161 Huggingface Jobs - Page 2

As a Generative AI Solution Architect with IBM Consulting, you are primarily responsible for designing and implementing complex GenAI solutions using IBM WatsonX and Ecosystem Partner Stacks (Microsoft Azure / Open AI, AWS, Aleph Alpha, as well as Open Source). In addition, you are supporting business development, sales as well as the delivery of consulting and system integration projects in Data & AI for our clients. * You have end-to-end technical responsibility during the acquisition, design and delivery of technically complex GenAI projects at scale * You are accountable for the development and productive deployment of scalable Generative AI applications and platforms, particularly within (hybrid) cloud architectures. * You provide consultation and support to clients and colleagues in architecting and selecting the right technology stack for flexible, scalable, and economical GenAI solutions. * You guide and support clients and colleagues in the adoption of development and operational processes for AI solutions, such as Agile DevOps, FinOps, Trustworthy AI and MLOps methodologies. * You stay abreast of the latest developments in the Artificial Intelligence market and research environment, actively participating in knowledge transfer within IBM Consulting, especially when it comes to mentoring junior team members and delivery teams. * You also develop the strategy, vision, and roadmap for GenAI architectures within our consulting business, contributing to both our immediate sales objectives and long-term business growth. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Professional with at least 5-10 years of experience ideally in data and analytics and/or architecture, including 3 years in the design, build, and implementation of AI/Deep Learning & GenAI solutions. * Experienced in architecting AI solutions and managing delivery of highly technical analytics use cases. * Conversant with technical stacks used to support Generative AI use cases (AWS, Google, Microsoft, Watson X). * Familiar with relevant concepts (eg transformer model architectures, prompt engineering, model fine tuning, retrieval augmented generation architectures) and models/technologies (Microsoft Azure / Open AI, AWS, Aleph Alpha, Hugging Face etc as well as Open Source). * Very good at stakeholder management and influencing skills, consultancy skills a very strong plus. * Able to convey complex technical concepts to non-technical stakeholder Preferred technical and professional experience Experienced in architecting AI solutions and managing delivery of highly technical analytics use cases. * Conversant with technical stacks used to support Generative AI use cases (AWS, Google, Microsoft, Watson X). * Familiar with relevant concepts (eg transformer model architectures, prompt engineering, model fine tuning, retrieval augmented generation architectures) and models/technologies (Microsoft Azure / Open AI, AWS, Aleph Alpha, Hugging Face etc as well as Open Source). * Very good at stakeholder management and influencing skills, consultancy skills a very strong plus. * Able to convey complex technical concepts to non-technical stakeholders.* Fluent in English

We are looking for a Technical Architect who has experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as a Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicators. Responsibilities Collaborate with stakeholders (Product Owners, Engineers, Clients) to define and refine software architecture aligned with product vision. Design scalable, modular, and secure system architecture using microservices and modern design patterns. Create high-level product specifications, architecture diagrams, and technical documentation. Provide architectural blueprints, guidance, and technical leadership to development teams. Build and integrate AI-driven components, including Agentic AI (AutoGen, LangGraph), RAG pipelines, and LLM capabilities (Open-source and Commercial models). Define vector-based data pipelines and integrate vector databases such as FAISS, ChromaDB, or Azure AI Search. Lead the implementation of Prompt Engineering strategies to optimize LLM outcomes. Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones. Drive innovation and exploration of emerging technologies, particularly in the field of Generative AI and Intelligent Automation. Requirements 10+ years of hands-on software development experience, with a strong Python background. 3+ years of experience in a Software or Solution Architect role. Proven experience in designing and building production-grade solutions using microservices architecture. Strong expertise in Agentic AI frameworks (AutoGen, LangGraph, CrewAI, LangChain, etc.). Working knowledge of LLMs (Open-source like LLaMA, Mistral; Commercial like OpenAI, Azure OpenAI). Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration. Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc. Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.). Experience with Apache Airflow or other workflow orchestration tools. Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.

About Guidesly: Do you enjoy the Outdoors? Are you an enthusiast who wants to work in a place where you can follow your personal and professional passions? Guidesly is a well-funded startup building software for the Outdoor industry. Mobile apps, SaaS software, product services, and websites; we have a bit of everything. Sophisticated technology and a dream to change the world. If your passion is the outdoors and you want to live your dream, then this is your job. Work with guides, build products, get honest feedback from enthusiasts to create the very best solutions in the marketplace. The outdoor recreation industry includes fishing, wildlife, boating, water sports, snow sports, hunting, ATV, hiking, and biking. We are starting with the fishing vertical in the outdoor recreation industry. The product manager will work with professional guides throughout the United States and enthusiasts in all fishing varieties. Key Responsibilities: Develop and deploy machine learning, deep learning and NLP models for AI applications. Process and analyze large datasets, including feature extraction, vectorization, and embedding-based retrieval. Build and maintain backend systems and APIs to support AI-powered applications. Implement scalable AI solutions in cloud environments, primarily AWS. Develop end-to-end pipelines for model training, testing, and deployment using AWS services such as SageMaker, Bedrock, Lambda, and Step Functions. Optimize AI models for efficiency, scalability, and low-latency inference. Implement MLOps best practices for continuous integration, deployment, and monitoring of AI models. Document system architecture, API specifications, and performance benchmarks. Stay up to date with advancements in AI, including LLMs, FAISS, and deep learning frameworks, to drive innovation. Required Skills & Qualifications: Hands-on experience in AI/ML development, with expertise in natural language processing (NLP) and/or computer vision. Proficiency in Python, SQL, and machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn. Strong understanding of LLM architectures, embeddings, and transformer-based models. Hands-on experience processing large datasets, including feature engineering, embedding retrieval, and vectorization. Experience with Cloud Services (Preferably AWS) for model deployment, data processing, and cloud-based AI solutions. Strong grasp of MLOps principles, including CI/CD pipelines, model monitoring, and workflow automation. Strong analytical and problem-solving skills with a proactive approach to AI model optimization. Excellent communication and teamwork skills to collaborate effectively with engineers, data scientists, and stakeholders. Key Technologies & Tools: Languages & Frameworks: Python, SQL, TensorFlow, PyTorch, Hugging Face Data Processing & Feature Engineering: Vectorization, Embeddings, FAISS Cloud & AI Services: AWS SageMakerAI, Bedrock, Lambda, Step Functions, Inference MLOps & Model Deployment: CI/CD, Model Optimization, API Integration Workflow Automation & AI Infrastructure Key skills: Machine Learning, Deep Learning, Python, SQL, TensorFlow, PyTorch, Hugging Face, AWS SageMakerAI, Lambda, Model Optimization, API Integration, AI Infrastructure

With strong programming exp with Python based deep learning frameworks like Pytorch, JAX, Tensorflow Have strong knowledge of machine learning concepts Exp in cloud platforms (AWS, Azure, or GCP) & infrastructure-as-code tools like Terraform Required Candidate profile Exp in LLMs, RAG architectures, Natural Language Processing(NLP) Python, LlamaIndex /LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript & React.

Independently design, develop, and implement machine learning and NLP models. Build and fine-tune LLM-based solutions (prompt engineering, few-shot prompting, chain of thought prompting). Develop robust, production-quality code for AI/ML applications using Python. Build, deploy, and monitor models using AWS services (SageMaker, Bedrock, Lambda, etc.). Conduct data cleaning, feature engineering, and model evaluation on large datasets. Experiment with new GenAI tools, LLM architectures, and APIs (HuggingFace, LangChain, OpenAI, etc.). Collaborate with senior data scientists for reviews but own end-to-end solutioning tasks. Document models, pipelines, experiments, and results clearly and systematically. Stay updated with the latest in AI/ML, GenAI, and cloud technologies.

Design and deploy AI-powered automation workflows. Build ML/NLP models, create scalable APIs, integrate with CRMs/ERPs, and lead end-to-end AI solution delivery in production.

Roles and Responsibilities: Collaborate with the Drupal and UI teams Gather requirements and provide updates via JIRA/Tracker. Collaborate using version control tools like GIT. Frontend and Backend Development Work with HTML, CSS, PHP, and Drupal frameworks. Ensure high-quality, bug-free code with timely delivery. API Design and Integration Design, develop, and maintain RESTful APIs. Integrate third-party services and APIs seamlessly. Use of AI Tools Utilize generative AI tools and libraries for application development. Performance Optimization Optimize server-side logic for performance and scalability. Database Management Work with both SQL and NoSQL databases. Asynchronous Programming Implement asynchronous programming and task queues. Code Quality and Documentation Write clean, maintainable, and well-documented code. Team Collaboration Work with cross-functional teams to define and implement solutions. CI/CD and Deployment Manage CI/CD pipelines and deploy applications on cloud platforms.

About The Role We seek an innovative professional with expertise in AI tools like Copilot to boost engineering productivity. The role involves identifying bottlenecks, proposing tailored GenAI solutions, and integrating them into networking product development to streamline workflows and drive AI adoption across teams. Technologies: ---- GenAI Algorithms, LLM's, NLP, Hugging Face, RAG, OpenAI models, Microsoft and GitHub Copilot, Agentic AI, AI-powered tools, Advanced python for Datascience, Flash , REST API, debugging tools, parser tools, troubleshooting and investigating capabilities. Required Qualifications: ---- 2+ years using GitHub Copilot, OpenAI, and other AI coding tools to boost development productivity. 2+ years in GenAImodel design, fine-tuning, and deployment. 3+ years in Pythonbuilding AI/ML pipelines, automation tools, and data processing scripts. Hands-on experience applying GenAI/ML for code generation, summarization, workflow automation, and virtual assistants. Delivered AI-driven impact in 23 engineering projects. Ability to identify and develop use cases in BI, automation, and areas like smart troubleshooting and adaptive testing. Proficient in LLMs, NLP, and AI/ML for software and networking applications. Knowledge of integrating AI with platforms like Webex, Zoom, and Teams via APIs. Skilled in scripting, automation, and AI-augmented workflows. Experienced in Agile/Scrum. Strong problem-solving, communication, and mentoring skills; able to work independently and collaboratively. Desired Skills: --- GitHub Copilot certification. Experience with networking products software development. Familiarity with CI/CD, DevOps, and automation tools. Understanding of responsible AI practices. Experience with data analysis and visualization for AI productivity. Knowledge of cloud-based AI services and integrations. Primary Skills GenAI, LLMs, AI Tools, Python

Overview: Be part of an innovative and forward-thinking environment! Join our dynamic IT team as a full-time AI/ML Engineer and take advantage of exciting growth opportunities. Requirement: Experience: 3+ Years Mandatory skills: ML & AI: ScikitLearn, TensorFlow, PyTorch, XGBoost, SHAP, LIME, LSTM, TimeSeries Forecasting NLP & LLMs: LangChain, HuggingFace, Transformers, FAISS, RAG, Gemini APIs, BLIP2 Register for a Global opportunity on the world's first & only Global Technology Job Portal: www.iitjobs.com Download our app on the Apple App Store and Google Play Store! Refer and earn 50,000!

You will be responsible for designing, developing, and deploying AI agents powered by LLMs such as GPT-4 Claude and Gemini. Your role will involve integrating AI agents with various tools, APIs, databases, and automation frameworks. You will be required to develop reusable prompt chains and workflows for common tasks and decision-making processes. Additionally, you will utilize frameworks like LangChain, AutoGen, CrewAI, or Semantic Kernel to manage multi-agent architectures. Your tasks will also include fine-tuning or instructing LLMs for specific use-cases or industry applications, as well as optimizing performance, reliability, and cost-efficiency of AI workflows. Collaboration with data scientists, product managers, and engineers to design end-to-end AI solutions is an essential part of this role. Furthermore, you will implement automation in internal tools, customer interactions, or operational pipelines using AI agents. To be successful in this position, you must have strong experience with LLMs such as OpenAI GPT, Anthropic Claude, or Meta Llama. Hands-on experience with agentic frameworks like LangChain, AutoGen, CrewAI, etc., is required. Proficiency in Python and relevant AI libraries such as HuggingFace, Transformers, LangChain is a must. A solid understanding of prompt engineering and retrieval-augmented generation (RAG) is also necessary. Knowledge of automation tools like Zapier, Make, Airflow, or custom Python automation will be beneficial. Previous experience working with APIs, webhooks, and data integrations is essential. Nice-to-have qualifications include experience with vector databases like Pinecone, Weaviate, FAISS, and knowledge of fine-tuning or customizing open-source LLMs. Familiarity with cloud platforms such as AWS, GCP, Azure, and deployment of AI solutions is an added advantage. Experience with UI/UX for chatbot or agent interfaces would also be beneficial. Joining Rysysth Technologies as an AI Agent Developer will provide you with exciting challenges and opportunities to work with cutting-edge technologies in the AI space.,

About MOTM Technologies MOTM Technologies is a fast-growing growth consulting and technology company helping over 150+ businessesespecially in engineering, manufacturing, and B2B sectorsscale through marketing, automation, and business transformation. We are currently building a AI based saas applications which solves the real world problems which has the ability to significantly increase the business efficiency. Role Summary Were looking for a visionary yet hands-on CTO to lead the end-to-end product development of our AI-driven SaaS platform. This includes architecting the system, integrating external APIs and automation tools, overseeing engineering execution, and helping take the product from MVP to scale. This is a strategic leadership position for someone who wants to build from scratch , drive a lean product team, and own long-term product outcomes. Compensation includes a profit-sharing model from Day 1 and access to future ESOPs as we raise funding and expand. Key Responsibilities Define the technical architecture and oversee the complete build of the business automation suite Integrate tools like OpenAI, Make.com, Apify, Airtable, Glide, Twilio , etc., into a seamless user flow Design and deploy AI agents for tasks like lead generation, CRM, content creation, outreach, and more Manage internal tech team (developers, AI engineers, testers) and ensure MVP speed + quality Collaborate directly with the founder to define product roadmap, module structure, and execution plan Handle product deployment, performance, uptime, and data privacy in a secure cloud environment (AWS Lightsail preferred) Must-Have Skills 3–6 years of experience in full-stack or backend development , ideally in SaaS, automation, or AI products Proven experience in API integrations , especially across CRM, scraping, messaging, or analytics tools Strong understanding of AI prompt design , LLM integrations, and intelligent automation Experience with no-code/low-code platforms like Make.com, Airtable, Glide, etc. Comfort with cloud environments like AWS, version control (Git), and building scalable modular architecture Entrepreneurial and product-first mindset, with an obsession for solving real-world business problems What MOTM Offers Strategic Leadership Role in a company with a proven track record in business growth and consulting Profit-sharing from Day 1 based on product revenue and impact Access to ESOP pool once scale and funding milestones are met A lean, execution-driven work culture where you drive product ownership Work on a real-world product with active paying customers and validated market demand

We are seeking developers who are eager to grow, experiment, and work on challenging technical problems. As an AI/ML Engineer-I at GeekyAnts, you'll be joining a fast-paced environment where you'll contribute to real projects from Day 1 and gain exposure to the latest trends in software engineering and AI. Key Responsibilities Write clean, efficient, and scalable code in Python. Work closely with cross-functional teams to design, develop, and deliver high-quality software solutions. Collaborate with senior developers and team leads for code reviews and knowledge sharing. Continuously learn and adapt to new technologies and frameworks. Contribute to project discussions, documentation, and team activities. Ideal Candidate Profile Technical Skills: Strong grasp of Python programming (Mandatory). Completed a Python course or certification from a recognized institute (Preferred). Basic understanding of Artificial Intelligence or exposure to AI projects is a plus. Familiarity with version control (e.g., Git) and collaborative tools (e.g., Jira, Slack) is appreciated. Soft Skills: Excellent verbal and written communication skills. Strong problem-solving mindset and willingness to take initiative. • Open to feedback and capable of working in a dynamic, team-oriented setting.

You will be joining Observe.AI, a company that is revolutionizing customer service by leveraging AI agents to automate routine customer calls and workflows, support agents in real time, and uncover insights from interactions. Trusted by renowned brands, Observe.AI aims to enhance automation, provide faster and consistent service, and foster stronger customer loyalty. As a part of the Machine Learning team at Observe.AI, you will play a pivotal role in developing cutting-edge AI capabilities for the company's product offerings. Your responsibilities will include designing and implementing state-of-the-art AI solutions, optimizing ML models and processing pipelines, and collaborating with cross-functional teams to address business challenges. To excel in this role, you should possess a Bachelor's or Master's degree in Computer Science or a related field, along with at least 5 years of experience in building large-scale NLP systems. A strong understanding of ML and NLP fundamentals, proficiency in Python and ML frameworks like Pytorch and Tensorflow, and the ability to provide thought leadership in technical areas are essential requirements. Additionally, experience with Spoken Language Understanding, published papers in NLP conferences, and open-source contributions are considered advantageous. Observe.AI offers a competitive compensation package, including medical insurance, leaves as per regulations, generous holidays, learning and development support, and flexible benefit plans. The company is committed to fostering an inclusive and diverse workplace, welcoming individuals from all backgrounds and encouraging them to apply. If you are passionate about leveraging AI to drive innovation in customer service, and if you possess the required skills and experience, we invite you to be a part of Observe.AI's mission to redefine customer interactions and experiences.,

Short Description: Key responsibilities: 1. Product Strategy & Vision (AI/ML & Scale) 2. Technical Product Development & Execution Leadership 3. People Management & Team Leadership 4. Technical Expertise & Hands-On Contribution 5. Cross-functional Collaboration & Stakeholder Management Description: Product Strategy & Vision (AI/ML & Scale): Define and evangelize the product vision, strategy, and roadmap for our AI/ML platform, data pipelines, and scalable application infrastructure, aligning with overall company objectives. Identify market opportunities, customer needs, and technical trends to drive innovation and competitive advantage in the AI/ML and large-scale data domain. Translate complex technical challenges and opportunities into clear, actionable product requirements and specifications. Product Development & Execution Leadership: Oversee the entire product lifecycle from ideation and discovery through development, launch, and post-launch iteration for critical AI/ML and data products. Work intimately with engineering, data science, and operations teams to ensure seamless execution and delivery of high-quality, performant, and scalable solutions. Champion best practices for productionizing applications at scale and ensuring our systems can handle huge volumes of data efficiently and reliably. Define KPIs and metrics for product success, monitoring performance and iterating based on data-driven insights. People Management & Team Leadership: Lead, mentor, coach, and grow a team of Technical Product Managers, fostering a culture of innovation, accountability, and continuous improvement. Provide clear direction, set performance goals, conduct regular reviews, and support the professional development and career growth of your team members. Act as a leader and role model, promoting collaboration, open communication, and a positive team environment. Technical Expertise & Hands-On Contribution: Possess a deep understanding of the end-to-end ML lifecycle (MLOps), from data ingestion and model training to deployment, monitoring, and continuous improvement. Demonstrate strong proficiency in Google Cloud Platform (GCP) services, including but not limited to, compute, storage, networking, data processing (e.g., BigQuery, Dataflow, Dataproc), and AI/ML services (e.g., Vertex AI, Cloud AI Platform). Maintain a strong hands-on expertise level in Python programming , capable of contributing to prototypes, proof-of-concepts, data analysis, or technical investigations as needed. Extensive practical experience with leading AI frameworks and libraries, including Hugging Face for natural language processing and transformer models. Proven experience with LangGraph (or similar sophisticated agentic frameworks like LangChain, LlamaIndex), understanding their architecture and application in building intelligent, multi-step AI systems. Solid understanding of agentic frameworks, their design patterns, and how to productionize complex AI agents. Excellent exposure to GitHub and modern coding practices , including version control, pull requests, code reviews, CI/CD pipelines, and writing clean, maintainable code. Cross-functional Collaboration & Stakeholder Management: Collaborate effectively with diverse stakeholders across engineering, data science, design, sales, marketing, and executive leadership to gather requirements, communicate progress, and align strategies. Act as a bridge between technical teams and business stakeholders, translating complex technical concepts into understandable business implications and vice-versa. Responsibilities: Technical Skills: Deep expertise in Google Cloud Platform (GCP) services for data, AI/ML, and scalable infrastructure. Expert-level hands-on Python programming skills (e.g., for data manipulation, scripting, API interaction, ML prototyping, productionizing) Strong working knowledge of Hugging Face libraries and ecosystem. Direct experience with LangGraph and/or other advanced agentic frameworks (e.g., LangChain, LlamaIndex) for building intelligent systems. Solid understanding of software development lifecycle, GitHub , Git workflows, and modern coding practices (CI/CD, testing, code quality). Qualifications: Education: Bachelors or Master’s degree in Computer Science, Engineering, or a related technical field. Experience: 8+ years of progressive experience in technical product management roles, with a significant portion focused on AI/ML, data platforms, or highly scalable systems. 3+ years of direct people management experience, leading and mentoring a team of product managers or technical leads. Demonstrable track record of successfully bringing complex technical products from concept to production at scale. Proven ability to manage products that handle massive volumes of data and require high throughput. Extensive practical experience with AI/ML model deployment and MLOps best practices in a production environment. Leadership & Soft Skills: Exceptional leadership, communication, and interpersonal skills, with the ability to inspire and motivate a team. Strong analytical and problem-solving abilities, with a data-driven approach to decision-making. Ability to thrive in a fast-paced, ambiguous, and rapidly evolving technical environment. Excellent ability to articulate complex technical concepts to both technical and non-technical audiences.

Short Description: Ford Artificial Intelligence Advancement Center is looking for professionals experienced in NLP/LLM/GenAI, who are hands-on and can employ many NLP/Prompt engineering techniques from traditional statistical/ML NLP to DL-based sequence models and transformers in their day-to-day work. Description: You'll be working alongside leading technical experts from all around the world, on a variety of products involving Sequence/token classification, QA/chatbots, translation, semantic/search and summarization, among others. Responsibilities: Design NLP/LLM/GenAI applications/products by following robust coding practices, Explore SoTA models/techniques so that they can be applied for automotive industry usecases Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions, Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools. Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.,) Converge multibots into super apps using LLMs with multimodalities. Develop agentic workflow using Autogen, Agentbuilder, langgraph Build modular AI/ML products that could be consumed at scale. Qualifications: Education : Bachelors or master’s degree in computer science, Engineering, Maths or Science Performed any modern NLP/LLM courses/open competitions is also welcomed. Technical Requirements : Soft Skills : Strong communication skills and do excellent teamwork through Git/slack/email/call with multiple team members across geographies. GenAI Skills : 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. ML/DL Skills : 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 NLP Skills : 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. Python Project Management Skills Familiarity in the use of Docker tools, pipenv/conda/poetry env Comfort level in following Python project management best practices (use of setup.py, logging, pytests, relative module imports,sphinx docs,etc.,) Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.,) Cloud Skills and Computing : 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. Deployment Skills : 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. UI : 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. Miscellaneous Skills : Data Engineering: Skillsets to perform distributed computing (specifically parallelism and scalability in Data Processing, Modeling and Inferencing through Spark, Dask, RapidsAI or RapidscuDF) Ability to build python-based APIs (e.g.: use of FastAPIs/ Flask/ Django for APIs) Experience in Elastic Search and Apache Solr is a plus, vector databases.

Senior Engineer (GenAI & Prompt Engineering) Company : Xebia | Job Type : Fulltime| Location : Hybrid Chennai, Bangalore, Hyderabad, Pune, Jaipur, Bhopal, Gurugram (India) Job Summary Xebia is hiring an experienced GenAI Engineer to lead initiatives embedding LLMs into internal DevOps and Engineering workflows. This is a hands-on opportunity for AI engineers with strong Python and prompt engineering skills. Key Responsibilities Design and optimize LLM prompts for contextual accuracy Build RAG architectures using FAISS, Pinecone, Weaviate , etc. Integrate LLMs into CI/CD pipelines, dashboards, internal tools Use LangChain, LlamaIndex, HuggingFace, Haystack frameworks Fine-tune LLMs (OpenAI, Claude, Cohere, Mistral) for enterprise use cases Ensure compliance, security, and performance of AI systems Collaborate across teams to identify automation opportunities Required Skills & Experience 6-10 years total experience with 2+ years in GenAI/LLM/NLP systems Strong in Python, vector DBs, embedding techniques Hands-on with LLM APIs , GenAI libraries, and NLP concepts Prior experience building contextual AI agents or CI/CD automation using LLMs Nice to Have Familiarity with multi-modal models , DevSecOps, Kubernetes Experience with developer-facing GenAI use cases (log triage, changelogs, copilots) Other Details Mode : Hybrid (3 days a week in-office) Locations : Chennai / Bangalore / Hyderabad / Pune / Jaipur / Bhopal / Gurugram Notice Period : Immediate to max 2 weeks Contract Role To Apply Send the following details to vijay.s@xebia.com : Full Name Total Experience Current CTC Expected CTC Current Location Preferred Xebia Location Notice Period / Last Working Day Primary Skills LinkedIn Profile Keywords : GenAI, Prompt Engineering, RAG, LangChain, Python, FAISS, LLM, LangChain, Vector DB, HuggingFace, LlamaIndex, CI/CD, Automation, DevOps, AI, NLP

Dear Candidate, We are looking for an experienced Machine Learning Engineer to develop and deploy ML models for real-world applications. If you have expertise in Python, TensorFlow, and data science pipelines, wed love to hear from you! Key Responsibilities: Design, develop, and deploy machine learning models for predictive analytics. Work with large datasets to train and fine-tune models. Optimize model performance and scalability. Implement MLOps practices for model deployment and monitoring. Collaborate with data scientists and engineers on AI/ML projects. Required Skills & Qualifications: Strong programming skills in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn). Experience with deep learning, NLP, or computer vision. Knowledge of cloud-based ML services (AWS SageMaker, Azure ML, Google AI). Familiarity with data preprocessing, feature engineering, and model evaluation. Understanding of MLOps and CI/CD for machine learning pipelines. Soft Skills: Strong analytical and problem-solving abilities. Ability to work with cross-functional teams. Excellent communication and presentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

As a visionary technical co-founder, you will combine engineering excellence with philosophical depth to embark on the journey of building something rare, intelligent, and deeply rooted. You will be driven by first-principle problem solving and AI that reasons instead of merely responding. Your role will involve leading the technical architecture of a foundational AI product while embodying the qualities of humility to listen and the conviction to build. Your core responsibilities will revolve around spearheading the design, development, and iteration of VIKAS AI's reasoning engine. This will include building and fine-tuning LLMs, integrating RAG pipelines, and designing multi-agent systems. You will architect systems that strike a balance between cultural depth, emotional nuance, and technical performance. Collaborating closely with the team, you will shape core product features such as culturally intelligent LLMs, an aesthetically curated image engine, and a short-form AI news video layer. Additionally, you will co-create the technical roadmap, hire the early team, and oversee the infrastructure. To excel in this role, strong experience in machine learning, NLP, and LLMs is essential. You should be proficient with Transformers, LangChain, HuggingFace, or similar frameworks and possess solid knowledge of Python, vector databases, and inference infrastructure. Experience with RAG (Retrieval-Augmented Generation) and agent-based architectures, as well as familiarity with embedding models, fine-tuning, and prompt engineering, will set you up for success. An added advantage would be an interest in Indic language modeling or symbolic reasoning, experience in building low-latency, high-context systems, and an eye for clean code, ethics, and culture. Beyond your technical skills, your philosophical outlook and values will play a crucial role in defining who you are as a builder-philosopher. Your commitment to cultural intelligence, ethical AI, and context-aware systems will be evident as you strive to bridge the gap in current AI capabilities. You will prioritize truth over hype, depth over speed, and alignment over noise, reflecting a holistic approach to your work. In return for your contributions, you will receive co-founder status with meaningful equity, the opportunity to be at the forefront of building a product with global potential and local essence, complete creative and architectural freedom to innovate from the ground up, and the guidance of a visionary founder who is relentless, clear, and deeply committed. This role offers you the chance to not just follow existing trends but to redefine the narrative by putting India on the map through innovative thinking and impactful solutions. If you are intrigued by this opportunity and resonate with the vision outlined, feel free to reach out by DM or email at vikasai150807@gmail.com. Let's engage in conversations that transcend mere features and delve into shaping promising futures.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

As an AI and Machine Learning Engineer at Dailoqa, you will play a crucial role in shaping the future of Financial Services clients and the company as a whole. Working directly with the founding team, you will have the opportunity to apply the latest AI techniques to address real-world problems encountered by Financial Services clients. Your responsibilities will include designing, constructing, and enhancing datasets to assess and continually enhance our solutions, as well as engaging in strategy and product ideation sessions to influence our product and solution roadmap. Key Responsibilities: - Agentic AI Development: Build scalable multi-modal Large Language Model (LLM) based AI agents using frameworks such as LangGraph, Microsoft Autogen, or Crewai. - AI Research and Innovation: Research and develop innovative solutions for relevant AI challenges such as Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, fine-tuning, and reasoning in LLMs. - Technical Expertise: Demonstrate proficiency in a technology stack comprising Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React. - LLM and NLP Experience: Hands-on experience with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems. - Dataset Development: Establish a strong track record of constructing datasets for training and/or evaluating machine learning models. - Customer Focus: Dive deep into the domain, comprehend the problem, and concentrate on delivering value to the customer. - Adaptability: Thrive in a fast-paced environment and demonstrate enthusiasm for joining an early-stage venture. - Model Deployment and Management: Automate model deployment, monitoring, and retraining processes. - Collaboration and Optimization: Collaborate with data scientists to review, refactor, and optimize machine learning code. - Version Control and Governance: Implement version control and governance for models and data. Required Qualifications: - Bachelor's degree in computer science, Software Engineering, or a related field. - 4-8 years of experience in MLOps, DevOps, or similar roles. - Strong programming experience and familiarity with Python-based deep learning frameworks like PyTorch, JAX, Tensorflow. - Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform. Desired Skills: - Experience with experiment tracking and model versioning tools. - Proficiency with the technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React. - Knowledge of data pipeline orchestration tools like Apache Airflow or Prefect. - Familiarity with software testing and test automation practices. - Understanding of ethical considerations in machine learning deployments. - Strong problem-solving skills and ability to work in a fast-paced environment.,

Job Title: Senior AI Engineer (Clinical Research) Required Experience: 3+ years Location: Pune Job Description: We are seeking a highly skilled and experienced Senior AI Engineer to lead the development and deployment of advanced artificial intelligence and machine learning solutions for clinical research initiatives. This role will drive innovation in clinical data extraction, patient cohort analysis, protocol optimization, and predictive modeling to support better decision-making and operational efficiencies in clinical trials. This position requires a strong combination of technical expertise, leadership skills, and business acumen . Key Responsibilities 1. AI/ML Development & Deployment Develop and deploy machine learning models for extracting, classifying, and analyzing structured and unstructured clinical data (e.g., EMRs, CRFs, protocols). Apply NLP techniques for entity recognition, relationship extraction, summarization, and semantic search of clinical trial texts. Build predictive models for trial success, patient recruitment, dropout risk, and adverse event detection. Lead the development of GenAI workflows, including LLM/SLM/VLM-based pipelines and multi-modal AI applications. Implement computer vision and OCR/IDP models for clinical document processing and imaging. 2. RAG (Retrieval-Augmented Generation) & LLM Engineering Design and optimize RAG workflows, including embedding and retrieval pipelines. Work with Gemini Flash 2.5 or similar models (e.g., GPT-4, Claude) for LLM-based clinical data tasks. Fine-tune prompt engineering, context window optimization, and chunking strategies. Integrate and manage vector stores such as FAISS, Chroma, or Vertex AI Matching Engine. 3. Data Engineering & Pipelines Collaborate with data engineers to build scalable pipelines for ingesting and transforming clinical and biomedical data (e.g., PubMed, CT.gov, EHR, imaging). Handle data cleansing, harmonization, annotation, and transformation for ML readiness. Develop ingestion processes for structured and unstructured sources: PDF, SCORM, HTML, internal documents. 4. Evaluation, Monitoring & Regulatory Compliance Evaluate models using domain-specific metrics (e.g., precision@k, response confidence) and build continuous feedback loops. Ensure transparency, explainability, and reproducibility in model design. Maintain compliance with HIPAA, GDPR, and GxP/ISO 13485 standards. 5. Leadership & Collaboration Lead and mentor a team of junior data scientists and ML engineers. Define and drive AI strategy aligned with clinical and regulatory objectives. Collaborate with clinical scientists, statisticians, product managers, and regulatory teams to translate clinical goals into technical AI solutions. 6. Project & Technical Ownership Own end-to-end execution of AI projects: scoping, design, development, deployment, monitoring. Provide technical direction in deep learning (CNNs, Capsule Networks, Variational Autoencoders, Graph Neural Networks). Ensure MLOps best practices, including CI/CD, monitoring, logging, and governance in cloud environments. Technical Skills & Experience Must-Have: Proficiency in Python (FastAPI/Flask), LangChain, HuggingFace, and vector database integrations. Experience with embedding techniques and vector similarity (cosine, dot product, top-k retrieval). Hands-on experience with GenAI models (e.g., Gemini Flash 2.5, GPT-4, Claude). Knowledge of biomedical ontologies (UMLS, SNOMED CT, MeSH) and EDC systems. Familiarity with CDISC, HL7 FHIR, and OMOP CDM standards for clinical data. Proven experience in deploying AI models on cloud platforms: AWS SageMaker, GCP Vertex AI, or Azure ML. Desirable: Exposure to MLOps, scientific ML, and data visualization tools. Experience with Google Cloud (AlloyDB, Vertex AI APIs, secure deployments). Working knowledge of LMS content ingestion (PDFs, SCORM, HTML). Familiarity with frameworks like LlamaIndex or Haystack. Qualifications Bachelors or Masters in Computer Science, Biomedical Engineering, Data Science, or related field. PhD preferred. 3+ years of AI/ML experience, with 1+ years in clinical research or healthcare. Strong leadership, communication, and stakeholder management skills. Demonstrated success in translating complex clinical problems into deployable AI solutions.

GenAI, NLP, or LLM based systems , strong Python development skills and working Artificial Intelligence, Python, AWS, Machine Learninges and embedding techniques

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 Experience in python and pyspark will be added advantage

As a Generative AI Senior Developer with IBM Consulting, you are primarily responsible for designing and implementing complex GenAI solutions using IBM WatsonX and Ecosystem Partner Stacks (Microsoft Azure / Open AI, AWS, Aleph Alpha, as well as Open Source). In addition, you are supporting business development, sales as well as the delivery of consulting and system integration projects in Data & AI for our clients. * You have end-to-end technical responsibility during the acquisition, design and delivery of technically complex GenAI projects at scale * You are accountable for the development and productive deployment of scalable Generative AI applications and platforms, particularly within (hybrid) cloud architectures. * You provide consultation and support to clients and colleagues in architecting and selecting the right technology stack for flexible, scalable, and economical GenAI solutions. * You guide and support clients and colleagues in the adoption of development and operational processes for AI solutions, such as Agile DevOps, FinOps, Trustworthy AI and MLOps methodologies. * You stay abreast of the latest developments in the Artificial Intelligence market and research environment, actively participating in knowledge transfer within IBM Consulting, especially when it comes to mentoring junior team members and delivery teams. * You also develop the strategy, vision, and roadmap for GenAI architectures within our consulting business, contributing to both our immediate sales objectives and long-term business growth. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Professional with at least 6-10 years of experience ideally in data and analytics and/or architecture, including 3 years in the design, build, and implementation of AI/Deep Learning & GenAI solutions. * Experienced in architecting AI solutions and managing delivery of highly technical analytics use cases. * Conversant with technical stacks used to support Generative AI use cases (AWS, Google, Microsoft, Watson X). * Familiar with relevant concepts (eg transformer model architectures, prompt engineering, model fine tuning, retrieval augmented generation architectures) and models/technologies (Microsoft Azure / Open AI, AWS, Aleph Alpha, Hugging Face etc as well as Open Source). * Very good at stakeholder management and influencing skills, consultancy skills a very strong plus. * Able to convey complex technical concepts to non-technical stakeholder Preferred technical and professional experience Experienced in architecting AI solutions and managing delivery of highly technical analytics use cases. * Conversant with technical stacks used to support Generative AI use cases (AWS, Google, Microsoft, Watson X). * Familiar with relevant concepts (eg transformer model architectures, prompt engineering, model fine tuning, retrieval augmented generation architectures) and models/technologies (Microsoft Azure / Open AI, AWS, Aleph Alpha, Hugging Face etc as well as Open Source). * Very good at stakeholder management and influencing skills, consultancy skills a very strong plus. * Able to convey complex technical concepts to non-technical stakeholders.* Fluent in English

Job Title: Software Engineer Job Type: Full-Time Experience Level: Mid-Level (4 - 6 years) What You Can Expect from the Job As a Mid-Level AI Engineer focused on Large Language Model (LLM) development , you will: Build and optimize LLM-powered applications using LangChain , CrewAI , and other orchestration tools. Implement context management protocols to improve model memory and performance. Design and deploy user-friendly interfaces using OpenWebUI for interacting with LLMs. Prepare and manage datasets for training, fine-tuning, and inference. Integrate vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG) pipelines. Collaborate with cross-functional teams on prompt engineering, agent workflows, and intelligent automation. Stay current with the latest developments in LLMs, open-source tools, and AI research. Contribute to scalable, ethical, and production-ready AI systems. What Will Help You Do the Job Well Must have skills/characteristics 46 years of experience in AI/ML engineering, with a focus on NLP or LLMs. Strong proficiency in Python and experience with frameworks like LangChain , CrewAI , and Transformers (Hugging Face) . Hands-on experience with OpenWebUI for deploying and managing LLM interfaces. Solid understanding of model context protocols , token limits, and memory handling. Experience in data preparation , including cleaning, labelling, and formatting for LLM workflows. Familiarity with vector databases , embedding models , and retrieval systems . A collaborative mindset and the ability to work in fast-paced, agile environments. Other desirable skills/characteristics Experience with agent-based architectures and multi-agent coordination. Knowledge of LLMOps , model deployment, and monitoring tools. Familiarity with Microsoft Co-pilot and its integration into enterprise workflows. Contributions to open-source AI projects or research publications. Knowledge if ISMS Principles and best practices. Willingness to Travel domestic/international. Thank you for your interest with CCS. We hope you find a meaningful career! Please send your profiles to careers@ccs-technologies.com We will Trust, Recognize, Care You will – Learn, Contribute, Grow