161 Huggingface Jobs - Page 4

We are seeking an innovative and forward-thinking AI Strategist to join our team. In this role, you will lead the development and implementation of AI-driven strategies that align with our organization's long-term goals. You will work closely with cross-functional teams to identify opportunities where artificial intelligence can drive business growth, operational efficiency, and competitive advantage. Role & responsibilities Required Skills: Proven experience with Large Language Models (e.g., GPT, BERT, LLaMA) and customizing them for business-specific use cases. Proficient in AI code tools, including GitHub Copilot, Cursor, and more. Expertise in prompt engineering and prompt optimization for effective LLM outputs. Strong understanding of security principles, specifically concerning LLM implementation and internal data protection Preferred candidate profile LLM Model Customization & Implementation Customize and fine-tune Large Language Models (LLMs) to address specific business and functional requirements. Design and implement LLM integrations to optimize business workflows and support various functional areas, ensuring high-quality and relevant outputs. Conduct regular assessments to maintain alignment with organizational goals and security standards, preventing any unintended exposure to external networks.

We are looking for immediate joiners only We are seeking an innovative and forward-thinking AI Strategist with .Net/Java Full stack to join our team. In this role, you will lead the development and implementation of AI-driven strategies that align with our organization's long-term goals. You will work closely with cross-functional teams to identify opportunities where artificial intelligence can drive business growth, operational efficiency, and competitive advantage. Role & responsibilities Required Skills: We are looking for a Full Stack Architect / Associate Architect with strong architectural expertise and deep hands-on experience across Angular, .NET Core, SQL Server, and especially IIS . The ideal candidate must be proficient in application architecture design , performance tuning , and end-to-end ownership of enterprise-grade solutions with significant exposure to hosting and configuration environments. Key Responsibilities Architect, design, and deliver high-performance enterprise applications using Angular, .NET Core, and SQL Server. Define and implement best practices around coding, architecture, security, and performance. Take complete ownership of IIS setup, deployment pipelines , and application hosting architecture , ensuring secure and scalable configuration. Troubleshoot and resolve issues related to Windows Authentication, Application Pools, and service account connectivity. Proven experience with Large Language Models (e.g., GPT, BERT, LLaMA) and customizing them for business-specific use cases. Proficient in AI code tools, including GitHub Copilot, Cursor, and more. Expertise in prompt engineering and prompt optimization for effective LLM outputs. Strong understanding of security principles, specifically concerning LLM implementation and internal data protection Preferred candidate profile LLM Model Customization & Implementation Customize and fine-tune Large Language Models (LLMs) to address specific business and functional requirements. Design and implement LLM integrations to optimize business workflows and support various functional areas, ensuring high-quality and relevant outputs. Conduct regular assessments to maintain alignment with organizational goals and security standards, preventing any unintended exposure to external networks.

About Us: We are an innovative and fast-growing company focused on leveraging cutting-edge technology to explore new opportunities in various industries. Our focus is on applying artificial intelligence (AI) and large language models (LLMs) to solve real-world business challenges. Job Description: We are seeking motivated and independent AI & LLM interns to help explore and develop AI-driven solutions. This internship offers the chance to work on AI projects that involve natural language processing (NLP), machine learning, and large language models, providing real-world applications for these technologies. Key Responsibilities: Independently explore and experiment with LLM models to identify potential applications and opportunities. Develop and fine-tune AI models using transformer architectures (e.g., GPT, BERT, etc.). Conduct research on emerging AI and NLP trends to identify new areas for growth. Analyze and interpret data sets to train AI models. Work on building prototype AI solutions for potential business applications. Document findings, processes, and recommendations for future projects. Creating AI agents using available tools in market including ChatGPT & Claude Qualifications: Currently pursuing or recently completed a degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Strong understanding of machine learning algorithms, natural language processing, and deep learning models. Experience with Python and relevant libraries (e.g., TensorFlow, PyTorch, Hugging Face). Familiarity with transformer models and their applications. Strong analytical and problem-solving skills. Ability to work independently and manage tasks with minimal supervision. Eagerness to learn and stay updated with emerging AI trends. What We Offer: Hands-on experience working with real-world AI/LLM applications. Opportunities to contribute to innovative AI projects.

Job Title: Senior AI/ML Engineer Custom LLM & RAG Implementation Location: On-site Experience: 7+ years Industry: Cross-Domain (Finance, Healthcare, Logistics, Retail, LegalTech, etc.) About the Role We are seeking a highly skilled and hands-on Senior AI/ML Engineer with strong expertise in building and deploying custom Large Language Models (LLMs) . The ideal candidate will have demonstrable experience in Retrieval-Augmented Generation (RAG) implementations, fine-tuning foundation models , and solving complex problems across domains using applied machine learning and natural language processing. This role is strategic and technical, requiring a blend of research, solution engineering, MLOps maturity, and domain adaptability. Key Responsibilities LLM Development & Deployment Design, build, and deploy customized LLM pipelines tailored to enterprise use cases. Implement end-to-end LLMOps workflows including model packaging, CI/CD, and monitoring. RAG & Fine-Tuning Implement RAG pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate) and document ingestion frameworks (e.g., LangChain, Haystack). Fine-tune open-source LLMs (e.g., LLaMA, Falcon, Mistral, MPT) on proprietary datasets using frameworks like Hugging Face Transformers and PEFT/LoRA. Solution Engineering Translate business problems into ML/LLM solutions with clear problem framing and data strategy . Collaborate with product, data engineering, and domain teams to prototype and deliver scalable solutions. Cross-Functional AI Applications Apply ML/LLM solutions across multiple verticals such as legal document analysis, customer support automation, compliance, supply chain optimization, or medical NLP. Build domain-agnostic prompt engineering strategies and apply zero-shot/few-shot learning where appropriate. Leadership & Mentorship Mentor junior engineers and contribute to AI/ML best practices . Act as a thought partner in innovation and experimentation within the team and with external stakeholders. Required Skills & Qualifications Bachelors or Master’s in Computer Science, AI/ML, Data Science, or related field. 5+ years of hands-on experience in ML/NLP , with a recent focus on LLMs and foundation models. Deep knowledge of Hugging Face ecosystem , PyTorch/TensorFlow, LangChain, OpenAI APIs, and popular model libraries. Experience deploying ML models to production using FastAPI, Docker, Kubernetes , or cloud-native tools (AWS/GCP/Azure). Familiarity with vector databases , embeddings, and search frameworks. Strong understanding of model evaluation metrics , bias/fairness in ML, and responsible AI practices. Ability to work cross-functionally with business, legal, and engineering teams. Preferred Qualifications Experience with RLHF (Reinforcement Learning from Human Feedback) . Published work in open-source communities or AI research conferences. Familiarity with multi-modal AI , autoML , or agentic workflows is a plus. Prior work in regulated domains (e.g., finance, healthcare, legal). Why Join Us Work on cutting-edge AI/LLM use cases that span industries and functions. Lead mission-critical AI initiatives from ideation to deployment. Be part of a collaborative, innovation-driven team shaping the next generation of enterprise AI solutions.

Min 1-3 yrs of exp in data science,NLP&Python Exp in PyTorch,Scikit-learn,and NLP libraries(NLTK,SpaCy,Hugging Face) Help deploy AI/ML solutions on AWS,GCP/Azure Exp in SQL for data manipulation & analysis Exp in Big Data processing Spark,Pandas,Dask

About the Role: Grade Level (for internal use): 10 The Team The Capital IQ Solutions Data Science team supports the S&P Capital IQ Pro platform with innovative Data Science and Machine Learning solutions, utilizing the most advanced NLP Generative AI models. This role presents a unique opportunity for hands-on ML/NLP/Gen AI/LLM scientists and engineers to advance to the next step in their career journey and apply their technical expertise in NLP, deep learning, Gen AI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research in LLMs, Gen AI, and related areas. Responsibilities and Impact Design solutions utilizing NLP models including chat assistants and RAG systems. Design and develop custom NLP LLM Models including both prompt engineering techniques and model fine-tunning and alignment (SFT, RLHF, DPO) NLP Model evaluation using both human-supported and synthetic evaluation methods and metrics. Deploy NLP models ensuring latency, reliability, and scalability. Discover new methods for prompt engineering, model fine-tuning, quantization and latency optimization, document embeddings and chunking. Collaborate closely with product teams, business stakeholders, and engineers to ensure smooth integration of NLP models into production systems. Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. Actively research, explore and identify the latest relevant methods and technologies What Were Looking For : Basic Required Qualifications : Degree in Computer Science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field. Good understanding ofmachine learning and deeplearningmethods and their mathematical foundations 5-8 years of professional experience in Advanced Analytics / Data Science / Machine Learning 5-8 years hands-on experience developing NLP models, ideally with transformer architectures. Demonstrated experience with Python, PyTorch, Hugging Face or similar tools. Mastery of Python and ability to write robust and high standard, testable code Knowledge of developing or tuning LLMS Additional Preferred Qualifications 3+ years of experience with implementing information retrieval systems. Experience with contributing to Open Source initiatives or in research projects and/or participation in Kaggle competitions. Publications related to Machine Learning or Deep Learning Ability to work in a team Able to report progress and summarize issues to a less technical audience Curious and open-minded attitude to new approaches About S&P Global Market Intelligence At S&P Global Market Intelligence, a division of S&P Global we understand the importance of accurate, deep and insightful information. Our team of experts delivers unrivaled insights and leading data and technology solutions, partnering with customers to expand their perspective, operate with confidence, andmake decisions with conviction.For more information, visit www.spglobal.com/marketintelligence . Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. 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Manager Data Science Experience: 8-14 Years Exp Salary: 45 LPA to 50 LPA Preferred Notice Period : Within 30 Days Opportunity Type: Office (Hyderabad) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills: Python, LLM, GenAI, Tensorflow, PyTorch, HuggingFace, NLP Blend360 (One of Uplers' Clients) is looking for: About Blend360: Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology, and analytics. The company has two divisions: Data Science Solutions. We work at the intersection of data, technology, and analytics. Talent Solutions: We live and breathe the digital and talent marketplace. Job Description We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models. Interview Process Step 1: Online Assessment Step 2: Technical Screenings 1: 1 Technical Screening with Technical Panel (45 mins) 1 Technical round with Senior Technical Panel (45 mins) Step 3: Technical Interviews 2 : 1 Technical rounds of Interview with Reporting Manager (45 mins) Agenda: To assess on technical parameters giving white board programming, problem solutioning and story telling 1 Technical rounds of Interview with Project Manager (45 mins) To assess on overall fitment Step 4: 1 Project Review (45 mins): 30 mins of presentation any chosen related topic with minimum 6 - 8 slides 10 - 15 mins Question and Answers by panels All interviewers will be part of the discussion. Step 5 : Client Interview (45 mins) How to apply for this opportunity: Easy 3 Step Process: 1. Click On Apply and register or log in to our portal 2.Upload updated Resume & complete the Screening Form 3. Increase your chances of getting shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Responsibilities: Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and the ability to work effectively in a team environment. Primary Skills: Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. AND/OR Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock fortext/audio/image/videomodalities. Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker,FastAPI/Django/Flask,and Git.

Hands on Experience:- NLP/LLM Hugging Face, YOLO, CNNs, Stable Diffusion ML algorithms (regression, decision trees, clustering) Model training/fine-tuning using real-world datasets FastAPI,Flask,Django Docker, Kubernetes Cloud experience

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

Role & responsibilities: Implement and integrate AI tools into business workflows and Automate tasks using no-code platforms and AI APIs. Integrate LLMs, vision models, and other pre-trained AI services (OpenAI, Hugging Face, Google Vertex AI) into internal systems. Deployment, Customization & Fine-tune foundation models using supervised learning, prompt engineering, and custom datasets. Build systems to extract structured data from PDFs and scanned documents using OCR, NLP, and document-understanding models. Design and optimize AI prompts for content generation, customer support, and business analytics. Knowledge in Agent2Agent, MCP Servers, Context Handling Cross-Functional Collaboration. Work with marketing, sales, support, and HR teams to identify and implement AI-driven process improvements. Monitor AI outputs for quality, compliance, and relevance. Ensure responsible and ethical AI usage. Preferred candidate profile: Bachelors/Masters in Computer Science, AI/ML, or related field. Strong programming skills in Python; experience with TensorFlow, PyTorch, Transformers, Scikit-learn. Hands-on experience with LLMs, prompt engineering, and model fine-tuning. Skilled in OCR and document parsing tools (e.g., Tesseract OCR, PDFMiner, LayoutLM, Azure Form Recognizer). Experience in workflow automation tools (e.g., Crew AI, LangChain). Knowledge of REST APIs, microservices, and containerization. Analytical mindset with a focus on process improvement. Perks and benefits: Competitive Salary and Professional development opportunities and training. Opportunity to work with cutting-edge technologies in a fast-paced environment. Collaborative and supportive work environment.

Scale an existing RAG code base for a production grade AI application Proficiency in Prompt Engineering, LLMs, and Retrieval Augmented Generation Programming languages like Python or Java Experience with vector databases Experience using LLMs in software applications, including prompting, calling, and processing outputs Experience with AI frameworks such as LangChain Troubleshooting skills and creative in finding new ways to leverage LLM Experience with Azure Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Experience in python and pyspark will be added advantage Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation Prepare the effort estimates, WBS, staffing plan, RACI, RAID etc. . Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Demonstrate a growth mindset to understand clients' business processes and challenges Preferred technical and professional experience EducationBachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

As an Associate Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors Communicating with internal and external clients to understand and define business needs and appropriate modelling techniques to provide analytical solutions. Evaluating modelling results and communicating the results to technical and non-technical audiences Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides Preferred technical and professional experience Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms Experience and working knowledge in COBOL & JAVA would be preferred

Grade C1/C2 Experience in agent frameworks atleast one of the below CrewAI LangChain agents Autogen AutoGPT / OpenAgents Understand agent roles, memory, planning, and tools .Experience with Prompt engineering (few-shot, chain-of-thought, tool-calling) Fine-tuning or RAG (Retrieval-Augmented Generation) Model selection and deployment (local vs API-based) Vector databases (e.g., Pinecone, Weaviate, Chroma) Tool execution environments (e.g., LangChain tools, custom wrappers) Awareness of model limitations, hallucinations, and how to mitigate them. Full-Stack Engineering Proficiency Ability to build end-to-end systems frontend + backend + infra. Fluency in Python (especially for AI orchestration) TypeScript/React (for building UIs around agents) REST/GraphQL APIs Comfortable integrating models via APIs (OpenAI, Anthropic, HuggingFace). Rapid Prototyping & Iteration Able to build, test, and iterate on Agent workflows Tooling pipelines UI/UX for human-agent interaction Familiarity with hacky proof-of-concept workflows and productionizing them. Product & Systems Thinking Strong sense of product intuition what to build and why. Thinks in terms of goals, user outcomes, system feedback loops , not just features.

Role & responsibilities Focus on designing and developing proof of concepts (PoCs) and demonstrate the solution on a tight schedule. Utilize GenAI no code, low code, and SDKs to build robust GenAI agents that automate business processes. Work with data platforms such as Microsoft Azure, Snowflake, and integration services like Azure Data Factory to build agentic workflow Embed/integrate GenAI agents (Copilot agents) into business platforms such as Workday, Teams, etc Manage small to medium-sized projects with minimal supervision. Automation of complex processes using GenAI agents, especially using the Azure GenAI echo system Advanced Python programming Hands-on experience with data storage systems, especially Snowflake, Azure Data Factory, Azure Fabric, and Azure Synaps Building Copilot agents and embedding them into systems such as Workday, Teams, etc Preferred candidate profile Bachelors or masters degree in AI, computer science, Engineering, mathematics or a related field. 2-4 years of experience in developing and deploying AI/ML solutions to production. Hands-on experience with no code, low code, and SDKs for AI system development. Proficiency in data platforms such as Microsoft Azure, Snowflake, and integration services like Azure Data Factory. Experience with Azure Cloud, Azure AI Foundry, Copilot Studio, and frameworks such LangChain, LangGraph, MCP for building agentic systems. Strong understanding of Agile methodology and project management. Ability to manage projects independently and make decisions under ambiguity.

Job Description: Python Gen AI Developer Seeking an experienced Python Developer with expertise in Generative AI to join our AI & ML Engineering team. The ideal candidate will work on building intelligent applications leveraging large language models (LLMs) and deep learning to enhance customer experience and streamline business processes. Key Responsibilities: Design, develop, and deploy GenAI solutions using Python and modern AI frameworks. Work with LLMs (e.g., GPT, LLaMA, Claude) and fine-tune them for enterprise use cases. Develop prompt engineering strategies and support prompt optimization. Integrate AI models with backend services and data pipelines. Implement scalable and secure APIs and services for GenAI use cases. Collaborate with data scientists, ML engineers, and product teams. Ensure compliance with enterprise security, data governance, and regulatory standards. Required Skills: 5+ years of experience with Python in enterprise application development. Strong knowledge of GenAI tools (OpenAI, HuggingFace, LangChain, etc.). Experience with LLMs, prompt tuning, RAG (Retrieval Augmented Generation). Experience with Flask/FastAPI or similar frameworks. Familiarity with vector databases (e.g., FAISS, Pinecone). Understanding of NLP and transformer models. Good knowledge of Git, Docker, CI/CD. Nice to Have: Knowledge of Azure OpenAI or AWS Bedrock. Experience working in the finance or banking domain. Exposure to Kubernetes and model deployment pipelines

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Pune Location-12th July 2025(Saturday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Pune Date of drive- 12th July 2025(Saturday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

Job Title: Backend Engineer Python + AI Integration Location: India (Hybrid - Preferably Chennai/ Mumbai / Pune) Experience Required: Minimum 5 Years Joining Timeline: Immediate to 30 Days Preferred Role Overview: We are seeking a seasoned Backend Engineer with strong proficiency in Python and a solid understanding of AI/ML model integration . This role is ideal for someone who thrives at the intersection of backend engineering and intelligent systems building scalable APIs, handling data workflows, and integrating machine learning models in production environments. Key Responsibilities: 1. Backend & API Development Develop RESTful and GraphQL APIs using Django, FastAPI, or Flask . Implement async tasks with tools like Celery, RabbitMQ , and webhooks. Design clean, scalable, and secure architecture following SOLID principles . 2. Database Design & Optimization Design, maintain, and optimize PostgreSQL databases JSONB, partitioning, window functions, materialized views, etc. Write complex SQL queries , design ER diagrams, manage schema migrations (e.g., Alembic, Flyway). Troubleshoot performance issues using EXPLAIN plans , handle connection pooling, and resolve deadlocks. 3. AI/ML System Integration Work closely with data scientists to deploy ML models as APIs. Use tools like scikit-learn, PyTorch, Hugging Face, TensorFlow for integrating AI capabilities. Deploy RAG systems using FAISS, Weaviate, Qdrant , and integrate with OpenAI APIs, LangChain, LlamaIndex . Build pipelines with Airflow, Prefect for continuous training and deployment. 4. Infrastructure & DevOps Containerize applications using Docker & Docker Compose . Implement CI/CD pipelines using GitHub Actions, GitLab CI, or Jenkins . Monitor systems using Prometheus, Grafana, ELK, or Sentry . Familiarity with cloud platforms ( AWS, GCP, Azure ) working with S3, Lambda, Cloud SQL, SageMaker , etc. Must-Have Skills: Proficiency in Python and OOP principles. Deep knowledge of PostgreSQL and general RDBMS optimization. Experience with RESTful APIs , async processing, and microservice design. Exposure to AI/ML workflows , including model deployment and monitoring. Knowledge of authentication/authorization standards (OAuth2, JWT). Good-to-Have (Bonus Skills): Experience with LLMs , embedding-based search , and RAG systems . Familiarity with Streamlit/Dash for internal tools and dashboards. Understanding of data governance , PII protection, and anonymization. Exposure to event-driven systems (Kafka, AWS SNS/SQS). Open-source contributions or technical blog writing. Interested Candidates can drop your resume to subashini.gopalan@kiya.ai

RESPONSIBILITIES: Develop, productionize, and deploy scalable, resilient software solutions for operationalizing AI & ML. Deploy Machine Learning (ML) models and Large Language Models (LLM) securely and efficiently, both in the cloud and on-premises, using state of the art platforms, tools, and techniques. Provide effective model observability, monitoring, and metrics by instrumenting logging, dashboards, alerts, etc. In collaboration with Data Engineers, design and build pipelines for extraction, transformation, and loading of data from a variety of data sources for AI & ML models as well as RAG architectures for LLMs. Enable Data Scientists to work more efficiently by providing tools for experiment tracking and test automation. Ensure scalability of built solutions by developing and running rigorous load tests. Facilitate integration of AI & ML capabilities into user experience by building APIs, UIs, etc. Stay current on new developments in AI & ML frameworks, tools, techniques, and architectures available for solution development, both private and open source. Coach data scientists and data engineers on software development best practices to write scalable, maintainable, well-designed code. Agile Project Work Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate AI and MLOps solutions. Act as a positive champion for broader organization to develop stronger understanding of software design patterns that deliver scalable, maintainable, well-designed analytics solutions. Advocate for security and responsibility best practices and tools. Acts as an expert on complex technical topics that require cross-functional consultation. Perform other duties as required. QUALIFICATIONS: Experience applying continuous integration/continuous delivery best practices, including Version Control, Trunk Based Development, Release Management, and Test-Driven Development Experience with popular MLOps tools (e.g., Domino Data Labs, Dataiku, mlflow, AzureML, Sagemaker), and frameworks (e.g.: TensorFlow, Keras, Theano, PyTorch, Caffe, etc.) Experience with LLM platforms (OpenAI, Bedrock, NVAIE) and frameworks (LangChain, LangFuse, vLLM, etc.) Experience in programming languages common to data science such as Python, SQL, etc. Understanding of LLMs, and supporting concepts (tokenization, guardrails, chunking, Retrieval Augmented Generation, etc.). Knowledge of ML lifecycle (wrangling data, model selection, model training, modeling validation and deployment at scale) and experience working with data scientists Familiar with at least one major cloud provider (Azure, AWS, GCP), including resource provisioning, connectivity, security, autoscaling, IaC. Familiar with cloud data warehousing solutions such as Snowflake, Fabric, etc. Experience with Agile and DevOps software development principles/methodologies and working on teams focused on delivering business value. Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking. Ability to communicate complex ideas in a concise way. Fluent with popular diagraming and presentation software. Demonstrated experience in teaching and/or mentoring professionals.

We are seeking a highly skilled and innovative Data Scientist with a strong focus on Generative AI, NLP, and Large Language Models (LLMs). The ideal candidate will design, develop, and deploy end-to-end data science solutions that harness the power of advanced ML, deep learning, and Gen AI technologies to drive real-world impact. Key Responsibilities: Design and implement scalable data science solutions using Generative AI, NLP, and ML techniques. Develop, fine-tune, and evaluate Large Language Models (LLMs) such as GPT, BERT, and similar architectures. Analyze structured and unstructured data to generate actionable insights for business problems. Collaborate cross-functionally with engineering, product, and business teams to integrate AI models into production systems. Conduct cutting-edge research in Gen AI and deep learning; evaluate and apply recent advancements. Build and maintain robust pipelines for model training, evaluation, monitoring, and deployment. Communicate complex technical findings clearly to technical and non-technical stakeholders. Required Skills & Qualifications: Strong hands-on experience with Generative AI, LLMs (e.g., OpenAI, Hugging Face Transformers, etc.). Proven expertise in core NLP tasks: text classification, summarization, named entity recognition, sentiment analysis, etc. Proficient in Python and related libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch. Experience developing, validating, and deploying ML models in production environments. Familiarity with vector databases (e.g., FAISS, Pinecone), embeddings, and semantic search. Exposure to cloud platforms like AWS, Azure, or GCP, and MLOps tools/workflows (CI/CD, model monitoring, etc.). Preferred Qualifications: Experience in prompt engineering, Retrieval-Augmented Generation (RAG), or fine-tuning/customizing LLMs. Contributions to AI research papers, open-source projects, or participation in ML competitions (e.g., Kaggle) is a plus. Knowledge of responsible AI practices, model interpretability, and bias mitigation techniques.

Job Title: Data Scientist (Python) Location: Chennai, Coimbatore, Bangalore, Pune Experience: 4+ Years Job Overview We are looking for a Data Scientist (Python) with strong experience in backend development, data science workflows, and exposure to modern AI/ML technologies. The ideal candidate should be proficient in Python, API development, data handling, and have working knowledge of NLP and LLM models. Key Responsibilities Design and build scalable backend components and APIs using Python and FastAPI Work on data wrangling, feature engineering, and model integration workflows Develop, test, and deploy machine learning/NLP pipelines Implement RESTful APIs to serve ML models and data services Use SQL for data extraction, transformation, and integration Leverage Docker for packaging and deployment Collaborate with DevOps teams on CI/CD workflows Integrate solutions using OpenAI, Hugging Face, and other LLM APIs (e.g., GPT, BERT) Work cross-functionally with data engineers, ML engineers, and business teams Required Skills Strong experience in Python programming Experience with FastAPI or equivalent frameworks Solid knowledge of SQL and data modeling Good grasp of Object-Oriented Programming (OOP) Familiar with Git, Docker, and CI/CD pipelines Exposure to data science workflows, model deployment, and MLOps practices Experience or familiarity with NLP, OpenAI libraries, and Hugging Face models Understanding of Large Language Models (LLMs) like GPT, BERT, etc. Preferred Qualifications Experience working in agile and cross-functional teams Familiarity with cloud platforms like GCP Why Join Us? Join KANINIs award-winning Data Engineering Team, recognized as the "Outstanding Data Engineering Team" at DES 2025 Work on real-world problems at the intersection of data, AI, and product development Be part of a collaborative, innovative, and growth-driven environment Access to cutting-edge tools, leadership support, and continuous learning opportunities Enjoy flexible work options and competitive compensatio

Job Title: Senior Data Scientist | Machine Learning Engineer (MLE) Job Location: [Mohali / Pune] Experience : 4+ years Skill Sets: Expertise in ML/DL, model lifecycle management, and MLOps (MLflow, Kubeflow) Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and Hugging Face models Strong experience in NLP, fine-tuning transformer models, and dataset preparation Hands-on with cloud platforms (AWS, GCP, Azure) and scalable ML deployment (Sagemaker, Vertex AI) Experience in containerization (Docker, Kubernetes) and CI/CD pipelines Knowledge of distributed computing (Spark, Ray), vector databases (FAISS, Milvus), and model optimization (quantization, pruning) Familiarity with model evaluation, hyperparameter tuning, and model monitoring for drift detection Roles & Responsibilities: Design and implement end-to-end ML pipelines from data ingestion to production Develop, fine-tune, and optimize ML models, ensuring high performance and scalability Compare and evaluate models using key metrics (F1-score, AUC-ROC, BLEU etc) Automate model retraining, monitoring, and drift detection Collaborate with engineering teams for seamless ML integration Mentor junior team members and enforce best practices

Job Title: Data Scientist. Job Type: Full-time, Contractor. Job Summary:. We are seeking an innovative and highly skilled Data Scientist to join our customer’s team. In this dynamic role, you will design and deploy advanced Generative AI and LLM solutions, driving impactful real-world applications. Your expertise will directly shape our customer’s AI products, working in a collaborative, forward-thinking environment.. Key Responsibilities:. Develop, fine-tune, and deploy Large Language Models (LLMs) and Generative AI applications for production environments.. Engineer robust RAG (Retrieval Augmented Generation) pipelines utilizing vector stores such as FAISS, Pinecone, or Weaviate.. Implement and optimize prompt engineering strategies for enhanced performance of commercial and open-source LLMs (OpenAI, Anthropic, Hugging Face, etc.).. Integrate NLP techniques and transformer architectures to boost customer’s product capabilities.. Collaborate cross-functionally to define AI-driven product features and recommend technical enhancements.. Write clean, efficient Python code while adhering to best practices in code quality and documentation.. Communicate technical concepts effectively in both written and verbal forms with stakeholders and team members.. Required Skills and Qualifications:. Strong programming proficiency in Python for AI/ML projects.. Hands-on experience with LLM frameworks such as LangChain or Haystack.. Proficient in designing and deploying RAG pipelines, including leveraging vector database technologies (e.g., Redis, FAISS, Pinecone, Weaviate).. Deep understanding of NLP fundamentals and transformer models.. Demonstrated experience with both commercial and open-source LLMs.. Expertise in prompt engineering and embeddings.. Exceptional written and verbal communication abilities, with an emphasis on clarity and collaboration.. Preferred Qualifications:. Experience deploying GenAI applications at scale in production environments.. Background in designing customer-facing AI solutions.. Prior experience collaborating in hybrid or distributed teams.. Show more Show less

Job Title : AI Engineer Location: Chennai Experience: 5+ Years (Hands-On Data Science & AI) Employment Type: Full-Time Work type - Work from office. About the Role We are seeking a skilled AI Engineer with deep hands-on experience in ML, NLP, LLMs, GenAI, and Agentic AI to join our technology team focused on automating US mortgage loan processing workflows. This role involves designing intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure. Key Responsibilities Design and implement ML/NLP/GenAI pipelines for automating loan origination, underwriting, and document intelligence processes. Develop and deploy LLM-based solutions using tools like Ollama, OpenAI, HuggingFace, and integrate via LangChain or similar frameworks. Build and orchestrate Agentic AI systems (e.g., using LangChain Agents, AutoGen, CrewAI) to enable autonomous decision-making, task planning, and loan-processing agents. Fine-tune domain-specific LLMs and embeddings for intelligent document classification, summarization, and question answering. Develop end-to-end MLOps workflows for scalable training, testing, and monitoring of models. Deploy AI models and microservices using Azure (Azure ML, Functions, Blob Storage, App Services). Work with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions. Leverage prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores for contextual mortgage document workflows. Required Skills & Qualifications 5+ years of hands-on experience in Machine Learning, NLP, or LLM-based systems. Proven expertise with LLMs (e.g., OpenAI, Ollama, GPT-4, Mistral) and LangChain / AutoGen / Agentic AI design. Proficiency in Python, Scikit-learn, PyTorch/TensorFlow, Spacy, HuggingFace Transformers. Strong knowledge of Azure Cloud including Azure ML, Azure Functions, Azure DevOps. Experience with MLOps tools like MLflow, Azure ML pipelines, or Kubeflow. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models into production-scale environments. Nice to Have Understanding of US mortgage or lending workflows (1003, 1008, bank statements, etc.). Experience with OCR, document intelligence tools (Azure Form Recognizer, Amazon Textract). Exposure to Agentic AI concepts such as autonomous agents, planning, memory chaining. Knowledge of privacy and compliance frameworks (HIPAA, SOC2) in AI deployments. What We Offer Opportunity to lead GenAI and Agentic AI initiatives for mortgage automation. Access to top-tier tools, frameworks, and cloud platforms. Remote flexibility and career growth in an innovation-first team. Impactful work transforming legacy loan operations through AI. Interested candidates kindly share your resume to SGrace@ca-usa.com.

We are looking for a Senior AI/ML Engineer to join our team and help design, build, and deploy the product. About Us Zonka Feedback is a fast-growing, bootstrapped SaaS company building an AI-first platform that combines machine learning, GenAI, and large-scale analytics. We are working on cutting-edge applications of AI including LLMs , NLP , unsupervised clustering , vector databases , and retrieval-augmented generation (RAG) systems . Key Responsibilities Design and build scalable NLP pipelines , unsupervised clustering models , and semantic search solutions . Develop vectorization pipelines and implement RAG (Retrieval-Augmented Generation) architectures for efficient information retrieval. Fine-tune large language models (LLMs) and craft effective prompt engineering strategies for real-world performance. Evaluate and optimize AI/ML models using tools like LangChain , Evals , Hugging Face , and custom evaluation frameworks. Work closely with backend and product engineering teams to integrate AI capabilities into production systems. Continuously research and implement advancements in AI, ML, and LLMs to keep the product innovative and competitive. Requirements 3 to 6 years of hands-on experience in Machine Learning and NLP . Solid experience in unsupervised learning techniques (clustering, dimensionality reduction, topic modeling, etc.). Strong understanding and experience in vector databases (e.g., FAISS, Pinecone, ChromaDB) and RAG system design . Experience with LLM fine-tuning , prompt engineering , and deployment of AI systems in production. Proficiency in Python and relevant ML/AI libraries such as TensorFlow, PyTorch, Hugging Face, LangChain, and OpenAI APIs. Strong analytical and problem-solving skills with an ability to work in a fast-paced environment. Prior experience building end-to-end AI features that are used in real products is a strong plus. If this sounds like you, we are here to have the next talk. Share your resume on hr@zonkafeedback.com