813 Llms Jobs

• Proficiency with Python (Pandas, NumPy), SQL & Java • Experience with LLMs, Lang Chain, & Generative AI technologies • Familiarity with ML frameworks (TensorFlow, PyTorch) & data engineering tools (Spark, Kafka) • Build ML, NLP & recommender models Required Candidate profile • Understanding of key data engineering concepts like data lakes, columnar formats, ETL tools, & BI tools • ML, NLP, Recommender system, personalization, Segmentation, microservice architecture & API

As an AI/ML Lead with Gen AI expertise at ParadigmIT, your role will involve architecting, developing, and delivering cutting-edge AI solutions. Your focus will be on Gen AI systems that have a significant impact on business outcomes. Key Responsibilities: - Architect and deliver AI/ML models and Gen AI solutions, taking projects from prototype to production - Provide technical leadership by setting the direction for AI/ML project pipelines, ensuring best practices and rigorous implementation - Lead end-to-end product architecture, design, development, and deployment - Implement Gen AI models such as LLMs for text generation, image processing, voice, video, and conversation AI in practical applications - Define technical strategy and mentor team members Qualifications: - Minimum of 7 years of experience in AI/ML, with a focus on Gen AI projects - Proficiency in Python or similar languages, along with expertise in ML/Gen AI frameworks for developing, fine-tuning, and deploying generative models - Experience in product architecture, design, and development - Demonstrated track record of building Gen AI products using LLMs, model fine-tuning, and API integration - Ability to lead teams, define technical strategies, and mentor junior team members - Strong coding skills, effective communication, and problem-solving abilities,

Role Overview: We are looking for a Data Scientist with a strong foundation in data analysis, exploratory data analysis (EDA), and applied statistics. The ideal candidate should have experience working with Python, SQL, and key data science libraries for data wrangling, visualization, and model building. Key Responsibilities: 4-6 years of experience Design, build, and deploy machine learning and generative AI models. Work with large datasets to extract insights and build predictive/analytical solutions. Apply NLP, LLMs, and GenAI frameworks to real-world use cases. Collaborate with cross-functional teams to identify business needs and deliver AI-driven solutions. Fine-tune pre-trained models (LLMs, transformers) for domain-specific tasks. Stay updated with latest GenAI advancements and apply them effectively. Required Skills & Qualifications: Strong background in Python, data science libraries (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Hands-on experience with Generative AI, LLMs, transformers, or diffusion models. Experience with NLP techniques, prompt engineering, and model fine-tuning. Familiarity with cloud platforms (AWS / Azure / GCP) and MLOps practices. Good understanding of data preprocessing, feature engineering, and model evaluation. Strong problem-solving and communication skills. Show more Show less

Key Responsibilities Leadership and Team Management Lead, manage, and mentor a high-performing team of data scientists, ensuring excellence in technical execution and professional development. Define, implement, and refine the data science strategy and roadmap, aligning with the organization&aposs long-term goals and evolving business needs. Cultivate a culture of technical innovation, collaboration, and continuous learning within the data science team. Strategic Collaboration and Communication Partner with senior leadership to identify and address strategic opportunities and challenges through data science initiatives. Present complex, data-driven insights and strategic recommendations to executive stakeholders, driving high-level decision-making. Develop and nurture relationships with key stakeholders across the organization, ensuring effective collaboration and alignment on data-driven projects. Innovation and Research Drive the development and deployment of state-of-the-art data science methodologies, leveraging the latest advancements in machine learning, artificial intelligence, LLMs, and computational techniques. Conduct pioneering research in emerging areas of data science, integrating new technologies and methodologies to solve complex business problems. Lead the evaluation and adoption of advanced tools, technologies, and frameworks to enhance the organization&aposs data science capabilities. Project Management and Execution Oversee the execution of complex, high-impact data science projects, ensuring they meet rigorous technical standards, deadlines, and business objectives. Ensure the scalability, reliability, and robustness of data science solutions through advanced model development, deployment, and monitoring practices. Proactively manage project risks and mitigate potential issues, ensuring successful delivery and alignment with strategic goals. Thought Leadership and Continuous Learning Serve as a thought leader in the data science field, representing the organization at industry events, conferences, and forums with high-level presentations and publications. Promote a culture of continuous learning and technical excellence within the data science team and across the organization. Contribute to the organization&aposs intellectual capital through research, white papers, and industry collaborations. Qualifications Ph.D., Masters or Bachelors in Data Science, Computer Science, Statistics, Mathematics, or a related field. 10+ years of experience in data science or a related field, with a proven track record of leading and executing high-impact, technically complex projects. Extensive expertise in advanced machine learning algorithms, deep learning, statistical modeling, LLM, and AI, with hands-on experience in cutting-edge techniques. Mastery of programming languages such as Python, with extensive experience in advanced machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Keras). Advanced skills in SQL and hands-on experience with big data technologies. Demonstrated expertise in MLOps/LLMOps practices, including model deployment, monitoring, and optimization at scale. Exceptional problem-solving, analytical, and strategic thinking skills, with the ability to tackle the most complex data challenges. Proven leadership abilities, with experience managing and developing high-performing technical teams. Outstanding communication skills, both written and verbal, with the capability to convey complex technical concepts to diverse audiences and influence executive decision-making. Recognized as a thought leader in the data science community, with a strong portfolio of publications, conference presentations, or significant contributions to the field. Ability to manage and deliver multiple high-stakes projects simultaneously, with a deep understanding of how to align data science initiatives with overarching business objectives and strategies. Our Commitment to a Culture of Inclusion & Belonging Ecolab is committed to fair and equal treatment of associates and applicants and furthering the principles of Equal Opportunity to Employment. We will recruit, hire, promote, transfer and provide opportunities for advancement based on individual qualifications and job performance in all matters affecting employment, compensation, benefits, working conditions, and opportunities for advancement. Ecolab will not discriminate against any associate or applicant for employment because of race, religion, color, creed, national origin,citizenship status, sex, sexual orientation, gender identity and expressions, genetic information, marital status, age, or disability. Show more Show less

Job Overview Were looking for a Lead Data Scientist with a passion for both math and technology to join our growing Advanced Analytics group. This group writes the math and software to unlock the value in data assets while creating new and unique decision product offerings for customers. In this role, you will have the opportunity to work directly with the business innovation teams, marketing, sales and global customers along with expertise from Ecolabs Center for Advanced Analytics, to develop the data strategy and advanced analytics applications pipeline. You will have the opportunity to stay on the cutting edge of technology research and then to put your skills this research to practical use by building advanced data analytics science models your own software systems. You will be able to see the results of your efforts ripple throughout the company our systems in real-time. You will design your systems as you see fit, own your code, and your work will have a very direct, measurable impact on the core metrics of the organization. Whats In It For You The opportunity to take on some of the worlds most meaningful challenges, helping customers achieve clean water, safe food, abundant energy and healthy environments The ability to make an impact and shape your career with a company that is passionate about growth The support of an organization that believes it is vital to include and engage diverse people, perspectives and ideas to achieve our best Actively engage with internal business teams to understand their challenges and deliver robust, data driven solutions. Work alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools. Be encouraged and expected to innovate and be creative in your data analysis, problem solving and presentation of solutions. Network and collaborate with a broad range of internal business units to define and deliver joint solutions. Work alongside customers to leverage cutting edge technology (Generative AI, machine learning, streaming analytics and real big data) to creatively solve problems and disrupt existing business models. Key Responsibilities Lead, manage, and mentor a high-performing team of data scientists, ensuring excellence in technical execution and professional development Define, implement, and refine the AI and ML strategy and roadmap, aligning with the organization&aposs long-term goals and evolving business needs Drive the development and deployment of state-of-the-art AI methodologies, leveraging the latest advancements in machine learning, artificial intelligence, and computational techniques Present complex, data-driven insights and strategic recommendations to stakeholders, driving high-level decision-making Develop and nurture relationships with business partners and stakeholders across the organization, ensuring effective collaboration and alignment on AI-driven projects Ensure the scalability, reliability, and robustness of AI solutions through advanced model development, deployment, and monitoring practices Proactively manage project risks and mitigate potential issues, ensuring successful delivery and alignment with strategic goals Conduct pioneering research in emerging areas, integrating new technologies and methodologies to solve complex business problems Pre-Requisites 10+ years of experience in AI, Data Science or a related field, with a proven track record of leading and executing high-impact, technically complex projects Extensive expertise in advanced machine learning algorithms, deep learning, statistical modeling, and AI, with hands-on experience in cutting-edge techniques Mastery of programming languages such as Python, with extensive experience in advanced machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Keras, LangChain, Transformers, OpenAI SDK, or Hugging Face) Advanced skills in SQL and hands-on experience with big data technologies Deep understanding of LLMs, prompt engineering, and transformer architectures Prior experience leading Generative AI solutions utilizing LLMs such as GPT, Claude, and LLaMA Demonstrated expertise in MLOps practices, including model deployment, monitoring, and optimization at scale Outstanding communication skills, both written and verbal, with the capability to convey complex technical concepts to diverse audiences and influence executive decision-making Ability to manage and deliver multiple high-stakes projects simultaneously, with a deep understanding of how to align data science initiatives with overarching business objectives and strategies (Preferred) Masters degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Marketing Research Our Commitment to a Culture of Inclusion & Belonging Ecolab is committed to fair and equal treatment of associates and applicants and furthering the principles of Equal Opportunity to Employment. We will recruit, hire, promote, transfer and provide opportunities for advancement based on individual qualifications and job performance in all matters affecting employment, compensation, benefits, working conditions, and opportunities for advancement. Ecolab will not discriminate against any associate or applicant for employment because of race, religion, color, creed, national origin,citizenship status, sex, sexual orientation, gender identity and expressions, genetic information, marital status, age, or disability. Show more Show less

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

Core AI is at the forefront of Microsoft's mission to redefine how software is built and experienced. We are responsible for building the foundational platforms, services, programming models, and developer experiences that power the next generation of applications using Generative AI. Our work enables developers and enterprises to harness the full potential of AI to create intelligent, adaptive, and transformative software. The Future of Scalable Software Engineering ( FoSSE ) team's objective is to build capabilities to enable AI-enabled modernization of very large code bases on a large scale and with very high quality. Job Purpose Overview In this role, you will help define the future of software development. Y ou will help build and combine static analysis and ML tools to help AI handle the scale of large code bases. You will work with state-of-the-art LLMs and reasoning models, very large code bases, and use data from pull requests, static analysis warnings reports, and developer feedback from AI recommendations to build AI agents that scale. You will grow by developing both static analysis and ML based techniques that are needed to build coding agents that scale to large code bases. You will be onsite 3 days a week and learn and grow through working with talented colleagues. Standard Company, Culture, Candidate Value Proposition - Use the following: Microsoft's mission is to empower every person and every organization on the planet to achieve more, and we're dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

Business Group Overview Core AI is at the forefront of Microsoft's mission to redefine how software is built and experienced. We are responsible for building the foundational platforms, services, programming models, and developer experiences that power the next generation of applications using Generative AI. Our work enables developers and enterprises to harness the full potential of AI to create intelligent, adaptive, and transformative software. The Future of Scalable Software Engineering ( FoSSE ) team's objective is to build capabilities to enable AI-enabled modernization of very large code bases on a large scale and with very high quality. Job Purpose Overview In this role, you will help define the future of software development. Y ou will help build and combine static analysis and ML tools to help AI handle the scale of large code bases. You will work with state-of-the-art LLMs and reasoning models, very large code bases, and use data from pull requests, static analysis warnings reports, and developer feedback from AI recommendations to build AI agents that scale. You will grow by developing both static analysis and ML based techniques that are needed to build coding agents that scale to large code bases. You will be onsite 3 days a week and learn and grow through working with talented colleagues. Standard Company, Culture, Candidate Value Proposition - Use the following: Microsoft's mission is to empower every person and every organization on the planet to achieve more, and we're dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

Role Overview: As a GenAI Specialist at Birlasoft, you will be completely hands-on with building applications using GenAI models and frameworks. You will serve as the primary technical expert for GenAI technologies, focusing on enhancing the GenAI footprint across clients by developing, implementing, and optimizing advanced AI models and solutions. Your role will involve defining best practices, standards, and templates for AI solutions, conducting workshops, demos, and client presentations on GenAI use cases, and collaborating closely with cross-functional teams to identify, evaluate, and implement use cases across different customers. Additionally, you will evaluate and integrate emerging GenAI technologies to enhance conversational AI capabilities, provide technical leadership and mentorship to teams, and troubleshoot and resolve complex platform integration and functionality issues. Your proactive approach will involve creating blueprints, PoCs, and pilots by independently building quick prototypes and demonstrating them to key decision-makers. Key Responsibilities: - Serve as the primary technical expert for GenAI technologies - Drive innovation and ensure successful integration of AI technologies into IT services for clients - Define best practices, standards, and templates for AI solutions - Conduct workshops, demos, and client presentations on GenAI use cases - Collaborate with cross-functional teams to identify, evaluate, and implement use cases across different customers - Evaluate and integrate emerging GenAI technologies to enhance conversational AI capabilities - Provide technical leadership, mentorship, and guidance to teams - Troubleshoot and resolve complex platform integration and functionality issues Qualifications Required: - 10+ years of total IT experience with at least 3-4 years of hands-on experience with AI/Gen AI technologies (OpenAI, Anthropic, Hugging Face, etc.) - Expertise in NLP, NLU, and NLG technologies - Solid understanding of API integrations, backend systems, and data flows - Programming skills in Python, Node.js, Java, or similar languages for API programming - Familiarity with LLMs (Large Language Models), prompt engineering, fine-tuning, and embeddings - Strong problem-solving skills and solution architecture capabilities - Excellent client-facing communication skills with the ability to translate business needs into technical solutions - Experience working with cloud platforms such as AWS, Azure, and GCP - Ability to manage multiple projects and priorities in a fast-paced environment.,

As a Senior GenAI / Agentic AI Specialist with 6-8 years of overall experience in AI/ML, including at least 2 years of hands-on expertise in Generative AI and agentic AI systems, your role will involve working with advanced AI models, designing agent workflows, and integrating AI systems into enterprise environments with a focus on scalability, security, and responsible AI practices. Key Responsibilities: - Work with Generative AI technologies including LLMs, diAusion models, and enterprise applications. - Develop and optimize agentic workflows, including multi-agent collaboration and orchestration. - Design and implement Generative AI solutions tailored for enterprise use cases. - Integrate AI agents with APIs, databases, and cloud services. - Apply prompt engineering, context management, and memory handling in agent systems. - Ensure Responsible AI practices are implemented and adhered to. - Deploy AI agents into production environments. - Optimize scalability and performance of AI systems. - Implement robust security practices including IAM, AD, ADLDS, roles, and service accounts. Required Skills & Qualifications: - 6-8 years of overall experience in AI/ML, with at least 2 years in Generative and Agentic AI. - Expertise in generative AI models and prompt engineering techniques. - Proficiency in Python/Java-based AI libraries for developing GenAI applications. - Hands-on experience with agentic AI systems including autonomous agents, multi-step reasoning, and tool orchestration. - Experience with frameworks such as LangGraph, LangChain, AutoGen, CrewAI, and Google ADK. - Practical exposure to MCP server implementation and agent-to-agent communication. - Experience designing and implementing retrieval-augmented generation (RAG) pipelines. - Experience building chatbots for platforms like Microsoft Teams or Slack. - Strong understanding and hands-on experience with vector databases. - Knowledge of context engineering. - Experience with reinforcement learning and fine-tuning LLMs. - Proven experience in building and deploying conversational chat applications. - Proficiency in containerization and orchestration using Kubernetes. - Experience working with SQL and NoSQL databases.,

Role Overview: You will be a part of the People & ORG CoE team at the Bain Capability Network (BCN), working on building and deploying analytical solutions related to Operating Model and Organization Practice. Your main responsibility will involve developing, maintaining, and evolving advanced internal tools with a focus on Python. Additionally, you will contribute to case delivery by generating meaningful insights for Bain clients using these tools. You will also play a role in creating efficiency gains and driving innovation within the team. Key Responsibilities: - Become an expert in developing and maintaining advanced internal tools with a focus on Python - Handle end-to-end tool processes, including troubleshooting errors and developing Python scripts - Assist in case delivery and provide valuable insights for Bain clients - Potentially build and maintain internal web applications using front-end technologies and frameworks like Streamlit - Work under the guidance of a Team Manager / Sr. Team Manager to drive innovation and identify areas for automation - Lead internal team calls, communicate data, insights, and actionable next steps on tool development - Stay updated on new statistical, database, machine learning, and advanced analytics techniques Qualifications Required: - Graduation/Post-graduation from a top-tier college with a strong academic background - Minimum of 4 years of relevant experience in Python, experience with GenAI, LLMs, or Machine Learning preferred - Advanced understanding of database design and Azure/AWS servers preferred - Experience in SQL, Git, statistical and machine learning models, and front-end technologies like HTML, CSS, JavaScript - Familiarity with low-code development tools such as Streamlit, Mendix, Power Apps - Experience with data science/analytics tools like Alteryx, Informatica will be a plus - Strong analytical skills with the ability to generate realistic answers and recommend actionable solutions - Excellent oral and written communication skills to interact with technical and non-technical stakeholders - Ability to manage multiple projects, prioritize tasks, and drive projects to completion under tight deadlines (Note: Additional details about the company were not included in the provided job description),

As a Generative AI Architect at NiCE, you will be responsible for providing technical leadership and architectural direction for the development and integration of Generative AI solutions within the organization's product portfolio and platform. Your role will involve collaborating closely with engineering, data science, product, and business stakeholders to ensure effective design, scalability, security, and operationalization of GenAI-powered features and systems. **Key Responsibilities:** - Set the end-to-end technical direction for Generative AI initiatives, including platform, technology stack, tools, and infrastructure. - Architect, design, and oversee the implementation of GenAI models and pipelines for production use cases. - Collaborate with cross-functional teams to define requirements, deliver functional and design specifications, and ensure alignment with business objectives. - Ensure that Generative AI solutions are scalable, secure, reliable, and maintainable, adhering to enterprise standards and best practices. - Lead architectural and design reviews for GenAI features and help establish coding and model development standards. - Evaluate, select, and integrate third-party GenAI platforms, frameworks, APIs, and cloud services as appropriate. - Drive continuous innovation by staying up-to-date with advances in GenAI, ML, and AI infrastructure. - Foster a culture of engineering excellence, mentoring team members on AI/ML, MLOps, and responsible AI practices. - Ensure robust model monitoring, performance evaluation, and feedback loops for deployed GenAI systems. - Collaborate with security and compliance teams to ensure adherence to data governance, privacy, and AI ethics requirements. - Contribute to strategic planning for AI initiatives and the company's long-term technology roadmap. - Mentor teams on the importance of each MCP pillar and drive adoption of best practices throughout the AI development lifecycle. **Qualifications:** - 15+ years of software development or technical leadership experience, with at least 5 years focused on AI/ML solutions and a minimum of 2 years architecting Generative AI systems. - Expertise in designing and deploying production-grade Generative AI solutions, including LLMs, summary generation, prompt engineering, and RAG-based architectures. - Experience with leading AI/ML frameworks and MLOps tools. - Strong understanding of cloud platforms and AI services. - Deep knowledge of machine learning concepts, data engineering, and model operationalization at scale. - Familiarity with responsible AI practices, including data privacy, fairness, explainability, and compliance. - Proficient in programming languages such as Python, Java, or similar; experience with containerization and orchestration. - Experience driving Continuous Integration and Delivery for AI/ML solutions. - Excellent problem-solving, decision-making, and communication skills. - Proven ability to mentor engineers and data scientists, foster teamwork, and drive consensus. - Experience working in Agile development environments. - Strong quality orientation, attention to detail, and ability to translate ideas into robust solutions. - Familiarity with security technologies and best practices for AI-enabled platforms. - Experience with AI/ML testing, monitoring, and continuous model evaluation in production. - Exposure to natural language processing (NLP) and computer vision applications. - Familiarity with MCP framework. - Passion for delivering innovative, high-quality GenAI products and platforms. - Ability to work independently and collaboratively across multi-disciplinary teams. - Demonstrated leadership in adopting new technologies and driving organizational change. - Strong customer orientation and ability to communicate complex technical concepts to non-technical stakeholders. - Commitment to ethical AI and continuous learning. NiCE offers a challenging work environment, competitive compensation, and benefits, and rewarding career opportunities. Join the NiCE team and be part of a fast-growing, highly respected organization where innovation and growth are at the forefront. Enjoy NiCE-FLEX hybrid model, combining office and remote work for maximum flexibility.,

Role Overview: As a Junior ML Engineer, you will be exposed to real-world machine learning systems from day one. You will support model development, testing, and deployment, and also take ownership of core data tasks like ingestion, vectorization, and indexing that form the backbone of the AI search engine. This role is perfect for someone who wants to grow fast, work with state-of-the-art AI tools, and help shape the future of legal research. Key Responsibilities: - Assist in Building and Deploying AI Models - Support senior ML engineers in developing search relevance models using LLMs and RAG. - Help test and evaluate embedding quality, ranking performance, and retrieval accuracy. - Contribute to deploying models into production on Azure. - Learn and Grow in a Production AI Environment - Gain exposure to real-world ML workflows used in legal and enterprise search. - Receive mentorship on best practices in model design, deployment, and optimization. - Participate in code reviews, architecture discussions, and technical deep dives. - Build APIs and Contribute to Integration Work - Help create and maintain REST APIs that expose AI-powered search to frontend apps. - Work alongside full-stack engineers to ensure seamless integration of models. - Manage Data Pipelines for Legal Search - Ingest, preprocess, and structure legal documents for AI consumption. - Chunk and generate embeddings from legal texts using pre-trained models. - Continuously update Azure AI Search indexes by ingesting fresh legal data on a regular basis. Qualification Required: - 2-3 years of experience or strong academic projects in ML/NLP/data science. - Strong programming skills in Python and experience with PyTorch or TensorFlow. - Familiarity with LLMs, vector search including Azure AI Search and RAG workflows. - Exposure to FastAPI, Flask, or Azure ML services. - Experience with data processing libraries (Pandas, NumPy, spaCy, NLTK). Additional Details: This is an on-site position for Lucknow, India. Nice to Have: - Experience working with legal, academic, or enterprise document data. - Interest in AI-powered document search or legal/enterprise NLP applications. - Strong desire to learn and collaborate with senior ML engineers. Notice Period: 1 Month or less,

As a Solution Architect specializing in AI & Automation, your role will involve designing and delivering cutting-edge agentic automation solutions that leverage technologies such as UiPath RPA, AI Agents, LLMs, and Generative AI. Your focus will be on building scalable, secure, and reusable architectures to optimize operations, enhance decision-making, and accelerate digital transformation. Key Responsibilities: - Design end-to-end automation solutions using UiPath RPA, AI Agents, LLMs, and Generative AI. - Define scalable, reusable, and secure solution architectures aligned with business and technology strategies. - Partner with stakeholders to understand business challenges and craft intelligent automation solutions. - Provide technical leadership for integrating automation and AI into existing workflows. - Work with UiPath, AI/ML models, APIs, and cloud platforms (AWS, Azure, Databricks) to build intelligent automation solutions. - Evaluate and recommend emerging AI technologies (LLMs, AI Agents, GenAI) for automation use cases. - Ensure compliance with industry standards, security, and governance requirements. - Lead the development of PoCs to validate automation use cases and measure business value. - Collaborate with AI/ML engineers to refine and enhance automation capabilities. - Stay current with trends in AI, LLMs, and automation to drive innovation. - Work closely with business stakeholders, developers, and AI/ML engineers on solution delivery. - Mentor developers and guide teams on best practices for automation and AI integration. Qualifications Required: - Extensive experience in automation solution design, with strong expertise in UiPath RPA. - Hands-on experience integrating AI (LLMs, AI Agents, GenAI) into automation workflows. - Proven ability in designing agentic automation architectures for process optimization and decision-making. - Deep knowledge of UiPath ecosystem (Orchestrator, AI Center, Action Center, Document Understanding). - Strong expertise in cloud platforms (AWS, Azure, Databricks, or similar). - Proficiency in Python, APIs, and optionally Power Automate for automation integration. - Strong problem-solving skills and ability to translate business needs into scalable technical solutions.,

Unlock the future of intelligent automation with a visionary AI Developer who excels in crafting agentic AI applications that effortlessly connect with structured databases. If you're passionate about pushing technological boundaries, possess deep expertise in LLMs, RAG, and orchestration frameworks, and thrive on transforming complex business needs into scalable, AI-driven solutions, this is your opportunity to make a transformative impact. Key Responsibilities: Design and develop agentic bots powered by Large Language Models (LLMs) to interact with structured databases (SQL, Snowflake, etc.). Integrate AI agents with external tools and data sources using Model Context Protocol (MCP). Implement RAG pipelines using vector databases (e.g., Pinecone, FAISS, Weaviate, ChromaDB) to enable accurate information retrieval. Build and optimize conversational workflows leveraging frameworks such as LangChain, LlamaIndex, or similar orchestration tools. Develop natural language-to-SQL mapping systems that allow users to query structured databases via conversational interfaces. Collaborate with data engineers, data scientists, and business stakeholders to define requirements, integrate datasets, and deliver impactful AI use cases. Deploy, monitor, and optimize AI applications in production using MLOps practices (CI/CD, containerization, model versioning). Ensure AI systems comply with data security, privacy, and governance standards. Stay current with emerging AI/ML tools, frameworks, and best practices, proactively bringing innovation into solutions. Qualifications: Bachelors or Masters in Computer Science, AI/ML, Data Science, or a related field with a minimum of 1+ years in AI/ML development. Strong programming skills in Python with hands-on experience building APIs and backend services. Hands-on experience with Model Context Protocol (MCP) to extend AI agents capabilities with external tools and context. Experience with LLMs and GenAI APIs (OpenAI, Anthropic, Hugging Face, Azure OpenAI), and AI orchestration frameworks (LangChain, LlamaIndex, or equivalent). Experience integrating AI applications with structured databases (Snowflake, Postgres, MySQL) and working with SQL. Familiarity with vector databases and embedding models for semantic search and RAG. Preferred Skills: Knowledge of MLOps practices (CI/CD, Docker, Kubernetes, MLflow). Experience deploying AI apps on AWS (SageMaker, Lambda, S3) or other cloud platforms. Knowledge of Power BI or Tableau for integrating AI outputs into business intelligence dashboards. Prior experience building chatbots, virtual assistants, or intelligent automation solutions.

Were seeking a forward-thinking Gen AI Engineer to design, implement, and optimize cutting-edge agentic AI solutions using frameworks such as Crew.ai , LangChain , and LangGraph . You will work at the intersection of LLMs , Retrieval-Augmented Generation (RAG) systems, and NLP , enabling impactful AI applications across diverse domains. Key Responsibilities Design and deploy autonomous AI agents and multi-agent systems using LLMs such as GPT-4o, Claude, and LLaMA, leveraging Crew.ai, LangChain (and LangGraph). Own the AI solution lifecycle , including data acquisition, model experimentation, fine-tuning, deployment, and production monitoring. Develop scalable AI backends and pipelines using Python with frameworks like PyTorch or TensorFlow, deploying via REST APIs (FastAPI) on cloud platforms like AWS or Azure. Implement RAG-based systems by integrating open-source LLMs (via Hugging Face or Ollama) with vector databases (e.g., Pinecone, ChromaDB) and structured data stores (SQL/NoSQL). Collaborate with cross-functional teams to ensure reliable, maintainable, and impactful AI solutions. Required Skills & Experience 2 to 5 years of experience in AI/ML, NLP, Generative AI, with a focus on agentic AI systems . Strong proficiency in Python and hands-on experience building RAG systems and deploying open-source LLMs. Experience developing AI-driven backends and services with a strong understanding of scalability and performance. Familiarity with vector search technologies, database integration, and cloud-native architectures. Excellent communication and collaboration skills; ability to work effectively in a team environment. Education B.Tech/B.E. or M.Tech/M.E. in Computer Science, AI/ML, or a related field. Role: Gen AI Engineer Designation: AI Developer Experience: 2-5 Years (AI/ML, NLP, Generative AI): Location: Pune

Why this role exists Were scaling our AI product suite - invoice & contract and terms extraction, anomaly and overpayment detection, and analyst workflows for both internal and client users. We need a product leader who can turn ambiguous customer pain into shipped, secure, and measurable AI features that enterprise customers love and finance leaders trust. What youll own Strategy & Outcomes Define and own the AI product strategy and measurable outcomes for recovery, accuracy, and time-to-value across enterprise accounts. Translate market and customer signals (Procurement, AP, Audit, Infosec, Legal) into a prioritized roadmap with clear trade-offs. Product Discovery Run deep discovery with Fortune 1000 stakeholders and Discover Dollar analysts to map jobs-to-be-done, decision points, and data realities (SAP/Oracle/Coupa/Ariba exports, data lake, data warehouse extracts, contracts, invoices, emails, credit notes). Validate problems and solutions with prototypes (AI tools like Lovable, Replit, Figma, Low-code tools etc) and pilot metrics before committing engineering. Product Delivery Lead cross-functional squads (ML/DS, Backend, Frontend, Design, Data Platform, Security) to ship high-quality increments on a predictable cadence. Write crisp PRDs, acceptance criteria, and instrument the product for analytics/telemetry (events, funnels, precision/recall dashboards). Drive integrations and partner workflows (e.g., SAP S/4HANA, Oracle, Coupa/Ariba, RMS) with clear APIs and data contracts. AI/ML Product Craft Shape AI features such as document extraction (OCR + NLP), contract terms understanding, Complex Agentic AI workflows, LLM/RAG assistants for analysts, anomaly/risk scoring, and human-in-the-loop review. Partner with DS/ML on evaluation frameworks (offline/online), data labeling strategy, prompt & model versioning, and cost/performance tuning (latency, tokens, GPU/CPU budgets). Establish monitoring/guardrails: drift, bias, hallucination containment, red-teaming, feedback loops. Governance, Privacy & Security Embed privacy-by-design and enterprise controls (role-based access, audit logs, retention, encryption). Coordinate with customers InfoSec/Legal on DPAs, SOC 2/ISO 27001 alignment, data residency, and model risk documentation (model cards, DPIAs where needed). Customer & GTM Own product pilots, success criteria, and value realization (business cases, ROI). Enable Sales/CS with narratives, demos, pricing/packaging inputs, and win/loss insights. Collect structured feedback and convert it into backlog and experiments. What success looks like 30 days: Understand domain and data flows; publish product health baseline; ship a small improvement (e.g., analyst UX, cost reduction). 60 days: Deliver a validated AI feature MVP (e.g., improved clause extraction or anomaly ranking) to a pilot customer with a signed success plan. 90 days: Hit agreed accuracy + adoption targets; publish a 2-quarter roadmap tied to revenue and recovery dollars; formalize AI evaluation & monitoring dashboards. Key KPIs/metrics youll move Business impact: Verified recovery dollars, time-to-detect, time-to-close. Model quality: Precision/recall/F1 by use case; false positive rate; drift indicators. Efficiency: Cost per decision (tokens/compute), latency, analyst throughput. Adoption: Active users, task completion rate, retention, NPS/CSAT. Reliability & risk: Incident rate, hallucination guardrail triggers, SLA/SLO adherence. Must-have qualifications 5+ years in product management with at least 1 year of shipping AI/ML-powered features in production (LLMs/RAG/NLP/vision/ML detection). Track record in B2B enterprise SaaS with complex data and security needs; comfortable working with Procurement/AP/Finance stakeholders. Strong discovery and storytelling skills: can turn messy datasets and ops realities into a clear product narrative and roadmap. Technical depth to partner with DS/ML/Engineering understands evaluation metrics, A/B testing, data pipelines, API design, and basics of SQL/Python. Analytics-first: habit of instrumenting funnels, defining guardrails, and making decisions from dashboards and user studies. Excellent written communication (PRDs, RFCs, customer docs) and stakeholder management across Sales, CS, Legal, and Infosec. Bachelors in Engineering/CS/Math/Statistics or equivalent experience. Nice-to-have Domain exposure to Source-to-Pay, AP automation, recovery audit, contract analytics, or financial controls. Experience with SAP/Oracle/Workday/Coupa/Ariba data models and enterprise integrations. Familiarity with MLOps (MLflow/W&B), vector databases (FAISS/Pinecone), and eval frameworks for LLMs. Understanding of model risk management, secure AI patterns, and enterprise compliance expectations. Prior startup or zero-to-one product experience. Our current tech context (helpful, not required) AI Stack: LLMs (commercial & open-source Open AI, Llama, Claude), RAG pipelines, OCR + NLP for documents, Data stack: cloud object storage, relational DBs, event pipelines, analytics stack like Databricks, Elastic Search, Cloud Stack: Primarily Azure but build cloud agnostic product to make it deployable in AWS, GCP etc. Dev Stack: Python, Javascript, React Product tooling: Clickup (Jira equivalent), Postman, Figma How we work Bangalore-based hybrid team with collaboration across India and North America Pragmatic agile: weekly planning, monthly business reviews, quarterly product reviews tied to revenue and recovery outcomes. What youll get to do Ship AI that recovers real money for global enterprises. (Already saved over $1B+ with current product, need to 10X the impact) Build analyst-in-the-loop systems that blend human judgment with AI scale. Influence pricing/packaging and help define the category for AI-assisted recovery audit. Compensation & benefits Competitive with Bangalore market for Product Manager talent, plus benefits and performance incentives. (Well share details during the first call.)

Company: Technodysis Pvt Ltd Location: Bangalore Experience: 6 - 8 Years Notice Period: Immediate Joiners Preferred Job Description: We are seeking a Technical Lead AI Development to lead AI solution design and implementation. This role requires technical leadership in architecting LLM-based AI workflows and mentoring developers. Key Responsibilities: Lead a team/module in building AI-driven applications Architect solutions using LLMs and agentic frameworks Provide guidance on AI model design, prompt engineering, and fine-tuning Integrate APIs, tools, and external systems with AI agents Ensure high-quality coding standards, version control, and CI/CD practices Collaborate with cross-functional teams for solution delivery Mentor developers and promote innovation in AI/ML practices Required Skills & Qualifications: Bachelors/Masters degree in Computer Science, AI, or related field 5 - 8 years in AI/ML development with 12 years in a lead role Strong programming expertise in Python, TensorFlow, PyTorch Proven experience with LLMs, prompt engineering, and fine-tuning Proficiency in frameworks like LangChain, AutoGen, CrewAI Knowledge of vector databases and knowledge graph-based systems Strong leadership, communication, and mentoring skills If interested for this role then please share your updated resume along with CTC Details to chanchal.kumar@technodysis.com

• Proficiency with Python (Pandas, NumPy), SQL, and Java. • Experience with LLMs, Lang Chain, and Generative AI technologies. • Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka). • Microservices, CI CD, ML Required Candidate profile • Machine Learning, NLP, Recommender system, personalization, Segmentation, microservice architecture & API development • Data engineering concepts like data lakes, columnar formats, ETL & BI tools

Responsibilities: *Design, develop & deploy AI/ML models using Python,deep learning & Agentic AI *Optimize model performance with Vector Databases & Docker/Kubernetes. Python, LLMs, PyTorch/TensorFlow, Hugging Face, NLP, Cloud,Model Deployment

As a candidate for this role, your main responsibilities will include: - Establishing and scaling the Advisory service Practice, driving strategic initiatives and solution offerings across verticals - Defining the practice roadmap, managing budgets, and contributing to P&L growth - Collaborating with sales and presales teams to develop go-to-market strategies and participate in key client pursuits - Driving innovation by integrating new-age technologies such as AI/ML, LLMs, and Generative AI into advisory delivery - Building frameworks, accelerators, and reusable assets to improve scalability and delivery maturity - Representing the Organization at external industry forums, client events, and webinars to strengthen market visibility To be successful in this role, you should have: - 20+ years of experience in IT, with significant exposure to Advisory/Professional services, including presales and practice leadership - Demonstrated success in building analytics practice from the ground up and scaling them across geographies - Exposure to solutioning, RFP support, and client presentations - Ability to balance strategic thinking with hands-on execution - Strong stakeholder and client management experience across global delivery models,

As a Transformation Lead at Capgemini Invent, you will play a key role in driving the organization's journey towards intelligent, scalable, and AI-augmented systems. Your responsibilities will include: - Designing and building secure, scalable applications using Azure services like App Services, Functions, and Azure DevOps. - Implementing GenAI solutions using frameworks such as LangChain, LangGraph, Autogen, crewAI, or OpenAI Agent SDK to orchestrate multi-step reasoning and agent workflows. - Delivering AI-powered solutions for production use cases such as intelligent document processing, automated content generation, enterprise search assistants, and decision-support systems, employing techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and model fine-tuning. Qualifications required for this role include: - Education: Bachelors or Masters degree in Computer Science, Engineering, or a related field. - Strong experience in Azure cloud services and infrastructure. - Practical understanding of GenAI frameworks such as LangChain, LangGraph, Autogen, crewAI, OpenAI Agent SDK. - Proficiency in Python for AI/ML development. - Experience working with LLMs and GenAI techniques such as prompt engineering and RAG. - Background in building microservices and serverless solutions. Joining Capgemini Invent will provide you with the opportunity to work in a flexible environment that supports remote work and offers flexible work hours, enabling you to maintain a healthy work-life balance. Additionally, you will benefit from career growth programs, diverse professions, and valuable certifications in the latest technologies such as Generative AI. Capgemini is a global business and technology transformation partner with a strong heritage of over 55 years. They are trusted by clients to unlock the value of technology by addressing a wide range of business needs. With a team of 340,000 members in more than 50 countries, Capgemini is committed to accelerating the dual transition to a digital and sustainable world, creating tangible impact for enterprises and society.,

As an experienced consulting professional in the field of Data Science or AI/ML Engineering, you will be responsible for understanding solutions, industry best practices, and implementing Oracle products and technology to meet customer needs. You will operate independently to deliver high-quality work products to engagements, applying Oracle methodology, company procedures, and leading practices. **Key Responsibilities:** - Lead end-to-end AI/ML solution design and production deployment - Specialize in Generative AI, LLMs, NLP, and AI agent development - Expertise in Python and modern ML/NLP frameworks such as HuggingFace, LangChain, PyTorch, TensorFlow - Fine-tune LLMs for domain-specific applications like Q&A systems, auto-documentation, and predictive insights - Build, scale, and optimize AI systems on OCI with knowledge of hybrid/multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, vector databases, and RAG pipelines - Familiarity with MLOps, model governance, and CI/CD for ML workflows - Excellent communication and stakeholder management skills to bridge the gap between technical and executive teams **Qualifications & Experience:** - 12-15 years of total experience, with a minimum of 5 years in Data Science or AI/ML Engineering roles - Proven track record in AI/ML solution design and deployment - Expertise in Python and modern ML/NLP frameworks - Hands-on experience with AI systems on OCI and knowledge of multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, and model governance - Experience in stakeholder engagement, program oversight, and solution design **Additional Details:** The company is committed to an inclusive culture that celebrates diverse insights and perspectives, fostering an environment that inspires thought leadership and innovation. Oracle offers a competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability, including Medical, Life Insurance, Retirement Planning, and more. The company encourages employees to engage in giving back to communities and values diversity and inclusion in the workforce. If you are looking for a challenging role where you can leverage your expertise in AI/ML engineering to drive innovative solutions and work in a diverse and inclusive environment, this position at Oracle might be the perfect fit for you.,

As a forward-thinking and AI-native VP of Product Management at Zycus, you will have the opportunity to lead the next frontier of innovation in Agentic AI and autonomous enterprise software. Your role will involve transforming Zycus" suite of procurement and supply chain solutions into next-gen, AI-driven products with built-in intelligence, automation, and adaptability. You will be empowered with complete ownership, from vision and design to launch and market success. **Key Responsibilities:** - Lead the vision, strategy, and execution of AI-first enterprise products, especially those leveraging Agentic AI, LLMs, intelligent agents, and advanced automation. - Drive product innovation that enables autonomous decision-making and enhances user experience via adaptive workflows and contextual intelligence. - Partner with engineering, AI/ML teams, and data science to shape product architectures that are scalable, secure, and continuously learning. - Define AI use cases across sourcing, procurement, supplier management, and compliance, translating business pain points into high-impact product features. - Guide end-to-end product development from discovery and rapid prototyping to deployment and post-launch iteration. - Develop a deep understanding of customer workflows and infuse AI capabilities to drive measurable business outcomes. - Champion a user-first mindset with experimentation, A/B testing, and behavioral analytics. - Work closely with GTM, sales, and marketing to define compelling product narratives and positioning. - Stay ahead of market trends, research advancements in GenAI and agentic systems, and bring those insights into the product roadmap. **Qualifications Required:** - Ability to handle ambiguity and change - Very strong logical thinking capabilities and analytical skills - Visualize and conceptualize new ideas and solutions - UI designing & prototyping (use of wireframing tools) - Research and analysis (both primary and secondary research) - Customer management and excellent communication & presentation skills - Art of negotiation and prioritization - Ability to manage teams and build close relationships with different team members - Visionary **Desired Experience:** - Education: BE is a must + full-time MBA from a Tier 1 B-School (IIMs, ISB, XLRI, SPJIMR, FMS, MDI, etc.). - 13+ years in product management, with recent experience building AI-native SaaS or enterprise software products. - Proven ability to conceptualize, build, and scale AI products or intelligent platforms. - Experience working with GenAI, LLMs (like GPT, Claude), intelligent agents, or autonomous product workflows. - Strong design thinking capabilities and ability to rapidly prototype innovative solutions. - Deep analytical mindset with strong intuition for user behavior, product adoption, and growth loops. - Outstanding stakeholder management, executive presence, and cross-functional leadership. - Bias for action, clarity of thought, and the ability to operate in fast-paced, ambiguous environments. **Why Should You Join Us ** - Cloud Product Company: Zycus is a Cloud SaaS Company that utilizes the latest technologies like ML and AI in product development. - Market Leader: Recognized by Gartner as a Leader in Procurement Software Suites. - Career Growth: Opportunity to shift roles and functions within the organization. - Global Exposure: Work and deal with global customers. - Impact Creation: Environment to create an impact on the product and transform ideas into reality. In summary, as a VP of Product Management at Zycus, you will lead the innovation in AI-driven products, work closely with cross-functional teams, and have the opportunity to make a real impact on the product and organization.,

As a Junior AI Engineer, you will be part of a fast-moving team working on developing and integrating LLMs and Generative AI tools into real-world applications. You will contribute to model experimentation, fine-tuning, prompt engineering, and data preparation while growing your understanding of how these technologies power modern software systems. Key Responsibilities: - Work with LLMs (e.g., OpenAI, Hugging Face Transformers) to develop, fine-tune, and integrate models into products. - Design and test prompts for various tasks (prompt engineering) to improve model outputs. - Support development and deployment of generative AI applications (text, code, or image generation). - Write Python code to build ML/AI pipelines, evaluate model performance, and preprocess data. - Collaborate with data engineers to prepare and manage datasets used for training and evaluation. - Monitor and test model performance in production environments. - Document technical work, including models, experiments, and results. Required Qualifications: - Bachelors degree in Computer Science, Engineering, Data Science, or a related field. - 01 year of industry experience in AI/ML, or a strong academic or project portfolio. - Proficient in Python and libraries such as pandas, NumPy, scikit-learn, and matplotlib. - Basic understanding of machine learning workflows and model evaluation. - Exposure to LLMs (e.g., GPT, LLaMA, Mistral) through personal or academic projects. - Familiarity with Hugging Face Transformers or OpenAI API is a plus. - Basic understanding of data engineering concepts such as ETL, data cleaning, and pipeline orchestration.,