880 Nlp Jobs - Page 21

We Advantum Health Pvt. Ltd - US Healthcare MNC looking for Data Scientist for our Hyderabad location. We Advantum Health Private Limited is a leading RCM and Medical Coding company, operating since 2013. Our Head Office is located in Hyderabad, with branch operations in Chennai and Noida. We are proud to be a Great Place to Work certified organization and a recipient of the Telangana Best Employer Award. Our office spans 35,000 sq. ft. in Cyber Gateway, Hitech City, Hyderabad Job Title: Data Scientist Location: Hitech City, Hyderabad, India Work from office Ph: 9177078628, 7382307530, 9059683624 Address: Advantum Health Private Limited, Cyber gateway, Block C, 4th floor Hitech City, Hyderabad. Location: https://www.google.com/maps/place/Advantum+Health+India/@17.4469674,78.3747158,289m/data=!3m2!1e3!5s0x3bcb93e01f1bbe71:0x694a7f60f2062a1!4m6!3m5!1s0x3bcb930059ea66d1:0x5f2dcd85862cf8be!8m2!3d17.4467126!4d78.3767566!16s%2Fg%2F11whflplxg?entry=ttu&g_ep=EgoyMDI1MDMxNi4wIKXMDSoASAFQAw%3D%3D Job Summary: We are seeking a highly skilled and results-driven Data Scientist with strong AI/ML expertise to join our technology team in Hyderabad. This role will play a critical part in designing, developing, and deploying machine learning models that support strategic initiatives across healthcare operations, RCM automation, and intelligent decision-making platforms. Location: Hyderabad, India Job Type: Full-time Experience Level: 3 to 8 years Key Responsibilities: Design and implement advanced machine learning and AI algorithms for real-world business use cases (e.g., Denial Prevention, Prior Authorization AI, Coding AI). Work with structured and unstructured healthcare data (e.g., claims, clinical notes, payer data) to create actionable insights. Collaborate with cross-functional teams including data engineers, product managers, and automation developers to deploy end-to-end AI solutions. Build and maintain model pipelines: data preprocessing, feature engineering, training, evaluation, and deployment. Develop NLP models to extract, classify, and interpret clinical and operational data from free-text sources. Evaluate model performance using appropriate metrics and iterate to improve accuracy, precision, and recall. Document experiments, methodologies, and findings to ensure traceability and reproducibility. Contribute to ML Ops efforts to ensure scalable, robust, and production-ready model deployments. Required Skills and Qualifications: Bachelors or Masters in Computer Science, Data Science, AI/ML, or a related field. 3+ years of hands-on experience in data science and machine learning. Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers. Strong experience in NLP, classification, entity recognition, or sequence labeling tasks. Familiarity with model versioning, deployment (e.g., Flask, FastAPI), and cloud platforms (Azure, AWS, or GCP). Experience working with healthcare datasets (e.g., claims, EHR, CPT, ICD-10) is highly preferred. Strong problem-solving and communication skills with the ability to explain complex models to non-technical stakeholders. Preferred Qualifications: Exposure to MLOps, model monitoring, and continuous model training pipelines. Experience working in RCM or healthcare IT environments. Contributions to open-source projects or relevant AI/ML publications. Follow us on LinkedIn, Facebook, Instagram, Youtube and Threads for all updates: Advantum Health Linkedin Page: https://www.linkedin.com/showcase/advantum-health-india/ Advantum Health Facebook Page: https://www.facebook.com/profile.php?id=61564435551477 Advantum Health Instagram Page: https://www.instagram.com/reel/DCXISlIO2os/?igsh=dHd3czVtc3Fyb2hk Advantum Health India Youtube link: https://youtube.com/@advantumhealthindia-rcmandcodi?si=265M1T2IF0gF-oF1 Advantum Health Threads link: https://www.threads.net/@advantum.health.india HR Dept, Advantum Health Pvt Ltd Cybergateway, Block C, Hitech City, Hyderabad Ph: 9177078628, 7382307530, 9059683624

Job Title: Senior developer - Artificial Intelligence & Machine Learning Location: Chennai / Bangalore / Pune (Hybrid model - 2 days working from office) Role Summary We are seeking a skilled and hands-on Senior Artificial Intelligence & Machine Learning (AI/ML) Engineer to build and productionize AI solutionsincluding fine-tuning large language models (LLMs), implementing Retrieval-Augmented Generation (RAG) workflows, multi-agent applications and MLOps pipelines. This role focuses on individual technical contribution and requires close collaboration with solution architects, AIML leads, and fellow engineers to translate business use cases into scalable, secure, cloud-native AI services. The ideal candidate will bring deep technical expertise across the AI/ML lifecycle—from prototyping to deployment—while contributing to a culture of engineering excellence through peer reviews, documentation, and platform innovation. They will play a critical role in delivering robust, high-performance AI systems in partnership with the broader AI/ML team. Key Responsibilities Model Development & Optimization Fine-tune foundation models (e.g., GPT-4, Llama 3). Implement prompt engineering and basic parameter-efficient tuning (e.g., LoRA). Conduct model evaluation for quality, bias, and hallucination; analyze results and suggest improvements. RAG & Agentic Systems (Exposure, Not Ownership) Assist in building RAG pipelines: Participate in integrating and embedding generation, vector stores (e.g., FAISS, pgvector), and retrieval/ranking components. Work with multi-agent frameworks (e.g., LangChain, Crew AI) Production Engineering / MLOps Contribute to CI/CD pipelines for model training and deployment (e.g., GitHub Actions, SageMaker Pipelines). Help automate monitoring for latency, drift, and cost; assist in lineage tracking (e.g., MLflow). Containerize services with Docker and assist in orchestration (e.g., Kubernetes/EKS/GKE) Data & Feature Engineering Build and maintain data pipelines for collection, cleansing, and feature generation (e.g., Airflow, Spark). Implement basic data versioning and assist with synthetic data generation as needed Code Quality & Collaboration Participate in design and code reviews. Contribute to testing (unit, integration, guardrail/hallucination tests) and documentation. Share knowledge through sample notebooks and internal sessions Security, Compliance, Performance Follow secure coding and Responsible AI guidelines. Assist in optimizing inference throughput and cost (e.g., quantization, batching) under guidance. Ensure SLAs are met and contribute to system auditability Technology Stack Programming Languages & Frameworks Python (expert) JavaScript/Go/TypeScript (nice-to-have) Strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch. PyTorch, TensorFlow/Keras, Hugging Face Transformers/PEFT, LangChain/LlamaIndex, Ray/PyTorch Lightning, FastAPI/Flask Experience working with RESTful APIs, authentication (OAuth, API keys), and pagination Cloud & DevOps Expertise in one or more cloud vendors like AWS, GCP, Azure Containers (Docker), Orchestration (Kubernetes, EKS/GKE/AKS) MLOps Databases Relational: PostgreSQL, MySQL NoSQL: MongoDB / DynamoDB Vector Stores: FAISS / pgvector / Pinecone / OpenSearch / Milvus / Weaviate RAG Components Document loaders/parsers, text splitters (recursive/semantic), embeddings (OpenAI, Cohere, Vertex AI), hybrid/BM25 retrievers, rerankers (Cross-Encoder) Multi-Agent Frameworks Crew AI / AutoGen / LangGraph / MetaGPT / Haystack Agents, planning & tool-use patterns Testing & Quality Unit/integration testing (pytest), guardrails Qualifications 7–10years total software/ML engineering experience, including 3+years delivering ML models or GenAI systems to production. Proven track record building and optimising RAG or LLMpowered applications at scale Proficiency in Python and ML frameworks (PyTorch, TensorFlow) and in cloudnative deployment (AWS/GCP/Azure). Handson experience with vector databases, embeddings, and prompt engineering. Experience in regulated industries (Fintech, Healthcare, eCommerce) is a plus. Experience with multiagent frameworks (CrewAI, AutoGen, LangGraph). Certifications such as AWS CertifiedMachineLearning Specialty / AzureAIEngineer / GoogleProfessionalMachineLearningEngineer. Bachelor’s degree in Computer Science, Data Science, Engineering or related discipline (Master’s preferred). Soft Skills & Leadership Attributes Ownership mindset: drives features from design through deployment and monitoring. Clear communicator: explains technical tradeoffs to stakeholders, writes concise docs, and updates project artefacts. Collaboration & mentorship: pairs with junior ngineers, shares knowledge in brownbag sessions, gives constructive PR feedback. Continuous learning: tracks latest GenAI research, evaluates new tooling, and proposes incremental improvements.

Job Title: Artificial Intelligence & Machine Learning Tech Lead Location: Chennai (Hybrid model - 2 days working from office) Role Summary We are seeking a seasoned Artificial Intelligence & Machine Learning (AI/ML) Tech Lead to drive the technical design, development, and deployment of AI solutionsincluding fine-tuning foundation models, building agentic applications, and implementing production-grade Retrieval-Augmented Generation (RAG) pipelines. This role requires close collaboration with pre-sales teams, account delivery managers, solution architects, and enterprise clients to define and deliver AI solutions tailored to business needs. The ideal candidate will provide hands-on technical leadership throughout the AI/ML lifecycle—leading proof-of-concept (POC) efforts, conducting solution demos, and overseeing production-grade implementations. They will also mentor engineering teams, enforce best practices, and ensure the successful delivery of AI initiatives Key Responsibilities 1. Lead Technical Delivery & Mentorship Lead and mentor a team of 6–10 engineers; establish coding standards, conduct design and PR reviews, and drive continuous improvement. Foster a culture of knowledge-sharing through KT Sessions, documentation, and best-practice guides. 2. AI/ML Model Development & Optimization Develop, fine-tune, and optimize models using PyTorch, TensorFlow, and modern ML frameworks. Apply prompt engineering and advanced techniques to foundation models (e.g., GPT-4, Claude, Llama). Deliver NLP solutions such as document classification, sentiment analysis, summarization, entity extraction, conversational AI, and generative content/workflow automation. Design and implement RAG workflows leveraging vector databases, smart chunking, ranking, and caching for accurate, grounded responses. Build multi-agent systems for task decomposition, planning, and tool usage in complex environments. 3. MLOps & Productionization Implement MLOps best practices: CI/CD pipelines, model monitoring, feature stores, lineage, and governance. Ensure model reproducibility, drift detection, explainability (SHAP, LIME), and responsible AI practices. Optimize inference throughput/latency and ensure robust rollback strategies. 4. Performance, Security, and Compliance Ensure security, compliance, and performance of AI solutions, adhering to industry standards and regulations. Integrate with external APIs, optimize for cost/latency, and manage observability. 5. Stakeholder Engagement & Roadmapping Translate business objectives into technical designs; communicate risks, metrics, and impact to executives and stakeholders. Produce design diagrams, runbooks, and model cards; lead knowledge-sharing sessions and workshops. Technology Stack Programming Languages & Frameworks Python (expert) JavaScript/Go/TypeScript (nice-to-have) Strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch. PyTorch, TensorFlow/Keras, Hugging Face Transformers/PEFT, LangChain/LlamaIndex, Ray/PyTorch Lightning, FastAPI/Flask Experience working with RESTful APIs, authentication (OAuth, API keys), and pagination Cloud & DevOps Expertise in one or more cloud vendors like AWS, GCP, Azure Containers (Docker), Orchestration (Kubernetes, EKS/GKE/AKS) Infrastructure as Code (nice-tohave) MLOps Experiment Tracking: DVC, Weights & Biases, Neptune, TensorBoard etc Databases Relational: PostgreSQL, MySQL NoSQL: MongoDB / DynamoDB Vector Stores: FAISS / pgvector / Pinecone / OpenSearch / Milvus / Weaviate RAG Components Document loaders/parsers, text splitters (recursive/semantic), embeddings (OpenAI, Cohere, Vertex AI), hybrid/BM25 retrievers, rerankers (Cross-Encoder) Multi-Agent Frameworks Crew AI / AutoGen / LangGraph / MetaGPT / Haystack Agents, planning & tool-use patterns Testing & Quality Unit/integration testing (pytest), guardrails, hallucination tests, behavioral evals Security & Compliance Best Practices & Design Governance Apply industry best practices: Secure AI development, responsible AI, model explainability, bias detection, and privacy-preserving techniques. Champion documentation standards, reusable reference architectures, and model cards. Participate in architecture review boards and provide guidance to ensure consistency and quality across AI initiatives. Leadership & Pre-Sales Experience Proven track record shipping ML products at scale Lead client workshops, technical discovery, and early-stage assessments. Support business development by identifying architectural differentiators and scalable patterns. Qualifications 10–12 years of experience in software engineering/data science, with 4+ years leading AI/ML projects end-to-end. Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Data Science, or related field. Certifications preferred: AWS Certified Machine Learning / Google Professional Machine Learning Engineer / Azure AI Engineer Associate and Kubernetes CKA/CKAD. Experience in regulated industries (Fintech, Healthcare, eCommerce) is a plus. Soft Skills & Leadership Attributes Influential communication: Translate complex ML concepts for non-technical stakeholders; strong presentation & storytelling. Mentorship mindset: Coach, upskill, and inspire cross-functional teams; foster psychological safety. Ownership & bias for action: Deliver POCs, iterate based on feedback, drive solutions to production. Critical thinking & experimentation: Data-driven decision making, hypothesis testing, A/B experimentation. Adaptability: Stay current with rapid advances in GenAI, tooling, and research; evaluate emerging models/services.

Develop and deploy ML models for real-time applications Work on NLP, computer vision, and deep learning projects Collaborate with data scientists and software teams for production-ready solutions Requirement: TensorFlow Developer Certificate

About Company: Papigen is a fast-growing global technology services company, delivering innovative digital solutions through deep industry experience and cutting-edge expertise. We specialize in technology transformation, enterprise modernization, and dynamic areas like Cloud, Big Data, Java, React, DevOps, and more. Our client-centric approach combines consulting, engineering, and data science to help businesses evolve and scale efficiently. We support flexible engagement models including Time & Material, Staff Augmentation, and SoW-based Managed Services. About the Role: Were hiring a Senior Machine Learning Developer to join our data modernization and AI engineering team. In this role, you will design, develop, and deploy ML models and intelligent systems that drive next-gen financial insights. You will work with structured and unstructured data on a secure cloud-based infrastructure leveraging Azure ML , Python , and modern NLP/AI frameworks . Key Responsibilities: Build, train, and implement ML/NLP models for classification, clustering, and text analysis Work with large-scale financial data and develop intelligent automation solutions Clean, normalize, and validate structured and unstructured datasets Build and consume REST APIs for ML services Integrate Azure AI services including Cognitive Services, OpenAI, and Form Recognizer Collaborate with cross-functional teams including DevOps, data engineers, and PMs Follow best practices in model versioning, testing, and deployment Document ML workflows and models for reproducibility and compliance Required Skills & Experience: 6+ years of experience in software/data engineering, with 3+ years in ML/AI Strong Python expertise with libraries like Scikit-learn , Pandas , NumPy , etc. Experience with ML frameworks such as TensorFlow or PyTorch Experience building AI models for NLP tasks like classification, summarization, or entity extraction Familiarity with Azure AI/ML services (Azure ML Studio, Cognitive Services, AKS, Key Vault) Experience handling both structured and unstructured datasets REST API and Python library development Excellent communication and documentation skills Nice to Have: Exposure to finance sector datasets or financial document automation Experience with Azure OpenAI , Azure Language Studio, or Chatbot frameworks Familiarity with statistical programming languages like R or Julia Microsoft Data or Azure AI/ML certifications Benefits and Perks Opportunity to work with leading global clients Flexible work arrangements with remote options Exposure to modern technology stacks and tools Supportive and collaborative team environment Continuous learning and career development opportunities

Skills Required Deep Learning Expertise: Strong understanding of deep learning concepts, including neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), transfer learning, etc. Proficiency in Machine Learning Frameworks: Hands-on experience with popular frameworks such as TensorFlow, Keras, PyTorch, or MXNet. Mathematics for Machine Learning: Solid knowledge of mathematical foundations, including linear algebra, probability, statistics, and optimization algorithms related to deep learning. Experience in Model Building: Ability to build, train, and optimize deep learning models for different use cases like image classification, NLP, speech recognition, etc. Content Development Skills: Experience in creating comprehensive learning materials, including video lectures, assignments, quizzes, and projects for students. Programming Proficiency: Strong knowledge of Python and libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn. Cloud and Deployment: Familiarity with deploying deep learning models on cloud platforms like AWS, GCP, or Azure. Hands-on Projects: Experience in creating hands-on projects to help students apply learned concepts practically. Pedagogy & Curriculum Development: Ability to structure and organize technical content clearly and logically to suit a range of learning levels. Communication Skills: Excellent written and verbal communication skills to explain complex technical concepts simply and effectively. Collaboration Skills: Ability to work with instructors, instructional designers, and subject matter experts to create engaging and accurate content. Prior experience in content development is preferred. Responsibilities Assist the Technical Content Developer (TCD) in creating high-quality technical content across various formats such as text, video scripts, presentations, and interactive materials. Support the TCD in researching and gathering resources to ensure the accuracy and relevance of the content. Collaborate with Subject Matter Experts (SMEs) and other team members to refine and polish content for final delivery. Contribute to developing curriculum outlines, roadmaps, and learning objectives under the guidance of the TCD. Ensure content is optimized for different learning formats, adapting materials as required. Participate in regular content reviews and provide suggestions for improvements or updates based on learner feedback. Stay updated on industry trends and assist in incorporating emerging technologies and techniques into the content. Manage smaller content projects independently while maintaining alignment with the overall curriculum goals. Job Overview Location : NxtWave Office Spaces in Hyderabad Job Type : Full-Time Working days : 5

Key Responsibilities: Machine Learning (ML): Design, build, and deploy ML pipelines for structured and unstructured data. Conduct feature engineering , model selection, and hyperparameter tuning. Evaluate model performance using industry-standard metrics and improve accuracy. Collaborate with data engineering teams to ensure clean and accessible data for model training. Apply supervised, unsupervised, and reinforcement learning techniques as per use case. Natural Language Processing (NLP): Develop NLP pipelines for text classification, sentiment analysis, entity recognition, summarization , etc. Leverage libraries like spaCy, NLTK, Hugging Face Transformers, and Gensim . Preprocess and tokenize large corpora using advanced NLP methods. Implement solutions for multi-lingual, domain-specific text data challenges. Integrate NLP services with applications or workflows. Large Language Models (LLM): Fine-tune and deploy LLMs (e.g., GPT, LLaMA, BERT, Falcon, Mistral ) on custom datasets. Use prompt engineering and retrieval augmented generation (RAG) to build intelligent systems. Optimize inference performance and latency for production-level deployment. Stay updated with the latest in GenAI, foundation models, and transformer architectures. Work on use cases like chatbots, question answering, summarization, content generation , and semantic search . Required Skills: Proficiency in Python , PyTorch or TensorFlow , and data science libraries ( scikit-learn , pandas , NumPy ). Experience with NLP frameworks and transformer-based architectures . Exposure to LLM model training/fine-tuning using tools like Hugging Face, LangChain, or OpenAI API. Familiarity with MLOps , model versioning, and deployment using Docker/Kubernetes. Understanding of vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings.

Looking for an AI/ML Engineer to build smart automation solutions. Must have experience in Python, Node.js, or Java scripting, and strong knowledge of ML/AI techniques and model integration. Required Candidate profile AI/ML Engineer with 4–8 years of experience in developing intelligent testing solutions. Skilled in Python/Node.js/Java, ML model deployment, automation frameworks, and cloud platforms.

ML Engineer is responsible to discover the information hidden in vast amounts of data and help us make smarter decisions to deliver better products. Your primary focus will be in applying machine learning techniques for data mining and statistical analysis, Text analytics using NLP/LLM and building high quality prediction systems integrated with our products. Job Responsibilities: Building models using best in class ML technology including LLMs. Training/fine tuning models with new/modified training dataset. Selecting features, building, and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods Processing, cleansing, and verifying the integrity of data used for analysis Enhancing data collection procedures to include information that is relevant for building analytic systems Technical skills Mandatory 5 to 10 years of experience as Machine Learning Engineer with strong Python skill. Graduate in Engineering, Technology along with good business skills Good scripting and programming skills in Python Excellent understanding of machine learning techniques and algorithms including knowledge about LLM like GPT, Llama, Claude, or Anthropic models etc. Experience with NLP. Knowledge about applied statistics skills, such as distributions, statistical testing, regression, etc. Basic understanding of NoSQL databases, such as MongoDB, Cassandra. Nice to have Exposure to financial research domain Experience with JIRA, Confluence Understanding of scrum and Agile methodologies Experience with data visualization tools, such as Grafana, power BI, GGplot, etc. Soft skills Oral and written communication skills Good problem solving and negotiation skills Passion, curiosity and attention to detail

Very Urgent: GenAI Consultant / Sr. GenAI Consultant Company: AurumData Solutions Location: Hyderabad Experience:7 -10Years (2+years in AI) Work type: Work From Office Key skills: GenAI, Python, Data analysis, LLM, TensorFlow, PyTorch, SQL, RAG, NLP, LangChain, LangGraph, SQL etc.. JD for Gen AI Consultant: This job description outlines a role for an AI Specialist who will be responsible for developing and implementing AI solutions across various domains. Here's a breakdown of the key aspects: This position combines traditional machine learning expertise with cutting-edge LLM technologies and practical application development skills. The role requires experience across the full AI development stack, from data management and model fine-tuning to building sophisticated agent-based systems and user-facing applications. Core Responsibilities - Developing AI models and algorithms - Implementing machine learning techniques for data analysis - Creating NLP applications (chatbots, virtual assistants) - Data preprocessing and feature engineering - Model evaluation and optimization - Research and innovation in AI - Cross-functional collaboration - Technical documentation Required Skills - Strong background in machine learning and deep learning - Python programming with frameworks like TensorFlow and PyTorch - Independent project management capabilities - Data science workflow experience - Cloud platform knowledge (AWS, Google Cloud, Azure) - Problem-solving with practical solutions - **Experience with vector databases** - **Knowledge of Large Language Models (LLMs)** - **Implementation of Retrieval-Augmented Generation (RAG) systems** - **Experience with LLM fine-tuning techniques** - **Expertise in fine-tuning LLMs for specific domains/tasks** - **Front-end development skills** for AI application interfaces - **Proficiency with Pydantic** for data validation and settings management - **Experience developing agentic frameworks** for autonomous AI systems - **Familiarity with LangChain** for building LLM applications - **Knowledge of Hugging Face** ecosystem and model hub - **Experience with LangGraph** for building complex, multi-agent systems Qualifications - Bachelor's or Master's in Computer Science, AI, or related fields - Experience in startup environments - Passion for AI applications If you are interested, kindly send your CVs to Madhavi@aurumdatasolutions.com

Role Overview We are seeking a highly skilled Senior Data Scientist with a minimum of 5 years of experience to join our Customer Experience Analytics team. The successful candidate will play a pivotal role in building products that enable leadership to extract insights efficiently, fostering data-driven decision-making processes. If you are passionate about leveraging NLP, ML algorithms, and feature engineering to drive business impact and enhance the customer experience, we invite you to join our team at FedEx. What youll be working on Collaborate cross-functionally with various teams to analyze user behavior and usage patterns, extracting actionable insights to enhance customer experience. Utilize advanced statistical techniques, NLP, and ML algorithms to identify opportunities for business problem-solving, leveraging scientific methodologies. Develop and refine predictive models based on historical user data, with a focus on feature engineering and improving machine learning algorithms for production. Design and execute controlled experiments to evaluate the potential impact of new approaches, contributing to data-driven decision-making processes. Provide detailed analysis and reporting on current trends and performance metrics, using NLP techniques for text data and identifying opportunities for improvement. Translate complex data findings into actionable insights for leadership, leveraging NLP outputs and ML algorithms for advanced analytics. Take ownership of end-to-end solution delivery, from problem statement formulation to product implementation, collaborating with other teams as needed. Contribute to the development of solutions and products supporting FedEx's GenAI services, specifically tailored for the Customer Experience vertical. What we are looking for Bachelors degree in computer science, Statistics, Mathematics, or a related field. Advanced degree preferred. Minimum of 5 years of experience in data science, with a focus on customer analytics, NLP, and machine learning. Proficiency in statistical analysis, predictive modeling, NLP techniques, and feature engineering. Any experience with development of GenAI solutions is preferred. Strong programming skills in languages such as Python, with experience in data manipulation and analysis libraries. Demonstrated experience in designing and executing controlled experiments to drive business insights. Excellent communication skills, with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders. Proven track record of delivering end-to-end solutions in a fast-paced, dynamic environment. Experience working with large-scale datasets and distributed computing frameworks is a plus.

Lead end-to-end architecture and design for mission-critical systems. Guide and influence engineering teams across multiple projects and domains. Make high-impact technical decisions that align with business goals. Define and enforce best practices in coding, design, testing, and operations. Partner with cross-functional teams including product, UX, QA, and DevOps. Identify technology gaps and drive solutions in infrastructure and product design. Contribute to long-term technical strategy and roadmap. Mentor and coach engineers at various levels to elevate team capabilities.

About this role: Wells Fargo is seeking a Quantitative Analytics Senior Manager to lead the Decision Science and Artificial Intelligence model risk team within Model Risk Management (MRM). Model Risk Management (MRM): Model Risk Managementis the second line of defense and is responsible for validating models, independently overseeing the management of model risk exposures across the enterprise, including governing, monitoring, and reporting on aggregate model risk exposures, model validations, and model oversight. This oversight extends to all phases of a models life cycle, including model identification, development, validation, implementation, resolution of model risk findings, model usage, performance monitoring, documentation, and retirement. The Decision Science and Artificial Intelligence (DSAI) team : this team oversees model risk in financial crimes, fair lending, marketing, fraud detection, credit scoring, natural language processing (NLP) and generative AI. The responsibilities of the DSAI Group include an end-to-end responsibility of managing the model risk over the model lifecycle including risk tiering, validation, and performance monitoring, etc. In this role, you will: Manage and develop teams responsible for the creation, implementation of complex financial and statistical models Analyze and manage risks to forecast losses or enable decision making for business, product, marketing, or other functional areas Support financial products, portfolios, business process and risk management Perform various compliance with corporate and regulatory reporting, involving finance and capitalization requirements Determine scope and prioritization of work Perform key input in the development of strategy, policies, procedures, and organizational controls Manage one or more teams of highly skilled quantitative analysts or managers Interface with internal and external audit or regulators Manage allocation of people and financial resources for Quantitative Analytics Develop and guide a culture of talent development to meet business objectives and strategy Required Qualifications: 6+ years of Quantitative Analytical experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 3+ years of management or leadership experience Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Desired Qualifications Knowledge of regulatory requirements: SR 11-7, industry standards on model validation, model governance, extensive expertise and keen insight on the model risk management process and future directions, expertise in defining model performance metrics and risk reduction techniques. Master's degree or higher in statistics, economics, computer science, optimization, electrical engineering, or a related quantitative discipline Previous model development or validation experiences for at least two areas of marketing, fraud detection, credit scoring, and generative AI. In-depth knowledge of AI/ML methodologies such as ensemble algorithms, neural networks, supervised and unsupervised learning. Strong computing and programming background and knowledge of one or more languages such as Python Experience with ML/AI computing platforms and tools Excellent oral, written, and interpersonal communication skills, with an ability to communicate effectively to audiences of varying technical maturity. Job Expectations: Manage a team of highly experienced model risk professionals, both individual contributors and managers, and deliver on the teams book of work. Be responsible for model risk management, including model validation, performance monitoring and governance for a suite of models covering marketing, fraud detection, credit scoring, natural language processing (NLP) and generative AI. Examine and disseminate best practices across validation teams to drive continuous improvement in model validation quality, processes, procedures, validation libraries, technical infrastructure, standards, and automation. Proactively identify efficiency opportunities and execute strategic initiatives in collaboration with peer teams. Formulate structures and processes to help validation teams to transition from a validation centric role to a model risk management centric function. Stakeholder management: engage both internal (developers, risk managers, auditors) and external (regulators) stakeholders to communicate model validation process and standards. Identify and work to reduce model risk according to Banks model risk policies and standards. Proactively manage talent within the team and contribute to managing the broader talent landscape of quantitative roles across the bank. Bring thought leadership to the MRM group and to the broader quant community in the bank.

Job Overview Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.ResponsibilitiesCredit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team. Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground. Qualifications 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.Excellent software engineering and programming skills, especially Python and SQL.A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.A deep understanding of using cloud computing infrastructure and data pipelines in production. Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done. Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.The drive to make a positive impact on customers' lives.

Qualifications Required: 8+ years of relevant industry experience leading the design, development, and deployment of machine learning models Experience being the technical lead for multiple project teams simultaneously Expert understanding of the state of the art of two or more fields in artificial intelligence; NLP and generative AI, probabilistic graphical models, time-series analysis, weak supervised learning, etc Understanding of LLMs and prompt engineering Previous experience mentoring, training, and developing junior members of the team; experience in employee performance reviews Expert understanding of Python and other common languages Deep understanding of machine learning model development life cycles Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain Extensive experience with at least one cloud-based ecosystem (Azure, GCP, AWS) Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.) Demonstrated ability to write high-quality, production-ready code (readable, well- tested, well-documented, with well-designed APIs) Demonstrated ability to develop novel machine learning methods that go beyond putting together existing open-source code, and to apply problem-solving skills to complex issues Solid understanding of Docker, Jenkins, Kubernetes, and other DevOps tools Excellent written and verbal communication skills Ability to travel as needed

Fresher or 3+ years of experience in AI/ML development with a focus on Generative AI and LLMs. Design, develop, and implement AI/ML models, including Generative AI and LLM-based solutions.

Looking for candidates from Premium institutes education background. Hands on Exp with AI ML, Gen AI - LLM, NLP, Lang chain

Role & responsibilities Total overall experience: 6-9 years Experience in Python: 5+ years (should be hands on with development) Experience in AI/ML: 1+ years Experience with Deployment on Cloud: 2+ years

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

We are seeking a highly skilled and experienced Senior AI Researcher to develop cutting-edge research and development in Natural Language Processing (NLP), Deep Neural Networks (DNN), Small Language Models (SLM), and Retrieval-Augmented Generation (RAG). The ideal candidate will focus on advancing information retrieval and semantic search technologies, driving innovation in model design, and optimizing performance for real-world applications. Key Responsibilities Model Development : Design, develop, and implement state-of-the-art machine learning and DNN models to enhance information retrieval capabilities. Data Management : Oversee the collection, cleaning, and preprocessing of datasets to ensure high-quality training data for DNN models. System Design : Develop scalable and efficient systems for deploying and managing NLP models, particularly for on-device applications. Research and Innovation : Conduct research to address abstract problems in NLP, IR, and semantic search, leveraging advanced methodologies to identify and solve complex challenges. Performance Optimization : Establish performance metrics, evaluate model effectiveness, and implement strategies to measure, manage, and maintain model performance. Collaboration : Work closely with cross-functional teams to align research efforts with business objectives and deliver impactful solutions. Expected Skills Proven experience in NLP, DNN, SLM, and RAG, with a strong track record of developing innovative solutions. Expertise in Information Retrieval (IR) and semantic search technologies. Hands on experience with bi encoders, cross encoders, SFT, distillation. LoRA techniques. Proficiency in TensorFlow and PyTorch for model development and deployment. In-depth knowledge of advanced model architectures such as BERT, RoBERTa, and their optimization for specific use cases Experience with model compression techniques (e.g., pruning, quantization) for on-device deployment. Knowledge of distributed computing frameworks for large-scale model training and inference. Research and Problem-Solving : NLP Advancements : Explore novel approaches to improve language understanding, generation, and retrieval capabilities in NLP models. Semantic Search : Develop advanced semantic search algorithms that enhance the relevance and accuracy of retrieved information. Retrieval-Augmented Generation : Investigate methods to integrate retrieval mechanisms with generative models for improved performance in tasks like question answering and summarization. On-Device Deployment : Focus on optimizing models for on-device deployment, ensuring efficiency in terms of latency, memory usage, and computational resources. Qualifications Experience : 6 to 15 years of experience in AI research, with a strong background in NLP, DNN, SLM, and IR. Education : Advanced degree (Ph.D. is a plus) in Computer Science, Artificial Intelligence, or a related field. Publications : Track record of publishing research papers in top-tier conferences and journals in AI, NLP, or IR domains. Impact As a Senior AI Researcher, you will play a pivotal role in shaping the future of NLP and information retrieval technologies. Your work will directly contribute to the development of intelligent systems that enable seamless and efficient information retrieval across various applications, driving innovation and delivering value to users worldwide.

Mandatory Skills & Experience : - Expertise in designing and optimizing machine-learning operations, with a preference for LLM Ops.- Proficient in Data Science, Machine Learning, Python, SQL, Linux/Unix shell scripting.- Experience on Large Language Models and Natural Language Processing (NLP), and experience with researching, training, and fine-tuning LLMs. Contribute towards fine tune Transformer models for optimal performance in NLP tasks, if required. Implement and maintain automated testing and deployment processes for machine learning models w.r.t LLMOps. Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. Develop and maintain robust monitoring and alerting systems for generative AI models ensuring proactive identification and resolution of issues. Research or engineering experience in deep learning with one or more of the following : generative models, segmentation, object detection, classification, model optimisations. Experience implementing RAG frameworks as part of available ready products. Experience in setting up the infrastructure for the latest technology such as Kubernetes, Serverless, Containers, Microservices etc. Experience in scripting/programming to automate deployments and testing, working on tools like Terraform and Ansible. Scripting languages like Python, bash, YAML etc. Experience on CI/CD opensource and enterprise tool sets such as Argo CD, and Jenkins (others like Jenkins X, Circle CI, Argo CD, Tekton, Travis, Concourse an advantage). Experience with the GitHub/DevOps Lifecycle. Experience in Observability solutions (Prometheus, EFK stacks, ELK stacks, Grafana, Dynatrace, AppDynamics). Experience in at least one of the clouds for example Azure/AWS/GCP. Significant experience on microservices based, container based or similar modern approaches of applications and workloads. You have exemplary verbal and written communication skills (English). Able to interact and influence at the highest level, you will be a confident presenter and speaker, able to command the respect of your audience. Desired Skills & Experience : Bachelor level technical degree or equivalent experience; Computer Science, Data Science, or Engineering background preferred; Master's Degree desired. Experience in LLM Ops or related areas, such as DevOps, data engineering, or ML infrastructure. Hands on experience in deploying and managing machine learning and large language model pipelines in cloud platforms (i.e., AWS, Azure) for ML workloads. Familiar with data science, machine learning, deep learning, and natural language processing concepts, tools, and libraries such as Python, TensorFlow, PyTorch, NLTK etc. Experience in using retrieval augmented generation and prompt engineering techniques to improve the model's quality and diversity to improve operations efficiency. Proven experience in developing and fine tuning Language Models (LLMs). Stay up to date with the latest advancements in Generative AI, conduct research, and explore innovative techniques to improve model quality and efficiency. The perfect candidate will already be working within a System Integrator, Consulting or Enterprise organisation with 8+ years of experience in a technical role within the Cloud domain. Deep understanding of core practices including SRE, Agile, Scrum, XP and Domain Driven Design. Familiarity with the CNCF open source community. Enjoy working in a fast paced and dynamic environment using the latest technologies.

We are seeking a motivated AI/ML and Python Developer with 6 years + of experience to join our team. The ideal candidate will have a strong foundation in AI/ML technologies, Python programming, and a passion for solving complex problems. Key Responsibilities: Develop, deploy, and maintain AI/ML models and solutions. Integrate and optimize Large Language Models (LLMs) and Generative AI (Gen AI) technologies. Design and implement AI agents for automation and decision-making tasks. Collaborate with cross-functional teams to deliver scalable AI-driven solutions. Technical Requirements: Proficiency in Python and AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with Gen AI, LLM integration (e.g., OpenAI GPT, Hugging Face), and AI agent development. Familiarity with data preprocessing, model training, and evaluation techniques. Knowledge of REST APIs, cloud platforms (e.g., AWS, GCP), and version control (e.g., Git). Understanding of NLP , computer vision, or reinforcement learning is a plus. Preferred Qualifications: Hands-on experience with Gen AI tools and frameworks. Must Have Good Command over LLM - NLP Techniques Proven ability to work on end-to-end AI/ML projects. Strong problem-solving and communication skills.

Hello Everyone, Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. Primary Skills: Machine Learning, Deep Learning, TensorFlow, PyTorch, Python, Data Analysis, Algorithm Design, AWS/GCP, Model Deployment, Big Data Technologies, Version Control (Git) Primary Responsibilities: Design and implement complex AI/ML models and algorithms Collaborate with data scientists to preprocess, analyze, and interpret large datasets Develop and maintain scalable and robust machine learning frameworks Integrate AI/ML solutions into products and develop new innovative features Perform model testing, validation, and optimization Deploy machine learning models into production environments Stay up-to-date with the latest advancements in AI/ML technologies and practices Mentor junior team members and provide technical guidance Required Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field 6+ years of experience in software engineering with a focus on AI/ML Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar Experience with data preprocessing and analysis Solid programming skills in Python, Java, or C++ Familiarity with cloud platforms and services (e.g., AWS, Google Cloud, Azure) Hands-on technical skill Proven excellent problem-solving skills and the ability to think algorithmically Proven solid communication and teamwork abilities Interested can share their updated CV at arshad_mohammad@optum.com Thanks and Regards, Arshad Ayub - Talent Scout Optum

Mandate Skills: - Gen AI - Python - NLP - LLM - RAG - Azure

Contractual (Project-Based) Notice Period: Immediate - 15 Days Fill this form: https://forms.office.com/Pages/ResponsePage.aspx?id=hLjynUM4c0C8vhY4bzh6ZJ5WkWrYFoFOu2ZF3Vr0DXVUQlpCTURUVlJNS0c1VUlPNEI3UVlZUFZMMC4u Resume- shweta.soni@panthsoftech.com