65 Huggingface Jobs - Page 2

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

The Team : As a member of the Data Transformation - Cognitive Engineering team you will work on building and deploying ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients. You will spearhead deployment of AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Lead a highly skilled and technically strong team (including leadership) Contribute to solving high complexity, high impact problems Build production ready pipelines from ideation to deployment Responsibilities: Design, Develop and Deploy ML powered products and pipelines Mentor a team of Senior and Junior data scientists ML Engineers in delivering large scale projects Play a central role in all stages of the AI product development life cycle, including: Designing Machine Learning systems and model scaling strategies Research & Implement ML and Deep learning algorithms for production Run necessary ML tests and benchmarks for model validation Fine-tune, retrain and scale existing model deployments Extend existing ML librarys and write packages for reproducing components Partner with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements Interpret results and present them to business leaders Manage production pipelines for enterprise scale projects Perform code reviews & optimization for your projects and team Lead and mentor by example, including project scrums Technical Requirements: Proven track record as a senior lead ML engineer Expert proficiency in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.) Excellent exposure to large scale model deployment strategies and tools Excellent knowledge of ML & Deep Learning domain Solid exposure to Information Retrieval, Web scraping and Data Extraction at scale Exposure to the following technologies - R-Shiny/Dash/Streamlit, SQL, Docker, Airflow, Redis, Celery, Flask/Django/FastAPI, PySpark, Scrapy Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures Open to learning new technologies and programming languages as required A Masters PhD from a recognized institute in a relevant specialization Good to have: 6-7+ years of relevant experience in ML Engineering Prior substantial experience from the Economics/Financial industry Prior work to show on Github, Kaggle, StackOverflow etc.

About the Role: Grade Level (for internal use): 09 The Team: As a member of the Data Transformation team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative. The Impact: The Data Transformation team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Key Responsibilities Design, Develop and Deploy ML powered products and pipelines Play a central role in all stages of the data science project life cycle, including: Identification of suitable data science project opportunities Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements Evaluation/interpretation of results and presentation to business leaders Performing exploratory data analysis, proof-of-concept modelling, model benchmarking and setup model validation experiments Training large models both for experimentation and production Develop production ready pipelines for enterprise scale projects Perform code reviews & optimization for your projects and team Spearhead deployment and model scaling strategies Stakeholder management and representing the team in front of our leadership Leading and mentoring by example including project scrums What Were Looking For: 2+ years of professional experience in Data Science domain Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.) Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures Expertise in probabilistic machine learning model for classification, regression & clustering Strong experience in feature engineering, data preprocessing, and building machine learning models for large datasets. Exposure to Information Retrieval, Web scraping and Data Extraction at scale OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Problem-solving and debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Prior work to show on Github, Kaggle, StackOverflow etc. Cloud expertise (AWS and GCP preferably) Expertise in deploying machine learning models in cloud environments Familiarity in working with LLMs

About the Role: Grade Level (for internal use): 11 The Team As a member of the Data Transformation team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative. The Impact The Data Transformation team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. What’s in it for you Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Key Responsibilities Design, Develop and Deploy ML powered products and pipelines Play a central role in all stages of the data science project life cycle, including: Identification of suitable data science project opportunities Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements Evaluation/interpretation of results and presentation to business leaders Performing exploratory data analysis, proof-of-concept modelling, model benchmarking and setup model validation experiments Training large models both for experimentation and production Develop production ready pipelines for enterprise scale projects Perform code reviews & optimization for your projects and team Spearhead deployment and model scaling strategies Stakeholder management and representing the team in front of our leadership Leading and mentoring by example including project scrums What We’re Looking For 7+ years of professional experience in Data Science domain Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.) Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures Expertise in probabilistic machine learning model for classification, regression & clustering Strong experience in feature engineering, data preprocessing, and building machine learning models for large datasets. Exposure to Information Retrieval, Web scraping and Data Extraction at scale OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Problem-solving and debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Prior work to show on Github, Kaggle, StackOverflow etc. Cloud expertise (AWS and GCP preferably) Expertise in deploying machine learning models in cloud environments Familiarity in working with LLMs What’s In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Were more than 35,000 strong worldwide—so were able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the worlds leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Flexible DowntimeGenerous time off helps keep you energized for your time on. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIt’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email toEEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning)

About the Role: Grade Level (for internal use): 10 The Team As a member of the Data Transformation team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative. The Impact The Data Transformation team has already delivered breakthrough products and significant business value over the last 3 years. In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems. What’s in it for you Be a part of a global company and build solutions at enterprise scale Collaborate with a highly skilled and technically strong team Contribute to solving high complexity, high impact problems Key Responsibilities Design, Develop and Deploy ML powered products and pipelines Play a central role in all stages of the data science project life cycle, including: Identification of suitable data science project opportunities Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements Evaluation/interpretation of results and presentation to business leaders Performing exploratory data analysis, proof-of-concept modelling, model benchmarking and setup model validation experiments Training large models both for experimentation and production Develop production ready pipelines for enterprise scale projects Perform code reviews & optimization for your projects and team Spearhead deployment and model scaling strategies Stakeholder management and representing the team in front of our leadership Leading and mentoring by example including project scrums What We’re Looking For 3+ years of professional experience in Data Science domain Expertise in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.) Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures Expertise in probabilistic machine learning model for classification, regression & clustering Strong experience in feature engineering, data preprocessing, and building machine learning models for large datasets. Exposure to Information Retrieval, Web scraping and Data Extraction at scale OOP Design patterns, Test-Driven Development and Enterprise System design SQL (any variant, bonus if this is a big data variant) Linux OS (e.g. bash toolset and other utilities) Version control system experience with Git, GitHub, or Azure DevOps. Problem-solving and debugging skills Software craftsmanship, adherence to Agile principles and taking pride in writing good code Techniques to communicate change to non-technical people Nice to have Prior work to show on Github, Kaggle, StackOverflow etc. Cloud expertise (AWS and GCP preferably) Expertise in deploying machine learning models in cloud environments Familiarity in working with LLMs What’s In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Were more than 35,000 strong worldwide—so were able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the worlds leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Flexible DowntimeGenerous time off helps keep you energized for your time on. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIt’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email toEEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.1 - Middle Professional Tier I (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning)

This role is for one of Weekday's clients Salary range: Rs 1200000 - Rs 1500000 (ie INR 12-15 LPA) Min Experience: 4 years Location: Bengaluru JobType: full-time About the Role We're looking for a highly skilled and motivated AI Engineer to join our growing team of machine learning practitioners, data scientists, and engineers. This role is ideal for someone passionate about building cutting-edge AI solutions using modern deep learning and NLP frameworks. You will work on a wide range of problemsfrom training and fine-tuning large language models to deploying intelligent systems at scalewhile collaborating across product, data, and engineering teams. As an AI Engineer, you will be at the core of our AI initiatives, applying your knowledge in Python, PyTorch, TensorFlow, Scikit-Learn, and other key libraries to build, optimize, and deploy high-performing models. You will also be instrumental in adopting MLOps best practices to ensure that our models are scalable, maintainable, and reproducible. Key Responsibilities Design, develop, and deploy machine learning and deep learning models for real-world AI applications with a focus on natural language processing (NLP) . Leverage libraries like PyTorch , TensorFlow , and Scikit-learn to build and train custom ML/DL models. Use Hugging Face Transformers , spaCy , and other NLP libraries to fine-tune and integrate state-of-the-art models for tasks like classification, summarization, entity recognition, and question answering. Implement MLOps practices such as experiment tracking, model versioning, CI/CD pipelines, and automated deployment. Collaborate with data engineers and analysts to preprocess and clean large datasets using Pandas and NumPy . Build and maintain reusable code and model components to streamline development and promote best practices. Evaluate model performance using rigorous metrics and troubleshoot issues related to bias, overfitting, or latency. Stay updated with the latest research, tools, and trends in AI, especially in the rapidly evolving NLP domain. Work cross-functionally with product, engineering, and business teams to define AI use cases and deliver high-impact solutions. Required Skills & Qualifications 4+ years of hands-on experience as an AI/ML Engineer or similar role. Strong programming skills in Python , with deep understanding of data structures , algorithms , and OOP principles. Expertise in PyTorch and/or TensorFlow for building and deploying deep learning models. Proficiency with Scikit-Learn , Pandas , NumPy , and other core Python libraries used in ML pipelines. Solid understanding and practical experience in natural language processing (NLP) using tools such as HuggingFace , spaCy , or similar. Familiarity with MLOps workflows , including model deployment, version control, and monitoring. Experience working with cloud environments or containerization tools is a plus (e.g., Docker, Kubernetes, AWS, GCP). Strong problem-solving, analytical, and communication skills. Preferred Qualifications Master's or Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field. Experience working on production-level NLP applications. Contributions to open-source ML libraries or participation in ML research.

Were Hiring | AI Data Analyst (8+ Years, Tech Lead Level) Location: Mahape, Navi Mumbai (Hybrid Work from Office) Joining: Immediate Joiners Preferred Role Overview We are looking for an experienced AI Data Analyst with 8+ years of professional experience, including leadership in tech projects. The ideal candidate should have strong expertise in Python , Machine Learning , AI APIs , and Large Language Models (LLMs) . Youll work on cutting-edge AI solutions, including vector-based search and data-driven business insights. Experience Must Include 2+ year of hands-on experience as a Data Analyst 1+ year of practical experience with AI systems (LLMs, AI APIs, or vector-based search) 2+ years of experience working with Machine Learning models/solutions 5+ years of hands-on Python programming Exposure to vector databases (e.g., pgvector, ChromaDB) is a plus Key Responsibilities Perform data exploration, profiling, and cleaning of large datasets Design, build, and evaluate ML and AI models to solve real-world problems Leverage LLM APIs, foundation models, and vector databases to deliver AI-driven insights Build end-to-end ML pipelines from preprocessing to deployment Create dashboards and visualizations for reporting and analysis Analyze model outputs and provide actionable insights to stakeholders Collaborate with engineering, product, and business teams to scale AI solutions Required Technical Skills Data Analysis Experience with real-world datasets, EDA, and data wrangling Visualization using Pandas, Seaborn, Plotly Machine Learning & AI Practical experience in classification, regression, clustering techniques Experience with Generative AI, LLMs, OpenAI/Hugging Face APIs, vector search Knowledge of RAG architecture and modern AI design patterns Skilled in model evaluation and hyperparameter tuning Programming & Tools Proficiency in Python (5+ years), with strong use of scikit-learn, NumPy, Pandas Expertise in SQL/PostgreSQL Hands-on experience with vector databases like pgvector, ChromaDB Familiarity with LLMs, embeddings, and foundation models Exposure to cloud platforms (AWS/SageMaker), Git, REST APIs, and Linux Nice to Have Experience with Scrapy, SpaCy, or OpenCV Knowledge of MLOps, model deployment, CI/CD pipelines Familiarity with PyTorch or TensorFlow Soft Skills Strong analytical thinking and problem-solving abilities Excellent verbal and written communication Self-motivated, proactive, and a great team player To Apply: Send your resume to [Insert Email] or apply via kajal.uklekar@arrkgroup.com Lets shape the future of AI together! Thanks & Regards, Kajal Uklekar Arrk Group Senior Manager-Talent Acquisition www.arrkgroup.com

Key Responsibilities: Lead the end-to-end design, architecture, and delivery of complex AI/ML solutions, including scalable data pipelines, advanced model development, training, deployment, and post-deployment support. Strategically develop and implement machine learning models across diverse domains such as natural language processing (NLP), computer vision, recommendation systems, classification, and regression. Drive innovation by integrating and fine-tuning Large Language Models (LLMs) like GPT, BERT, LLaMA, and similar state-of-the-art transformer architectures into enterprise-grade applications. Own the selection and implementation of appropriate ML frameworks, tools, and cloud technologies aligned with business goals and technical requirements. Spearhead AI/ML experimentation, Proof-of-Concepts (PoCs), benchmarking, and model optimization initiatives. Collaborate cross-functionally with data engineering, software development, and product teams to seamlessly integrate ML capabilities into production systems. Establish and enforce robust MLOps pipelines covering CI/CD for ML, model versioning, reproducibility, and monitoring to ensure reliability at scale. Stay at the forefront of AI advancements, particularly in generative AI and LLM ecosystems, and champion their adoption across business use cases. Required Qualifications: Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field. Hands on experience in the AI/ML domain, with a proven track record of delivering production-grade ML systems. Expertise in machine learning algorithms, deep learning architectures, and advanced neural network design. Demonstrated hands-on experience with LLMs, transformer-based models, prompt engineering, and embeddings. Proficiency with ML frameworks and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, LangChain, etc. Strong programming skills in Python and familiarity with cloud platforms (AWS, Azure, or GCP) for scalable ML workloads. Solid experience with MLOps tools and practices — including MLflow, Kubeflow, SageMaker, or equivalent. Excellent leadership, analytical thinking, and communication skills. Preferred Qualifications: Experience with vector databases . Exposure to real-time AI systems, edge AI, and streaming data environments. Active contributions to open-source projects, research publications, or thought leadership in AI/ML. Certification in AI/ML is big plus. Interested candidates can apply directly or share their resume at shubhra_bhugra@softprodigy.com

We are looking for an experienced AI Developer or aspiring CTO who is ready to take up a co-founder-level role and lead the entire AI development.This is not just another jobit’s an opportunity to build a game-changing product from the ground up , shape the company’s future, and be rewarded with long-term equity and profits. Responsibilities Take end-to-end ownership of AI product development (design, architecture, implementation, optimization). Build and deploy AI/ML/NLP models for intelligent data extraction, analysis, personalization, and automation. Integrate third-party APIs (e.g., ChatGPT API, Make.com, Apify, Hunter, Apollo, etc.). Work closely with frontend/backend teams to build seamless user experiences. Continuously monitor, evaluate, and optimize AI solutions. Contribute to product strategy and roadmap as part of the core leadership team. Create scalable, secure, and modular systems for AI agents, market research tools, and CRM components. Must-Have Qualities Strong experience in AI/ML/NLP (e.g., OpenAI, LangChain, vector databases, RAG pipelines). Proven expertise in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch). Experience with APIs, automation workflows, no-code/low-code integrations, and AI infrastructure. Startup mindset: proactive, resourceful, and comfortable working with ambiguity. Entrepreneurial drive with a hunger to build and scale. Ability to independently manage projects, deadlines, and product cycles. Preferred Qualities Experience building AI products from scratch (especially SaaS platforms). Familiarity with marketing tech, web scraping, data enrichment tools. Prior startup or product-building experience (bonus if you’ve been a founder/CTO). Understanding of business and user-driven product development. What’s in It for You? Profit-Sharing : A percentage of profits plus salary as a founding team member. ESOPs : Earn equity based on performance, commitment, and milestones. Founder's Track : You’re not just an employee—you grow with the company as a leader. Ownership & Autonomy : You’ll define the AI roadmap and lead technical vision. Impact & Innovation : Directly influence how hundreds of businesses use AI to grow.

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

GenAI, NLP, or LLM based systems , strong Python development skills and working LangChain, LlamaIndex, Hugging Face Transformers, or similar GenAI libraries Deep understanding of vector databases and embedding techniques

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).

About the Role: We are seeking a highly skilled and experienced Senior GenAI Developer with a strong foundation in AI-powered search algorithms to join our innovative team. In this role, you will play a crucial part in developing and deploying cutting-edge search solutions that leverage the power of Generative AI to deliver exceptional user experiences. Responsibilities: Design, develop, and deploy advanced search algorithms that utilize GenAI techniques, such as: Semantic Search: Develop and implement algorithms that understand user intent and retrieve relevant information based on meaning and context. Personalized Search: Create search experiences tailored to individual user preferences and search history. Conversational Search: Develop AI-powered search interfaces that enable users to interact with search engines using natural language. Multilingual Search: Develop search solutions that effectively handle queries and retrieve results across multiple languages. Research and implement state-of-the-art GenAI models, including LLMs, for search enhancement. Collaborate with data scientists, engineers, and product managers to define search requirements and evaluate search performance. Develop and maintain robust and scalable search infrastructure. Conduct A/B testing and analyze search results to continuously improve search quality and user experience. Mentor junior developers and provide technical guidance on search-related projects. Stay abreast of the latest advancements in search technology, AI/ML, and natural language processing. Qualifications: Education: Master's or Ph.D. in Computer Science, Information Retrieval, or a related field. Experience: 5+ years of hands-on experience in developing and deploying search algorithms in a professional setting, with a strong focus on AI/ML-powered search. Technical Skills: Expert proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Hugging Face Transformers). Strong understanding of information retrieval principles, indexing techniques, and ranking algorithms. Experience with NLP techniques such as text processing, sentiment analysis, and topic modeling. Experience with MLOps practices, including model training, deployment, monitoring, and maintenance. Proficiency with cloud platforms (AWS, Azure, GCP) and their search services. Other Skills: Excellent problem-solving, analytical, and communication skills. Strong leadership, mentorship, and team collaboration skills. Proven ability to work independently and as part of a high-performing team. Passion for innovation and a strong desire to contribute to cutting-edge search technology. Bonus Points: Experience with open-source search engines (e.g., Elasticsearch, Solr). Experience with building and deploying real-time search applications. Publications in top-tier search or AI/ML conferences or journals.

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

Job Title: Senior AI Engineer Location: Bangalore (Hybrid) Experience: 4+ years Employment Type : Full-time Preferred : Immediate - within 15 days joiners only Company Overview : Join KrtrimaIQ Cognitive Solutions, a leading AI/ML company enabling intelligent enterprises through advanced technologies like machine learning, NLP, computer vision, and automation. Be part of a dynamic team transforming data into powerful business decisions. Key Responsibilities : - Design, develop, and deploy AI/ML models using Large Language Models (LLMs) and Multimodal LLMs. - Work on building and optimizing Retrieval-Augmented Generation (RAG) pipelines for real-world use cases. - Implement and fine-tune transformer models using Hugging Face and PyTorch. - Conduct experiments, benchmark models, and continuously improve performance and scalability. - Collaborate with data engineers and product teams to integrate AI models into production environments. - Stay updated with the latest advancements in generative AI, LLM architectures, and open-source frameworks. Required Skills : - Strong hands-on experience with LLMs (GPT, LLaMA, Mistral, etc.) and Multimodal models (e.g., CLIP, Flamingo). - Expertise in PyTorch and Hugging Face Transformers. - Proficiency in building RAG-based solutions, integrating vector databases like FAISS, Pinecone, or Weaviate. - Solid understanding of deep learning concepts, NLP, and model evaluation techniques. - Experience in deploying and scaling AI models in production environments. - Good programming skills in Python and familiarity with APIs and ML Ops tools. Preferred Qualifications : - Master's or Bachelor's degree in Computer Science, AI, Data Science, or related fields. - Experience with distributed computing and cloud platforms (AWS/GCP/Azure). - Contributions to open-source projects or research papers in the AI/ML domain. Why Join Us ? - Cutting-edge AI/ML projects - Flexible hybrid work culture - Competitive compensation and benefits - Opportunity to grow in a rapidly scaling AI company

As a Generative AI developer with IBM Consulting, you are primarily responsible for developing 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 Required technical and professional expertise Professional with at least 5-8 years of experience ideally in data and analytics and/or architecture, including 2 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 stake holder Preferred technical and professional experience Experienced in developing AI solutions 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 seeking an experienced and innovative AI Solution Engineer to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI and Automation solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. In this role, you will be resposible for : 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. Customer Engagement and SupportAct as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Bachelor’s or Master's degree in Computer Science, Artificial Intelligence, or a related field. 4+ years of experience in designing and delivering AI solutions, with a focus on foundation models, large language models, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and related services is a plus. Solutioning ExperienceExperience in solution architecture and design, translating business requirements into technical specifications, and developing scalable and robust AI solutions. Business AcumenAbility to understand customer needs and business objectives. Experience in working closely with customers and translating their requirements into effective AI solutions. Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients’ business processes and cha Preferred technical and professional experience Experience in full AI project lifecycle, from research and prototyping to deployment in production environments. Familiarity with Agile development methodologies Experience with AI and/or data governance Experience with building business automation or digital labor solutions Experience with building customer care solutions/digital assistants Experience with Red Hat OpenShift Experience with Kubernetes Experience with vector DB’s or open file formats like parquet ,avro or orc

Job Title: AI/ML and Chatbot Lead Experience Level: 10+ Years (Lead/Architect level) Location: Remote Employment Type: Full-time No. of Positions: 1 Job Overview: We are seeking a visionary and hands-on AI/ML and Chatbot Lead to spearhead the design, development, and deployment of enterprise-wide Conversational and Generative AI solutions. This role will establish and scale our AI Lab function, define chatbot and multimodal AI strategies, and deliver intelligent automation solutions that enhance user engagement and operational efficiency. Key Responsibilities Define and lead the enterprise-wide strategy for Conversational AI, Multimodal AI, and Large Language Models (LLMs). Build an AI/Chatbot Lab , creating a roadmap and driving innovations across in-app, generative, and conversational AI. Architect scalable AI/ML systems including presentation, orchestration, AI, and data layers. Collaborate with business stakeholders to assess needs, conduct ROI analyses, and deliver impactful AI use cases. Identify and implement agentic AI capabilities and SaaS optimization opportunities. Deliver POCs, pilots, and MVPs owning the design, development, and deployment lifecycle. Lead, mentor, and scale a high-performing team of AI/ML engineers and chatbot developers . Build multi-turn, memory-aware conversations using frameworks like LangChain or Semantic Kernel . Integrate bots with platforms like Salesforce, NetSuite, Slack , and custom applications via APIs/webhooks. Implement and monitor chatbot KPIs using tools like Kibana , Grafana , and custom dashboards. Champion ethical AI , governance, and data privacy/security best practices. Must-Have Skills 10+ years in AI/ML; demonstrable success in chatbot, conversational AI , and generative AI implementations. Experience building and operationalizing an AI/Chatbot architecture framework used enterprise-wide. Expertise in: Python , LangChain, ElasticSearch, NLP (spaCy, NLTK, Hugging Face) LLMs (e.g., GPT, BERT), RAG, prompt engineering Chatbot platforms (Azure OpenAI, MS Bot Framework), CLU, CQA AI solution deployment and monitoring at scale Familiarity with: Machine learning algorithms, deep learning, reinforcement learning NLP techniques for NLU/NLG Cloud platforms ( AWS, Azure, GCP ), Docker , Kubernetes Vector DBs (Pinecone, Weaviate, Qdrant) Semantic search, knowledge graphs, intelligent document processing Strong grasp of AI governance , documentation, and compliance standards Excellent team leadership, communication, and documentation skills Good-to-Have Skills Experience with Glean , Perplexity.ai , Rasa , XGBoost Familiarity with Salesforce , NetSuite , and business domains like Customer Success Knowledge of RPA tools like UiPath and its AI Center Role & responsibilities Interested candidate can call at 7087707007

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Key Responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcedeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

ideyaLabs is seeking a talented and innovative Generative AI Engineers with experience in leveraging Low-Code/No-Code (LCNC) platforms. This unique role will be at the forefront of developing and deploying cutting-edge generative AI models while utilizing LCNC tools to accelerate prototyping, integration, and application development. The ideal candidate will possess a strong understanding of generative AI techniques, proficiency in programming, and a passion for exploring the synergy between AI and rapid application development. Responsibilities: Generative AI Model Development & Deployment: Design, develop, train, and evaluate generative AI models for various applications (e.g., text generation, image synthesis, code generation, synthetic data generation). Implement and optimize generative AI models using relevant frameworks (e.g., TensorFlow, PyTorch, Transformers). Deploy and scale generative AI models on cloud platforms (e.g., AWS, Azure, GCP) or on-premise infrastructure. Stay up-to-date with the latest advancements in generative AI research and techniques. Low-Code/No-Code Platform Utilization: Utilize LCNC platforms (e.g., Zoho Creator, Microsoft Power Apps, OutSystems, Mendix, Quixy) to rapidly prototype and build applications that integrate with generative AI models. Develop user interfaces and workflows using LCNC visual development tools. Connect generative AI APIs and services to LCNC applications. Build and deploy data connectors and integrations between various systems using LCNC capabilities. Integration & Application Development: Design and implement robust APIs and integration strategies to connect generative AI models with other systems and applications. Collaborate with software engineers and data scientists to build end-to-end AI-powered solutions. Develop and maintain documentation for AI models, LCNC applications, and integration processes. Experimentation & Innovation: Research and experiment with new generative AI models, LCNC platforms, and integration techniques. Evaluate the feasibility and potential of applying generative AI to solve specific business problems. Contribute to the development of best practices and guidelines for using generative AI and LCNC tools. Collaboration & Communication: Work closely with cross-functional teams, including product managers, designers, and business stakeholders. Communicate technical findings and progress effectively to both technical and non-technical audiences. Participate in code reviews and knowledge-sharing activities. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 3 + years of experience in developing and deploying machine learning models, with a focus on generative AI. Proven experience working with at least one or more Low-Code/No-Code development platforms (e.g., Zoho Creator, Microsoft Power Apps, OutSystems, Mendix, Quixy). Experience in building and consuming APIs (RESTful, etc.). Technical Skills: Strong programming skills in Python and experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Transformers). Solid understanding of deep learning concepts and architectures relevant to generative models (e.g., GANs, VAEs, Diffusion Models, Transformers). Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. Familiarity with data preprocessing, feature engineering, and model evaluation techniques. Understanding of database concepts and SQL. Proficiency in using visual development tools and integration capabilities of LCNC platforms. Soft Skills: Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to learn quickly and adapt to new technologies. Proactive and self-motivated with a strong sense of ownership. Passion for innovation and exploring the potential of generative AI. Preferred Qualifications: Experience with specific generative AI applications relevant to our industry (e.g., content generation, synthetic data). Familiarity with containerization technologies (e.g., Docker, Kubernetes). Experience with MLOps practices and tools. Certifications in relevant AI/ML or LCNC platforms.

Role - Senior Data Scientist / Senior Gen AI Engineer Exp Range - 8 to 18 yrs Position - Permanent Fulltime Company - Data Analytics & AIML MNC Location - Hyderabad, Pune, Bangalore (Relocation accepted) About the Role: We are seeking a Software Engineer with expertise in Generative AI and Microsoft technologies to design, develop, and deploy AI-powered solutions using the Microsoft ecosystem. You will work with cross-functional teams to build scalable applications leveraging generative AI models and Azure services. Skills Required: Experience with Large Language Models (LLMs) like GPT, LLaMA, Claude, etc. Proficiency in Python for building and fine-tuning AI/ML models Familiarity with LangChain , LLMOps , or RAG (Retrieval-Augmented Generation) pipelines Experience with Vector Databases (e.g. FAISS, Pinecone, Weaviate) Knowledge of Prompt Engineering and model evaluation techniques Exposure to cloud platforms (Azure, AWS or GCP) for deploying GenAI solutions Preferred Skills: Experience with Azure OpenAI , Databricks or Microsoft Fabric Hands-on with Hugging Face Transformers , OpenAI APIs or custom model training

Preferred candidate profile 1. LLM Basics : (Llama, Gemini ) : Understand the basics of generative AI and LLMs, such as key terminology, uses, potential issues, and primary frameworks. One should know what the data is trained on and any potential biases/issues that there may be with the data . Knowledge on know exactly how big LLMs can be, how computationally expensive training will be, and the differences between training LLMs and machine learning models. 1. Prompt Engineering : Knowledge on designing inputs for LLMs once theyre developed. 2. Prompt Engineering with OpenAI : As a leading figure in LLMs and generative AI, it’s important to know how to use prompt engineering specifically with OpenAI tools, as you’ll likely be using them at some point in your career. 3. Question-Answering :Question-answering (QA) LLMs are a type of large language model that has been trained specifically to answer questions. 4. Fine-Tuning : Knowledge on Fine-tuning to improve the performance of an LLM on a variety of tasks, including text generation, translation, summarization, and question-answering. Customize LLMs for specific applications, such as customer service chatbots or medical diagnosis systems. Awareness on supervised learning. This involves providing the LLM with a dataset of labelled data, where each data point is a pair of input and output.. 1. Lang Chain : To architect complex LLM pipelines by chaining multiple models together (Classification, text generation, code generation, etc.)`Agents` to interact with all these external systems to execute actions dictated by LLMs. 2. Parameter Efficiency/Tuning : LORA 3. RAG Building : Generative AI, mastering RAG building—short for Retrieval-Augmented Generation—is becoming increasingly crucial 4. ML OPS and in particular LLMOps : Large Language Model Operations, is the practice of managing and maintaining large language models (LLMs) in a production setting 5. TensorFlow i s like a versatile toolbox for creating intelligent programs that can learn and understand various concepts, including machine learning, deep learning, and data science

We are looking for a passionate and skilled AI/ML Developer with 4 to 9 years of experience to join our team in Kolkata. The ideal candidate will have hands-on experience in building and deploying AI/ML models, with strong proficiency in Python, machine learning frameworks, and a solid understanding of modern development practices. Role & responsibilities Design, develop, and deploy machine learning and AI solutions for business needs. Work with Generative AI models, Whisper (Speech-to-Text/Text-to-Speech), and NLP-based chatbot solutions. Build and maintain scalable and reliable AI model pipelines. Collaborate with cross-functional teams using Agile methodologies. Perform data preprocessing, feature engineering, and model tuning. Deploy models to production environments and monitor performance. Integrate AI/ML solutions into web applications using technologies such as React.js, Oracle APEX, Oracle JET, and HTML5. Participate in system design and apply software engineering best practices including design patterns and testing. Preferred candidate profile AI/ML & Data: Machine Learning, Deep Learning Generative AI, Whisper (Speech-to-Text/Text-to-Speech) Chatbot Development, Natural Language Processing (NLP) AI Model Deployment (cloud/on-premise) Programming & Frameworks: Proficient in Python Experience with TensorFlow, PyTorch Frontend/Backend & Scripting: React.js, HTML5 Oracle APEX, Oracle JET Linux Shell Scripting Tools & DevOps: Docker, Git, Jira Methodologies: Agile Development System Design, Design Patterns Preferred Qualifications: Bachelors/Master’s degree in Computer Science, Engineering, or a related field. Strong analytical and problem-solving skills. Excellent communication and teamwork abilities. Experience working in a product or R&D environment is a plus.

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Role & responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Preferred candidate profile Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcdeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

reliability Role Summary: The AI/ML Engineers will be responsible for developing, testing, and deploying machine learning models and AI algorithms that can be integrated into the product suite. The ideal candidate will have expertise in integrating large language models (LLMs) with external knowledge bases, fine-tuning model architectures for specific tasks, and optimizing retrieval strategies to improve the accuracy and relevance of generated content. Key Responsibilities: Implement and optimize AI/ML algorithms for product integration. Collaborate with data scientists to deploy models and integrate them with software products. Design scalable solutions for AI/ML applications. Develop automated pipelines for continuous model training and updates. Work with engineering teams to ensure smooth integration and operation of AI models in production. Monitor and troubleshoot AI/ML models to ensure reliability and performance. Required Experience: 4 - 6 years of hands-on experience in machine learning model development and deployment. Hands-on experience in developing and fine-tuning Generative AI models, specifically focusing on Retrieval-Augmented Generation (RAG) systems. Experience with frameworks such as Hugging Face, OpenAI, or other GenAI platforms, along with proficiency in data preprocessing and model evaluation, is required Proficiency in Python, TensorFlow, Keras, PyTorch, or other AI/ML frameworks. Experience with model deployment and monitoring in production environments. Strong problem-solving skills and experience with cloud computing platforms (AWS, GCP, Azure). Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).