LLaMA, Mistral, GPT-like), RAG, fine-tuning, prompt engineering. • Agent architecture: task decomposition, memory, tool orchestration. • Languages: Python Preferred Skills Handling a team and deliver it with support and guidance. Agent Building Expertise : Hands-on experience in developing and deploying LLM agents with advanced features like tool integration, contextual memory systems, and feedback-driven learning us

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

AI Bot Developer Location: Remote (India) Experience: 0-2 years Salary: ₹7 LPA base + ₹ 2 LPA performance bonus (based on skills) Type: Full-Time/Part-time/Contract/Internship About Us: We’re an early-stage startup building AI-driven digital products that blend large language models (LLMs) with scalable products. Our organisation's goal is to increase product and service visibility, user engagement and create high ROI with marketing budget on social media platforms, The ideal candidate can be a university student, recent graduate, contractor or a full-time employee, however, they should have previous part-time or full-time technical experience, have a well composed github profile or personal portfolio, be able to prove their technical capabilities and knowledge on bot development upon immediate request and show commitment to the role. Responsibilities: Design and deploy LLM-powered bots (e.g., auto-reply systems, content summarizers, viral thread generators). Integrate RAG pipelines (e.g., retrieve Reddit comments + LLM responses) with vector DBs (Pinecone, Weaviate). Fine-tune/open-source LLMs (Llama 3, Mistral) for bot-specific tasks (persona mimicry, NSFW filtering). Optimize cost/latency (model quantization, caching, hybrid rule-based + AI logic). Implement stealth measures (human-like delays, randomized phrasing, proxy rotation). Technical Stack: Core: Python (Tweepy, PRAW, AsyncIO, LangChain, LlamaIndex) LLMs: OpenAI, Anthropic, Gemini, or self-hosted (Llama.cpp, vLLM) Infra: AWS Lambda, FastAPI, Docker, Redis (for rate-limiting) Data: Vector DBs (Pinecone), PostgreSQL, Firebase Bonus: Next.js/Streamlit for bot dashboards Ideal Candidate: ✅ 1-2 years of experience building Python bots (X/Reddit API automation). ✅ Worked with LLM integrations (RAG, fine-tuning, prompt engineering). ✅ Understands detection tactics (IP rotation, CAPTCHA solvers). ✅ Pragmatic problem-solver who cares about scalability vs. cost tradeoffs. ✅ Prefered: Deployed bots at scale (10K+ reqs/day) or contributed to open-source LLM projects. Compensation & Benefits: ₹7 lakhs base salary + ₹2 lakhs performance-based bonus (58,350 INR per month, 50k INR bonus per successful quarter) 100% remote work - work from anywhere within the working hours Opportunity to work on cutting-edge AI products from ground up Flat hierarchy and direct impact on technical decisions Learning budget for courses/certificates

Job Title: Data Architect Location: Bangalore ,Hyderabad,Chennai, Pune, Gurgaon - hybrid- 2/3 days WFO Experience: 8+ years Position Overview: We are seeking a highly skilled and strategic Data Architect to design, build, and maintain the organizations data architecture. The ideal candidate will be responsible for aligning data solutions with business needs, ensuring data integrity, and enabling scalable and efficient data flows across the enterprise. This role requires deep expertise in data modeling, data integration, cloud data platforms, and governance practices. Key Responsibilities: Architectural Design: Define and implement enterprise data architecture strategies, including data warehousing, data lakes, and real-time data systems. Data Modeling: Develop and maintain logical, physical, and conceptual data models to support analytics, reporting, and operational systems. Platform Management: Select and oversee implementation of cloud and on-premises data platforms (e.g., Snowflake, Redshift, BigQuery, Azure Synapse, Databricks). Integration & ETL: Design robust ETL/ELT pipelines and data integration frameworks using tools such as Apache Airflow, Informatica, dbt, or native cloud services. Data Governance: Collaborate with stakeholders to implement data quality, data lineage, metadata management, and security best practices. Collaboration: Work closely with data engineers, analysts, software developers, and business teams to ensure seamless and secure data access. Performance Optimization: Tune databases, queries, and storage strategies for performance, scalability, and cost-efficiency. Documentation: Maintain comprehensive documentation for data structures, standards, and architectural decisions. Required Qualifications: Bachelors or master’s degree in computer science, Information Systems, or a related field. 5+ years of experience in data architecture, data engineering, or database development. Strong expertise in data modeling, relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra). Experience with modern data platforms and cloud ecosystems (AWS, Azure, or GCP). Hands-on experience with data warehousing solutions and tools (e.g., Snowflake, Redshift, BigQuery). Proficiency in SQL and data scripting languages (e.g., Python, Scala). Familiarity with data privacy regulations (e.g., GDPR, HIPAA) and security standards. Tech Stack AWS Cloud – S3, EC2, EMR, Lambda, IAM, Snowflake DB Databricks Spark/Pyspark, Python Good Knowledge of Bedrock and Mistral AI RAG & NLP LangChain and LangRAG LLMs Anthropic Claude, Mistral, LLaMA etc.,

About Valorant Valorant is a fast-growing procurement consulting firm helping mid-market and PE-backed companies transform operations. We’re now launching our next chapter: building AI products to radically automate and augment procurement workflows. This isn’t about chatbot demos. We’re building real enterprise software with real client data, solving real problems. About the Role As our Full-Stack AI Engineer / Technical Product Lead , you’ll drive the design, development, and launch of intelligent agentic systems that blend LLMs, vector search, structured data, and enterprise workflows. You’ll work closely with domain experts, iterate fast, and own the tech stack end to end—from backend services to frontend interfaces. This is a zero-to-one opportunity to build production-grade AI tools that work at scale and matter to real businesses. What You’ll Do Architect and build AI-powered products for procurement and supply chain use cases Develop LLM features using RAG (Retrieval-Augmented Generation), prompt engineering, and custom context pipelines Implement semantic document search using vector databases (Chroma, FAISS, etc.) Build Python backend services for data ingestion, transformation, and orchestration of AI pipelines Work with structured enterprise data (e.g., ledgers, SaaS exports, CSVs) to extract insights and power analytics Design or collaborate on frontend development for dashboards, chat interfaces, and user-facing tools (React or similar) Translate complex workflows into clean, intuitive UX with strong usability principles Ensure enterprise-grade reliability, explainability, and data privacy Contribute to product roadmap, feature planning, and fast iteration cycles with consultants and PMs Take ownership of the full stack and help shape a modern, scalable AI-first architecture What We’re Looking For 5–7+ years of experience in software engineering, full-stack development, or AI/ML product engineering Hands-on experience shipping LLM features in production (OpenAI, Claude, LLaMA, Mistral, etc.) Strong Python skills; experience with LangChain, LLaMA Index, or similar frameworks Experience with vector search, semantic indexing, and chunking strategies Backend engineering experience: designing modular APIs, microservices, and orchestration layers (FastAPI, Flask, Django, etc.) Proficiency in frontend development using React, Vue, or similar frameworks Understanding of UI/UX principles and ability to turn workflows into usable interfaces Familiarity with structured data workflows: pandas, SQL, and validation pipelines Exposure to cloud environments and dev tooling (Docker, GitHub Actions, AWS/GCP) Pragmatic, product-focused mindset — values useful outputs over academic perfection Bonus: Domain experience in procurement, supply chain, legal tech, or enterprise SaaS Bonus: Experience mentoring junior engineers or contributing to team scaling Why Join Us? Build meaningful AI products that solve real problems — not just tech showcases Collaborate with domain experts and access rich real-world data from day one Operate with autonomy, fast iteration cycles, and strong strategic backing Shape the tech foundation of an ambitious, AI-native product company Competitive pay and flexible remote work.

About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. About Yubi Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. All of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any and all capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset based securitization Spocto - Debt recovery & risk mitigation platform Corpository - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals and Predictions to Lenders, Investors and Business Enterprises So far, we have on-boarded over 17000+ enterprises, 6200+ investors & lenders and have facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today, who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come, join the club to be a part of our epic growth story. Responsibilities This particular role is within our Yubi Invest vertical, and you would get to work on building our bonds platform, called Aspero, for retail users. Be able to operate in ambiguous situations and define clear objectives by breaking down the narratives independently. Work closely with business, research, data and engineering teams to understand the user goals, market dynamics and ship products. Aligning product strategy, proposition and roadmap with measurable metrics with all stakeholders. Drive PRDs, product planning, and product design of new features and enhancements. Clearly communicate product and platform benefits to our users and internal stakeholders About The Role- We’re looking for a highly skilled, results-driven AI engineer who thrives in fast-paced, high-impact environments. If you are passionate about pushing the boundaries of Computer Vision, OCR, and Large Language Models (LLMs) and have a strong foundation in building and deploying AI solutions, this role is for you. As a Senior Data Scientist, you will take ownership of designing and implementing state-of-the-art OCR and Computer Vision systems. This role demands deep technical expertise, the ability to work autonomously, and a mindset that embraces complex challenges head-on. Here, you won’t just fine-tune pre-trained models—you’ll be architecting, optimizing, and scaling AI solutions that power real-world applications. Key Responsibilities- Architect, develop, and deploy high-performance Computer Vision and OCR models for real-world applications. Implement and optimize state-of-the-art OCR models such as Donut, TrOCR, LayoutLM, and DocFormer for document processing and information extraction. Fine-tune and integrate LLMs (GPT, LLaMA, Mistral, etc.) to enhance text understanding and automation. Develop custom deep learning models for large-scale image and document processing. Build and optimize end-to-end AI pipelines, ensuring efficient data processing and model deployment. Work closely with engineers to operationalize AI models in production (Docker, FastAPI, TensorRT, ONNX). Enhance GPU performance and model inference efficiency, applying techniques such as quantization and pruning. Stay ahead of industry advancements, continuously experimenting with new AI architectures and training techniques. Work in a highly dynamic, startup-like environment, balancing rapid experimentation with production-grade robustness. Requirements 5-10 years experience p roven technical expertise – Strong programming skills in Python, PyTorch, TensorFlow with deep experience in Computer Vision and OCR. Hands-on experience in developing, training, and deploying OCR and document AI models. Deep understanding of Transformer-based architectures for vision and text processing. Experience working with Hugging Face, OpenCV, TensorRT, and NVIDIA GPUs for model acceleration. Autonomous problem solver – You take initiative, work independently, and drive projects from research to production. Strong experience in scaling AI solutions, including model optimization and deployment on cloud platforms (AWS/GCP/Azure). Thrives in fast-paced environments – You embrace challenges, pivot quickly, and execute effectively. Familiarity with MLOps tools (Docker, FastAPI, Kubernetes) for seamless model deployment. Experience in multi-modal models (Vision + Text). Nice to Have- Strong background in vector databases, RAG pipelines, and fine-tuning LLMs for document intelligence. Contributions to open-source AI projects.