880 Nlp Jobs - Page 29

The Opportunity: We are seeking a talented and experienced Senior AI Engineer to play a pivotal role in developing and enhancing our conversational AI capabilities across multiple modalities (text, voice/telephony) and building intelligent agents to drive workflow automation. You will work closely with our Director of AI Engineering, product managers, and other engineering teams to bring our AI vision to life, primarily focusing on fine-tuning off-the-shelf Large Language Models (LLMs) and developing agentic systems for end-users (members, CBO staff, healthcare providers). This is a unique opportunity to apply your AI expertise to solve meaningful problems in the social and healthcare space, directly impacting people's lives. What You'll Do: Conversational AI Development & Fine-Tuning (Text & Voice): Lead the fine-tuning, evaluation, and deployment of pre-trained LLMs (e.g., Gemini, GPT series, open-source models) to create natural, empathetic, and effective conversational experiences for various user interactions via text-based channels (chat, SMS) and voice-based telephonic systems (IVR chatbots). Develop and implement strategies for data collection, preparation, and augmentation to support model fine-tuning and continuous improvement for both text and voice modalities. Design and implement robust evaluation frameworks to measure conversational AI performance, including metrics for accuracy, fluency, empathy, task completion, and call handling efficiency for telephonic agents. Work on prompt engineering, context management, and dialogue flow design to optimize conversational AI interactions across channels. Integrate and manage speech-to-text (STT) and text-to-speech (TTS) services for telephonic AI solutions. Agentic System Development: Design, build, and deploy AI agents that can reason, make decisions, and take actions to automate and optimize key workflows within the platform (e.g., intelligent referral initiation, proactive follow-ups, task management assistance). Develop agents capable of interacting with internal platform APIs, external data sources, and potentially third-party tools to achieve their goals. Explore and implement techniques for agent planning, tool usage, and multi-step reasoning. Collaboration & Technical Leadership: Collaborate closely with the Director of AI Engineering to define AI strategy, architecture, and technical roadmap for conversational AI and agentic systems. Partner with Product Managers to understand user needs and translate them into technical requirements for AI features. Work with platform and application engineers to integrate AI models and agents into the broader ecosystem. Mentor junior engineers and contribute to building a strong AI engineering culture. Stay up-to-date with the latest advancements in LLMs, conversational AI (text and voice), agent-based systems, and MLOps. MLOps & Productionization: Contribute to the development and maintenance of our MLOps infrastructure for training, deploying, monitoring, and iterating on AI models and agents in production. Ensure AI systems are scalable, reliable, and maintainable. Back-end Development: Solid understanding of back-end development principles and experience building or integrating with APIs (e.g., RESTful services) to connect AI models and agents with broader application systems. Familiarity with database technologies (SQL and/or NoSQL) and practical experience in how AI systems interact with data storage and retrieval for training, inference, and logging. What You'll Bring: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 5+ years of hands-on experience in AI/ML engineering, with a significant focus on Natural Language Processing (NLP) and conversational AI. Demonstrable experience developing and deploying AI-powered telephonic chatbots or Interactive Voice Response (IVR) systems, including integration with STT/TTS technologies. Proven experience fine-tuning and deploying Large Language Models (LLMs) for specific tasks and domains. Strong understanding of model architectures, training techniques, and evaluation metrics. Demonstrable experience designing and building AI agents or systems that exhibit autonomous behavior, decision-making, and/or tool usage. Proficiency in Python and common AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex). Experience with cloud platforms (GCP preferred, AWS/Azure acceptable) and their AI/ML services (e.g., Vertex AI, SageMaker, cloud telephony APIs). Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and CI/CD for ML. Skills: Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Ability to translate complex technical concepts to non-technical stakeholders. Proactive, self-starter with a passion for building impactful AI solutions. Nice to Haves: Experience working in the healthcare or social care domain. Familiarity with data privacy and security considerations in regulated environments (e.g., HIPAA). Experience with specific telephony platforms or APIs (e.g., Twilio, Vonage, Google Dialogflow CX). Contributions to open-source AI/ML projects.

Solutions Architect / Technical Lead - AI & Automation1 Key Responsibilities Solution Architecture & Development: Design end-to-end solutions using Node.JS (backend) and Vue.JS (frontend) for custom portals and administration interfaces. Integrate Azure AI services , Google OCR , and Azure OCR into client workflows. AI/ML Engineering: Develop and optimize vision-based AI models ( Layout Parsing/LP, Layout Inference/LI, Layout Transformation/LT ) using Python . Implement NLP pipelines for document extraction, classification, and data enrichment. Cloud & Database Management: Architect and optimize MongoDB databases hosted on Azure for scalability, security, and performance. Manage cloud infrastructure (Azure) for AI workloads, including containerization and serverless deployments. Technical Leadership: Lead cross-functional teams (AI engineers, DevOps, BAs) in solution delivery. Troubleshoot complex technical issues in OCR accuracy, AI model drift, or system integration. Client Enablement: Advise clients on technical best practices for scaling AI solutions. Document architectures, conduct knowledge transfers, and mentor junior engineers. Required Technical Expertise Frontend/Portal: Vue.JS (advanced components, state management), Node.JS (Express, REST/GraphQL APIs). AI/ML Stack: Python (PyTorch/TensorFlow), Azure AI (Cognitive Services, Computer Vision), NLP techniques (NER, summarization). Layout Engineering : LP/LI/LT for complex documents (invoices, contracts). OCR Technologies: Production experience with Google Vision OCR and Azure Form Recognizer . Database & Cloud: MongoDB (sharding, aggregation, indexing) hosted on Azure (Cosmos DB, Blob Storage, AKS). Infrastructure-as-Code (Terraform/Bicep), CI/CD pipelines (Azure DevOps). Experience: 10+ years in software development, including 5+ years specializing in AI/ML, OCR, or document automation . Proven track record deploying enterprise-scale solutions in cloud environments (Azure preferred). Preferred Qualifications Certifications: Azure Solutions Architect Expert , MongoDB Certified Developer , or Google Cloud AI/ML. Experience with alternative OCR tools (ABBYY, Tesseract) or AI platforms (GCP Vertex AI, AWS SageMaker). Knowledge of DocuSign CLM , Coupa , or SAP Ariba integrations. Familiarity with Kubernetes , Docker , and MLOps practices.

Company: Compunnel INC Job Location: Noida/Chandigarh Experience Required: 4+ years Mode of Work: 5 days work from the office Job Title: AI /ML Engineer We are seeking a talented and innovative Generative AI Engineer to join our team. The ideal candidate will have expertise in training and testing large language models (LLMs) for applications like speech-to-text and text-to-speech, with a focus on the Hindi language. This role requires proficiency in cutting-edge AI technologies, including transformers, GPU acceleration, and CUDA, along with strong Python programming skills. Key Responsibilities: Design, train, and fine-tune LLMs for speech-to-text and text-to-speech applications in Hindi. Develop and optimize transformer-based architectures for natural language processing (NLP) tasks. Leverage GPU acceleration and CUDA for efficient model training and deployment. Pre process and manage large datasets to ensure high-quality data for model training. Collaborate with cross-functional teams to integrate AI models into production systems. Conduct rigorous testing and evaluation of models to ensure accuracy, efficiency, and scalability. Stay updated with the latest advancements in generative AI and NLP technologies. Required Skills and Qualifications: Proficiency in Python and experience with deep learning frameworks like TensorFlow or PyTorch. Strong understanding of transformer architectures (e.g., BERT, GPT, T5). Hands-on experience with GPU acceleration and CUDA programming. Familiarity with Hindi language processing, including phonetics, grammar, and linguistic nuances. Experience in developing and deploying speech-to-text and text-to-speech systems. Knowledge of data preprocessing techniques for audio and text datasets. Strong problem-solving skills and ability to work in a collaborative environment. Preferred Qualifications: Experience with tools like Hugging Face Transformers, Kaldi, or Mozilla Deep Speech. Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) for AI model deployment. Understanding of end-to-end speech recognition and synthesis pipelines. A background in linguistics or computational linguistics is a plus. Please fill in all the essential details which are given below & attach your updated resume, and send it to ralish.sharma@compunnel.com 1. Total Experience: 2. Relevant Experience in Python : 3. Experience in Pytorch : 4. Experience in Tensorflow: 5. Experience in LLM : 6. Experience in RAG : 7. Experience in NLP : 8. Experience in GPT : 9. Experience in Bert: 10 . Experience in CUDA : 11. Current company : 12. Current Designation : 13. Highest Education : 14. Notice Period: 15. Current CTC: 16. Expected CTC: 17. Current Location: 18. Preferred Location: 19. Hometown: 20. Contact No: 21. If you have any offer from some other company, please mention the Offer amount and Offer Location: 22. Reason for looking for change: If the job description is suitable for you, please get in touch with me at the number below: 9910044363 .

Job Summary: We are seeking a passionate and skilled AI Engineer to design, develop, and deploy cutting-edge AI solutions across domains such as large language models (LLMs), computer vision, and autonomous agent workflows. You will collaborate with data scientists, researchers, and engineering teams to build intelligent systems that solve real-world problems using deep learning, transformer-based architectures, and multi-modal AI models. Key Responsibilities: Design and implement AI/ML models, especially transformer-based LLMs (e.g., BERT, GPT, LLaMA) and vision models (e.g., ViT, YOLO, Detectron2). Develop and deploy computer vision pipelines for object detection, segmentation, OCR, and image classification tasks. Build and orchestrate intelligent agent workflows using prompt engineering, memory systems, retrieval-augmented generation (RAG), and multi-agent coordination. Fine-tune and optimize pre-trained models on domain-specific datasets using frameworks like PyTorch or TensorFlow. Collaborate with cross-functional teams to understand problem requirements and translate them into scalable AI solutions. Implement inference pipelines and APIs to serve AI models efficiently using tools such as FastAPI, ONNX, or Triton Inference Server. Conduct model evaluation, benchmarking, A/B testing, and performance tuning. Stay updated with state-of-the-art research in deep learning, generative AI, and multi-modal learning. Ensure reproducibility, versioning, and documentation of all experiments and production models. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 35 years of hands-on experience in designing and deploying deep learning models. Strong knowledge of LLMs (e.g., GPT, BERT, T5), Vision Models (e.g., CNNs, Vision Transformers), and Computer Vision techniques. Experience building intelligent agents or using frameworks like LangChain, Haystack, AutoGPT, or similar. Proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Scikit-learn. Familiarity with MLOps concepts and deployment tools (Docker, Kubernetes, MLflow). Strong understanding of NLP, image processing, model fine-tuning, and optimization. Experience with cloud platforms (AWS, GCP, Azure) and GPU environments. Excellent problem-solving, communication, and teamwork skills. Preferred Qualifications: Experience in building multi-modal AI systems (e.g., combining vision + language models). Exposure to real-time inference systems and low-latency model deployment. Contributions to open-source AI projects or research publications. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Job Summary: We are seeking a highly skilled and hands-on AI Engineer with 3+ years of proven experience in building and deploying solutions using Generative AI and Large Language Models (LLMs). You will work on cutting-edge applications leveraging transformer-based architectures, fine-tuning, prompt engineering, and scalable AI deployments. This role is ideal for engineers passionate about AI research and real-world productization of generative AI technologies. Key Responsibilities: Design, develop, and deploy solutions using LLMs (e.g., GPT, LLaMA, Mistral, Claude, PaLM, etc.) for various NLP and content generation tasks. Work on fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) pipelines. Integrate LLMs into enterprise applications with APIs and orchestrate workflows using Python, LangChain, or similar frameworks. Optimize model performance, latency, and cost for production use. Collaborate with data scientists, MLOps engineers, and product managers to deliver scalable AI features. Conduct experiments, analyze results, and publish internal findings or contribute to whitepapers. Ensure ethical, secure, and responsible use of AI technologies in all implementations. Required Skills & Experience: 3+ years of hands-on experience working with Generative AI, LLMs, and NLP technologies. Strong programming skills in Python and experience with libraries like Transformers (Hugging Face), LangChain, PyTorch, TensorFlow, etc. Proven track record of fine-tuning LLMs, developing embeddings, and working with vector databases (e.g., FAISS, Pinecone, Weaviate). Experience deploying models on cloud platforms (AWS, Azure, GCP) and using ML pipelines or MLOps tools. Solid understanding of deep learning, NLP architectures, tokenization, and evaluation metrics for generative models. Experience in API development and integration of LLMs into user-facing applications. Preferred Qualifications: Masters or PhD in Computer Science, AI/ML, Data Science, or related field. Experience with OpenAI APIs, Anthropic, Cohere, or open-source LLMs (e.g., Mistral, Falcon, LLaMA 3). Understanding of RLHF (Reinforcement Learning from Human Feedback) and model alignment techniques. Contributions to open-source AI projects or publications in GenAI/LLM.

Job Description Develop fit for purpose AIML models/algorithms/processes to address pharma/healthcare applications and innovative products upon completion of prototypes followed by the building of production grade algorithms/automation engines for client deliverables. Test for viability in order to deliver final products to clients. Able to bring newly researched ideas to reality quickly and on a large scale. Design, build, test, and deliver products from post-prototype to client delivery. Essential Functions Assists with the ongoing development and implementation of an enterprise architecture. May devise and present business cases and program release plans to senior management with priority recommendations to maintain and evolve this architecture. Builds effective business relationships with business line managers and provides technical and system expertise as input to product concepts. May assist product development management to define IT strategic direction and assists in the mapping of projects to that strategic direction whilst ensuring product capabilities and process improvements are delivered over time within the framework of the IQVIA enterprise architecture. Participates in cross-functional product development teams, may also act as a consultant to provide system and technical advice. Keeps up to date with technology changes and identifies opportunities for implementation in future systems. Participates in R&D projects and may run those projects in compliance with standard project management practices. May mentor and assist lower level architects and business analysts Qualifications 10+ years of experience in engineering roles with team management experience 5-7 relevant years experience on NLP, Machine Learning and Deep learning 5-7 relevant years of experience on Python Extensively work on NLP applications, ability to work on Machine learning model, Deep learning development Knowledge of LLMs, fine tuning and deployment Experience annotated datasets for Supervised Learning methods and correction Experience on text to transform natural language into useful features Find and implement the right algorithms and tools for NLP tasks Perform statistical analysis of results and refine models Extend ML libraries and frameworks to apply in NLP tasks Experience on ORM, SQL Alchemy, Alembic is a must Experience on Writing on effective and scalable code Experience on Unit Testing using Pytest or equivalent framework A deep understanding and multi-process architecture and the threading limitations of Python. Familiarity with server-side templating languages including Jinja 2 and Mako is good to have Experience on REST API, Flask API, Fast API is must, Django or Pyramid framework is good to have Knowledge of NER, Knowledge graphs is good to have Education Qualification Master's Degree Masters Degree in Machine Learning, Statistics, Computer Science, Physics, Math, or related field

Job Description With excellent analytical and problem-solving skills, you should understand business problems of the customers, translate them into scope of work and technical specifications for developing into Data Science projects. Efficiently utilize cutting edge technologies in AI, Generative AI areas and implement solutions for business problems. Good exposure technology platforms for Data Science, AI, Gen AI, cloud with implementation experience. Ability to provide end to end technical solutions leveraging latest AI, Gen AI tools, frameworks for the business problems. This Job requires the following: Designing, developing, and implementing end-to-end machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation) Deep experience in predictive analytics and statistical modeling Deep experience in successfully making use of the following: Logistic Regression Multivariate Regression, Support Vector Machines, Stochastic Processes, Decision Trees, Lifetime analysis, common clustering algorithms, Optimization, CNN Essential Qualifications B-Tech or BE - computer / IT or MCA or MSC- Computer Science along with necessary certifications is preferred Technical Qualifications (Essential) At least 2 to 3 ML apps deployed in production At least 1 to 2 Gen AI apps in production. Experience in Computer vision is a must. Core ML experience is a must Hands-on programming experience Hands-on technical design experience Hands-on prompt engineering experience At least 3 Data Science, AI Projects designed, developed and delivered to production At least 1 Generative AI Project designed, developed and delivered to production Primary Skills Hands-on coding experience in Python, PyTorch, Spark/PySpark, SQL, TensorFlow, NLP Frameworks and similar tools/frameworks Good understanding of business and domain of the applications Hands-on experience in design and development of Gen AI applications using Open Source LLMs and cloud platforms Hands-on experience in design and development of API based applications for AI and Data Science Projects Expertise in GenAI concepts, RAG and Models fine-tuning techniques Understand the concepts of major AI models such as OpenAI, Llama, Hugging Face, Mistral AI etc., and implementation experience Understanding of DevOps pipelines for deployment Good understanding of Data Engineering lifecycle data pipelines, data warehouse, data lake Secondary Skills End to end data engineering project experience using Databricks and Azure Data platform Knowledge of any configuration management tools is desirable Familiarity with containerization and container orchestration services like Docker and Kubernetes Description of Responsibility Sills / Competencies requirement Functional & Technical Responsibilities Understand customers requirements (Business, Functional, Non-Functional etc.,), conduct feasibility study and develop technical specifications for Data Science, AI and Gen AI Projects Design and implement scalable solutions for Data Science, AI and Gen AI Projects using major technology and computing platforms (open source and cloud) Possess excellent analytical and problem-solving skills and be able to understand various forms of data, patterns and derive insights. Should be able to develop efficient Prompts to automate project activities using LLM tools and provide end to end solutions Provide Generative AI solutions for the business/automation requirements using open source LLMs (Open AI, Llama, Mistral etc.,) Collaborate internal and external stakeholders for deriving solution that requires cross functional teams and smoother execution of the projects Provide technical solutions to sales, pre-sales teams for the proposals Develop and guide team members in implementation of solutions related to Data Science, AI and Gen AI Projects Expert knowledge of data modeling and understanding of different data structures Experience with design of AI/ML solutions either as standalone or integrated with other applications Research Orientation Proactive & Clear Communication Collaboration Solution Orientation Solution Articulation Accountability Adaptability / Flexibility Analytical Skills Listening Skills Customer Service Orientation

Seniority : Senior Description & Requirements Position Summary The Senior AI Engineer with GenAI expertise is responsible for developing advanced technical solutions, integrating cutting-edge generative AI technologies. This role requires a deep understanding of modern technical and cloud-native practices, AI, DevOps, and machine learning technologies, particularly in generative models. You will support a wide range of customers through the Ideation to MVP journey, showcasing leadership and decision-making abilities while tackling complex challenges. Key Responsibilities Technical & Engineering Leadership Develop solutions leveraging GenAI technologies, integrating advanced AI capabilities into cloud-native architectures to enhance system functionality and scalability. Lead the design and implementation of GenAI-driven applications, ensuring seamless integration with microservices and container-based environments. Create solutions that fully leverage the capabilities of modern microservice and container-based environments running in public, private, and hybrid clouds. Contribute to HCL thought leadership across the Cloud Native domain with an expert understanding of open-source technologies (e.g., Kubernetes/CNCF) and partner technologies. Collaborate on joint technical projects with partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware. Service Delivery Engineer innovative GenAI solutions from ideation to MVP, ensuring high performance and reliability within cloud-native frameworks. Optimize AI models for deployment in cloud environments, balancing efficiency and effectiveness to meet client requirements and industry standards. Assess existing complex solutions and recommend appropriate technical treatments to transform applications with cloud-native/12-factor characteristics. Refactor existing solutions to implement a microservices-based architecture. Innovation & Initiative Drive the adoption of cutting-edge GenAI technologies within cloud-native projects, spearheading initiatives that push the boundaries of AI integration in cloud services. Engage in technical innovation and support HCLs position as an industry leader. Author whitepapers, blogs, and speak at industry events. Maintain hands-on technical credibility, stay ahead of industry trends, and mentor others. Client Relationships Provide expert guidance to clients on incorporating GenAI and machine learning into their cloud-native systems, ensuring best practices and strategic alignment with business goals. Conduct workshops and briefings to educate clients on the benefits and applications of GenAI, establishing strong, trust-based relationships. Perform a trusted advisor role, contributing to technical projects (PoCs and MVPs) with a strong focus on technical excellence and on-time delivery. Mandatory Skills & Experience A passionate developer with 10+ years of experience in Java, Python, Node.js, and Spring programming, comfortable working as part of a paired/balanced team. Extensive experience in software development, with significant exposure to AI/ML technologies. Expertise in GenAI frameworks: Proficient in using GenAI frameworks and libraries such as LangChain, OpenAI API, Gemini, and Hugging Face Transformers. Prompt engineering: Experience in designing and optimizing prompts for various AI models to achieve desired outputs and improve model performance. Strong understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models. Proven experience developing complex solutions that leverage cloud-native technologiesfeaturing container-based, microservices-based approaches; based on applying 12-factor principles to application engineering. Exemplary verbal and written communication skills (English). Positive and solution-oriented mindset. Solid experience delivering Agile and Scrum projects in a Jira-based project management environment. Proven leadership skills and the ability to inspire and manage teams. Desired Skills & Experience Machine Learning Operations (MLOps): Experience in deploying, monitoring, and maintaining AI models in production environments using MLOps practices. Data engineering for AI: Skilled in data preprocessing, feature engineering, and creating pipelines to feed AI models with high-quality data. AI model fine-tuning: Proficiency in fine-tuning pre-trained models on specific datasets to improve performance for specialized tasks. AI ethics and bias mitigation: Knowledgeable about ethical considerations in AI and experienced in implementing strategies to mitigate bias in AI models. Knowledgeable about vector databases, LLMs, and SMLs, and integrating with such models. Proficient with Kubernetes and other cloud-native technologies, including experience with commercial Kubernetes distributions (e.g., Red Hat OpenShift, VMware Tanzu, Google Anthos, Azure AKS, Amazon EKS, Google GKE). Deep understanding of core practices including DevOps, SRE, Agile, Scrum, XP, Domain-Driven Design, and familiarity with the CNCF open-source community. Recognized with multiple cloud and technical certifications at a professional level, ideally including AI/ML specializations from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat. Verifiable Certification At least one recognized cloud professional / developer certification (AWS/Google/Microsoft)

Job Summary We are seeking a highly skilled Generative AI Data Scientist to design, develop, and deploy generative AI applications and models that can generate meaningful insights, creative business domain content, or solve domain-specific challenges. The ideal candidate will combine expertise in data science, machine learning, AI and natural language processing (NLP) with a passion for innovation and real-world applications. As part of the EXL Digital AI R&D Innovation team, you will work as a Data Scientist in the Innovation unit supporting all EXL Business Units. You will be exposed to hundreds of different enterprise GenAI business use cases and help our clients create value architecting GenAI applications and solutions. This role involves working on cutting-edge Generative AI technologies to drive significant revenue growth, operational efficiencies, and enhanced customer experiences for our Fortune 1000 enterprise clients across various industries in insurance, healthcare, banking & financial services, media, and retail. You will work with a team of talented data scientists, AI researchers, software engineers, ML engineers, project managers and delivery managers helping them in deploying advanced AI technologies. Youll work with domain-specific data, design models and AI systems & architectures at scale, design RAG pipelines, improve AI Governance and responsible, LLM selection(GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) & fine-tuning PEFT LoRa/QLoRa adapters, LLM Prompt Engineering, Agentic AI, AutoGen, AI Autonomous Agents, Multimodal LLMs and LLM orchestration architectures for enterprise data at scale in Python. Key Responsibilities Model Development: Research, design, and develop state-of-the-art generative models such as GPT, GANs, VAEs, or diffusion models for tasks like text generation, summarization, reasoning, Q&A, or predictive analytics. Fine-Tuning: Fine-tune pre-trained models (e.g., Llama3, Mistral, OpenAI GPT, BERT, T5) to meet domain-specific requirements. Data Preparation: Clean, preprocess, and structure large datasets to train, validate, and test generative AI models. Deployment: Implement scalable solutions for deploying generative AI models in production environments using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). Collaboration: Work closely with cross-functional teams, including product managers, engineers, and stakeholders, to align AI solutions with business goals. Evaluation: Develop metrics and benchmarks to evaluate model performance and ensure quality outputs. Research: Stay up to date with the latest advancements in AI/ML, particularly in generative AI techniques, and propose innovative solutions. Ethical AI Practices: Ensure ethical considerations are addressed in model development, including fairness, accountability, and explainability. Experience of architecting AI systems to solve complex business problems. Build advanced RAG pipelines, text chunking, and retrieval, LLM Prompt Engineering, using Vector Databases. Implement right LLM selection based on use cases and client criteria (GPT-4, Llama2, Mistral, Claude, Gemini, Flan, BERT) while managing trifecta of accuracy, cost, and latency/scale. Develop, fine-tune, context tune and implement state-of-the-art NLP models including Large Language Models like GPT, Llama3.1, Claude, BLOOM, Flan-T5, Falcon etc. fine-tuning PEFT LoRa/QLoRa adapters design AI systems & architectures, while considering good Responsible AI standards and AI Governance. Build Agentic AI, AutoGen, Muti-agents use cases, AI Autonomous Agents and LLM orchestration architectures for enterprise data at scale in Python. Hands on experience with complementary technologies around LLMs like embedders, vector databases (chroma, weaviate etc.), orchestration tools like Langchain, LlamaIndex etc. Conduct research and experimentation to improve existing models and propose novel approaches. Collaborate with cross-functional teams to integrate generative AI solutions into real-world applications. Stay up-to-date with the latest advancements in deep learning and generative models and apply them to enhance our AI capabilities. Document research findings, prepare technical reports, and contribute to whitepaper/scientific publications. Provide deep leadership and coaching in the project delivery lifecycle. Focus on shared learning, continuous improvement, and drive adoption of best practices. Qualifications Education and Experience: Masters of Science or PhD in computer science, data science, statistics, Natural Language Processing 2-3 years of experience in GenAI and Large Language Models. Strong programming skills in Python, including experience with libraries like TensorFlow, PyTorch, Hugging Face Transformers, or similar. as evidenced by released code (e.g., GitHub repositories – version control awareness). Solid understanding of optimization techniques for training deep neural networks, regularization methods, and hyperparameter/fine tuning. Hands-on experience with generative AI models, such as Llama3, GPT4, Claude Knowledge of NLP, computer vision, or multimodal AI techniques. Proficiency in data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Experience in Generative AI Models and LLMs, finetuning LLMs, prompt engineering and experience with LLM orchestration frameworks like Langchain, LlamaIndex, RAGAS, etc. Strong software engineering skills for rapid and accurate development of AI models and systems. Understanding of Agentic AI, Autonomous Agents, AI Agents, AutoGen, Crew.ai, Langchain, and workflow steps design. NVIDIA Blueprints. Google AI Agents. Provide business-oriented solution with ability to communicate effectively, both verbally and in writing, with technical and non-technical stakeholders. Experience working in a collaborative environment, contributing to multidisciplinary teams and projects. Proven ability to solve complex problems, think creatively, and adapt to evolving research trends. Experience in deploying ML models in cloud environments (AWS SageMaker, GCP AI Platform, or Azure ML). Strong problem-solving and analytical skills. Excellent communication skills, both technical and non-technical. Skills and Competencies: 5 years of experience in AI, NLP including transformer architecture and LLMs, Computer Vision and related technologies Excellent communication and problem-solving skills. Working with cross-functional teams across different stakeholders. Ability to explain GenAI to non-technical audiences across many different industries. Ability to do GenAI Architecture solutioning for existing clients and potential clients. People leadership skills. Candidate is also hands on developer while people managing Data Scientists, ML Engineers etc. Experience in ML Engineering and MLOps, MLFlow Strong understanding of statistical and machine learning concepts Experience with deep learning frameworks such as TensorFlow and PyTorch Familiarity with key concepts and techniques used in generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models. Strong programming skills in languages such as Python, along with experience working with popular deep learning frameworks like PyTorch and TensorFlow. Understanding of Graph Database and/or Vector Database along with knowledge of cloud services (e.g., AWS, Azure, GCP). Experience with deploying AI models in production environments. Familiarity with domain-specific applications of generative AI Leveraged both Azure and AWS for model inferencing. For finetuning, he has worked more on AWS SageMaker. Has used different retrieval, reranking, and generation techniques based on the use case complexity and the metrics required. Has played multiple roles in the past, such as an individual contributor, a solution architect, a mentor, a trainer, and a people manager. He also participates in RFI, RFP, thought leadership, and business development activities. ole & responsibilities Preferred candidate profile Perks and benefits

Role & responsibilities : Requirements: Strong expertise in NLP, text summarization, semantic search, and LLM APIs. Practical experience with Amazon Bedrock, OpenAI, or Hugging Face transformers. Familiar with prompt tuning and few-shot learning. Python (pandas, langchain, boto3, NumPy, etc.) Experience working with unstructured audio-to-text data (e.g., call transcripts). Key Responsibilities: Design and Development: Design, develop, and deploy LLM-based solutions for text summarization, semantic search, and other NLP tasks LLM APIs: Integrate LLM APIs from Amazon Bedrock, OpenAI, or Hugging Face transformers into existing applications Prompt Tuning and Few-Shot Learning: Implement prompt tuning and few-shot learning techniques to improve LLM performance Unstructured Audio-to-Text Data: Work with unstructured audio-to-text data, such as call transcripts, to develop accurate and efficient NLP models Python Programming: Utilize Python libraries like pandas, LangChain, boto3, and NumPy for data processing and model development Preferred candidate profile : We're seeking a highly skilled NLP Engineer with expertise in Large Language Models (LLMs) and text summarization to join our team. The ideal candidate will have hands-on experience with Amazon Bedrock, OpenAI, or Hugging Face transformers and a strong background in Python programming. This role involves working with unstructured audio-to-text data, such as call transcripts, and developing innovative solutions using LLMs.

What You'll Do We are looking for experienced Machine Learning Engineers with a background in software development and a deep enthusiasm for solving complex problems. You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara. Your responsibilities will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features. You will build core agent infrastructureA2A orchestration and MCP-driven tool discoveryso teams can launch secure, scalable agent workflows. You will be reporting to Senior Manager, Machine Learning What Your Responsibilities Will Be We are looking for engineers who can think quick and have a background in implementation. Your responsibilities will include: Build on top of the foundational framework for supporting Large Language Model Applications at Avalara Experience with LLMs - like GPT, Claude, LLama and other Bedrock models Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place. Promote innovation by researching and applying the latest technologies and methodologies in machine learning and software development. Write, review, and maintain high-quality code that meets industry standards, contributing to the project's. Lead code review sessions, ensuring good code quality and documentation. Mentor junior engineers, encouraging a culture of collaboration Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful 6+ years of experience building Machine Learning models and deploying them in production environments as part of creating solutions to complex customer problems. Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices. Experience working with technological innovations in AI & ML(esp. GenAI) and apply them. Experience with design patterns and data structures. Good analytical, design and debugging skills. Technologies you will work with: Python, LLMs, Agents, A2A, MCP, MLFlow, Docker, Kubernetes, Terraform, AWS, GitLab, Postgres, Prometheus, and Grafana.

What You'll Do We are looking for experienced Machine Learning Engineers with a background in software development and a deep enthusiasm for solving complex problems. You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara. Your responsibilities will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features. You will have a blend of technical skills in the fields of AI & Machine Learning especially with LLMs and a deep-seated understanding of software development practices where you'll work with a team to ensure our systems are scalable, performant and accurate. You will be reporting to Senior Manager, AI/ML. What Your Responsibilities Will Be We are looking for engineers who can think quick and have a background in implementation. Your responsibilities will include: Build on top of the foundational framework for supporting Large Language Model Applications at Avalara Experience with LLMs - like GPT, Claude, LLama and other Bedrock models Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place. Inspire creativity by researching and applying the latest technologies and methodologies in machine learning and software development. Write, review, and maintain high-quality code that meets industry standards. Lead code review sessions, ensuring good code quality and documentation. Mentor junior engineers, encouraging a culture of collaboration. Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful Bachelor's/Master's degree in computer science with 5+ years of industry experience in software development, along with experience building Machine Learning models and deploying them in production environments. Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices. Work with technological innovations in AI & ML(esp. GenAI) Experience with design patterns and data structures. Good analytical, design and debugging skills. Technologies you will work with: Python, LLMs, MLFlow, Docker, Kubernetes, Terraform, AWS, GitLab, Postgres, Prometheus, Grafana

Position Summary LLMOps(Large language model operations) Engineer will play a pivotal role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, establishing efficient and scalable systems for LLM research, evaluation, training, and fine-tuning. Engineer will be responsible for managing and optimizing large language models (LLMs) across various platforms This position is uniquely tailored for those who excel in crafting pipelines, cloud infrastructure, environments, and workflows. Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models and associated platform. LLMOps engineers expertise will ensure the smooth deployment, maintenance, and performance of these AI platforms and powerful large language models. You will follow Site Reliability Engineering & MLOps principles and will be encouraged to contribute your own best practices and ideas to our ways of working. Reporting to the Head of Cloud Native operations, you will be an experienced thought leader, and comfortable engaging senior managers and technologists. You will engage with clients, display technical leadership, and guide the creation of efficient and complex products/solutions. Key Responsibilities Technical & Architectural Leadership Contribute to the technical delivery of projects, ensuring a high quality of work that adheres to best practices, brings innovative approaches and meets client expectations. Project types include following (but not limited to): Solution architecture, Proof of concepts (PoCs), MVP, design, develop, and implementation of ML/LLM pipelines for generative AI models, data management & preparation for fine tuning, training, deployment, and monitoring. Automate ML tasks across the model lifecycle. Contribute to HCL thought leadership across the Cloud Native domain with an expert understanding of advanced AI solutions using Large Language Models (LLM) & Natural Language Processing (NLP) techniques and partner technologies. Collaborate with cross-functional teams to integrate LLM and NLP technologies into existing systems. Ensure the highest levels of governance and compliance are maintained in all ML and LLM operations. Stay abreast of the latest developments in ML and LLM technologies and methodologies, integrating these innovations to enhance operational efficiency and model effectiveness. Collaborate with global peers from partner ecosystems on joint technical projects. This partner ecosystem includes Google, Microsoft, Nvidia, AWS, IBM, Red Hat, Intel, Cisco, and Dell VMware etc. Service Delivery Provide a technical hands-on contribution. Create scalable infra to support enterprise loads (distributed GPU compute, foundation models, orchestrating across multiple cloud vendors, etc.) Ensuring the reliable and efficient platform operations. Apply data science, machine learning, deep learning, and natural language processing methods to analyse, process, and improve the models data and performance. Understanding of Explainability & Biased Detection concepts. Create and optimize prompts and queries for retrieval augmented generation and prompt engineering techniques to enhance the models capabilities and user experience w.r.t Operations & associated platforms. Client-facing influence and guidance, engaging in consultative client discussions and performing a Trusted Advisor role. Provide effective support to HCL Sales and Delivery teams. Support sales pursuits and enable HCL revenue growth. Define the modernization strategy for client platform and associated IT practices, create solution architecture and provide oversight of the client journey. Innovation & Initiative Always maintain hands-on technical credibility, keep in front of the industry, and be prepared to show and lead the way forward to others. Engage in technical innovation and support HCLs position as an industry leader. Actively contribute to HCL sponsorship of leading industry bodies such as the CNCF and Linux Foundation. Contribute to thought leadership by writing Whitepapers, blogs, and speaking at industry events. Be a trusted, knowledgeable internal innovator driving success across our global workforce. Client Relationships Advise on best practices related to platform & Operations engineering and cloud native operations, run client briefings and workshops, and engage technical leaders in a strategic dialogue. Develop and maintain strong relationships with client stakeholders. Perform a Trusted Advisor role. Contribute to technical projects with a strong focus on technical excellence and on-time delivery. Mandatory Skills & Experience Expertise in designing and optimizing machine-learning operations, with a preference for LLMOps. 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, worked 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, Jenkins. Experience with the GitHub/DevOps Lifecycle Experience in at least one of the 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; masters degree desired. Experience in LLMOps 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 (e.g., 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 models 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 environment using the latest technologies, love Labs dynamic and high-energy atmosphere, and want to build your career with an industry leader.

Primary skill Gen AI developer Secondary skill Model hosting LLM knowledge. Ability to stay updated with the latest advancements in generative AI research and incorporate them into work. -Advanced programming knowledge, including mastery of programming languages such as Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. -Expertise in generative models such as generative adversarial networks (GANs) and variational autoencoders (VAEs). The candidate should be able to design, train, and optimize these models to generate high-quality, creative content. -Natural language processing (NLP) for text generation projects. This includes familiarity with techniques for text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. -Model hosting LLM knowledge -Ability to design and implement scalable and efficient AI systems. -Advanced knowledge of natural language processing for text generation tasks. -Familiarity with computer vision and image generation using AI. Akshay : Ignore -Skills in data preprocessing and feature engineering for AI model training. -Strong understanding of neural network architectures and optimization techniques.

What you will do In this vital role you will be a Senior Manager BI & Visualization to lead and drive enterprise-wide business intelligence (BI) and data visualization initiatives. This role will be responsible for strategic planning, governance, and execution of BI and analytics solutions, ensuring that business leaders have access to actionable insights through advanced reporting and visualization platforms. The ideal candidate will have a deep understanding of BI tools, data visualization best practices, self-service BI enablement, and enterprise analytics strategy, working closely with business executives, data teams, and technology leaders to foster a data-driven culture. Develop and execute a strategic BI & visualization roadmap, aligning with business goals, analytics objectives, and digital transformation strategies. Lead and mentor BI, analytics, and visualization teams, fostering a culture of innovation, collaboration, and continuous learning. Own the end-to-end BI lifecycle, including data modeling, dashboard development, analytics governance, and self-service BI adoption. Oversee the implementation of modern BI solutions, leveraging tools like Power BI, Tableau, Looker, Qlik Sense, or similar to deliver high-impact visual insights. Define and enforce data visualization best practices, ensuring dashboards are intuitive, user-friendly, and business-focused. Drive self-service BI enablement, empowering business users to explore, analyze, and act on data independently while maintaining data security and governance. Collaborate with business leaders, data scientists, and engineering teams to identify and prioritize high-value analytics use cases. Optimize BI infrastructure and reporting architecture, ensuring scalability, performance, and cost efficiency. Establish BI governance frameworks, defining data access controls, security policies, KPI standardization, and metadata management. Champion the use of AI/ML-powered BI solutions, enabling predictive analytics, anomaly detection, and natural language-driven insights. Monitor BI performance metrics, ensuring reporting solutions meet business SLAs, operational efficiency, and data accuracy. Stay ahead of emerging trends in BI, data visualization, and analytics automation, ensuring the company remains competitive in its data strategy. What we expect of you Masters degree and 8 to 10 years of experience in Computer Science, IT or related field OR Bachelors degree and 10 to 14 years of experience in Computer Science, IT or related field OR Diploma and 14 to 18 years of experience in Computer Science, IT or related field. Certifications on PowerBI / Any other visualization tools Basic Qualifications: 10-14 + years of experience in BI, analytics, and data visualization, with at least 5 years in a leadership role. Expertise in BI tools, including Power BI, Tableau, Looker, Qlik Sense similar enterprise BI platforms. Strong proficiency in data visualization principles, storytelling with data, and dashboard usability best practices. Experience in leading large-scale BI transformation initiatives, driving self-service analytics adoption across an enterprise. Strong knowledge of data modeling, dimensional modeling (star/snowflake schema), and data warehousing concepts. Hands-on experience with SQL, DAX, Power Query (M), or other analytics scripting languages. Strong background in BI governance, data security, compliance, and metadata management. Ability to influence senior leadership, communicate insights effectively, and drive business impact through BI. Excellent problem-solving skills, with a track record of driving efficiency, automation, and data-driven decision-making. Preferred Qualifications: Experience in Biotechnology or pharma industry is a big plus Experience with Data Mesh, Data Fabric, or Federated Data Governance models. Experience with AI/ML-driven BI solutions, predictive analytics, and NLP-based BI capabilities. Knowledge infrastructure & deploayment automation for visualization platforms. Experience integrating BI with ERP, CRM, and operational systems (SAP, Salesforce, Oracle, Workday, etc.). Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for BI project delivery. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills.

What you will do We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. Roles & Responsibilities: Collaborate with data scientists to develop, train, and evaluate machine learning models. Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring. Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment. Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency. Develop and implement monitoring systems to track model performance and identify issues. Conduct A/B testing and experimentation to optimize model performance. Work closely with data scientists, engineers, and product teams to deliver ML solutions. Guide and mentor junior engineers in the team Stay updated with the latest trends and advancements Basic Qualifications: Doctorate degree and 2 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Masters degree and 8 to 10 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Bachelors degree and 10 to 14 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Diploma and 14 to 18 years of years of Computer Science, Statistics, and Data Science, Machine Learning experience Preferred Qualifications: Must-Have Skills: Strong foundation in machine learning algorithms and techniques Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD) Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills Good-to-Have Skills: Experience with big data technologies (e.g., Spark), and performance tuning in query and data processing Experience with data engineering and pipeline development Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification Knowledge of NLP techniques for text analysis and sentiment analysis Experience in analyzing time-series data for forecasting and trend analysis Familiar with AWS, Azure, or Google Cloud; Familiar with Databricks platform for data analytics and MLOps Professional Certifications Cloud Computing and Databricks certificate preferred Soft Skills: Excellent analytical and fixing skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills.

Hello, Urgent job openings for Data Science Manager role @ GlobalData(Hyd). Job Description given below please go through to understand the requirement. if requirement is matching to your profile & interested to apply please share your updated resume @ mail id (m.salim@globaldata.com). Mention Subject Line :- Applying for Data Science Manager @ GlobalData(Hyd) Share your details in the mail :- Full Name : Mobile # : Qualification : Company Name : Designation : Total Work Experience Years : Current CTC : Expected CTC : Notice Period : Current Location/willing to relocate to Hyd? : Office Address : 3rd Floor, Jyoti Pinnacle Building, Opp to Prestige IVY League Appt, Kondapur Road, Hyderabad, Telangana-500081. Job Description :- About the Role We are seeking an experienced Data Science Manager to lead our data science team in transforming complex data into actionable business insights. The ideal candidate will combine strong technical expertise with leadership skills to guide a team of data scientists while collaborating with cross-functional stakeholders to drive data-informed decision making throughout the organization. Key Responsibilities Lead and mentor a team of 5-8 data scientists, providing technical guidance and career development Develop and implement the organization's data science strategy and roadmap in alignment with business objectives Oversee the full lifecycle of data science projects from conception to deployment Establish best practices, methodologies and standards for data science processes Drive the development of machine learning models, predictive analytics, and other advanced analytical solutions Collaborate with business leaders to identify opportunities for data-driven improvements Translate complex technical concepts into clear insights for non-technical stakeholders Ensure data quality, integrity, and proper governance in all data science initiatives Stay current with emerging technologies and methodologies in data science and AI Manage project timelines, resources, and budgets to ensure timely delivery of solutions Qualifications Master's degree or PhD in Computer Science, Statistics, Mathematics, or related quantitative field 7+ years of experience in data science or related analytical roles 5+ years of experience managing data science teams and projects Strong programming skills in Python, R, or similar languages Expertise in machine learning algorithms, statistical analysis, and data mining techniques Experience with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP) Proven track record of delivering impactful data science solutions that drive business value Excellent communication and presentation skills with ability to translate technical concepts for business audiences Strong project management and organizational abilities Business acumen with understanding of how data science can drive organizational success Preferred Qualifications Experience in our industry sector Knowledge of data visualization tools (Tableau, Power BI) Familiarity with MLOps and model deployment Experience implementing NLP or computer vision solutions Agile/Scrum certification or experience Thanks & Regards, Salim (Human Resources)

Hi Immediate opening for Data Scientist Lead Location : Ahmedabad ( Onsite only ) Experience : 6 + years Job Description : Key Skills : Advanced degree or Masters degree in machine learning/data science/computer science or a related field Proven experience in developing and deploying machine learning models in a healthcare or RCM setting Strong programming skills in languages like Python or R Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Deep understanding of healthcare data and industry-specific challenges Strong problem-solving and analytical abilities Excellent leadership and team management skills Effective communication and stakeholder management skills Experience in MLOps, containerization, CI/CD pipeline is a plus Role & responsibilities: Engage with business and product teams to identify and flesh out ML use-cases Responsible for identifying needs, ingestion, quality and value evaluation, distillation & analysis of both structured and unstructured data from multiple sources Researching solutions to overcome machine learning challenges Managing and mentoring a team of ML engineers work allocation and planning, problem solving, tactical problem solving and thought leadership Leading development and optimization of machine learning and deep learning models Customizing models and build on top of existing framework to address client specific requirements Creating assets to fast-track solution development Staying informed about latest developments in Data Science / AI field Candidates serving notice / Early Immediate joiners can share updated CV on anand.rawal@agshealth.com

Job Title: Full Stack Developer AI Integration & Prompt Engineering Employment type: Full Time About the Role: Were looking for a talented Full Stack Developer with strong JavaScript skills and hands-on experience integrating AI models like ChatGPT into web applications. If you’re passionate about AI, prompt engineering , and building intelligent, responsive web apps, this is the perfect opportunity. Key Responsibilities Build and maintain web applications using JavaScript frameworks (React.js, Node.js, Vue.js). Integrate AI/ML models and APIs (e.g., OpenAI) into scalable web applications. Design, test, and refine effective prompts to drive accurate and meaningful AI responses. Create smooth and responsive AI-driven user experiences , including chat interfaces. Optimize application performance, ensuring high responsiveness and scalability. Experiment with different prompting strategies to improve AI performance and user interaction. Collaborate closely with AI engineers, UI/UX designers, and backend developers to deliver cohesive features. Stay updated on the latest trends in AI/ML, NLP, and JavaScript frameworks . What We’re Looking For Strong experience with JavaScript, React, Redux, and TypeScript Proven ability to integrate AI APIs (e.g., OpenAI, GPT models) Hands-on experience in prompt engineering and AI model tuning Good understanding of Vector Search and AI application workflows Excellent English communication skills , both verbal and written Familiarity with frontend and backend web development best practices Why Join Us? Be at the forefront of AI innovation in real-world applications Work on exciting projects that merge web technology and artificial intelligence Collaborate with a passionate, forward-thinking team Role & responsibilities

The Role Machine learning and data science are interdisciplinary fields that require a combination of skills in mathematics, statistics, programming, and domain-specific knowledge to extract meaningful insights from data and develop predictive models. Skills Requirements Mandatory Skillset - ML Techniques, any ML Framework, Gen AI COncepts, Azure, Python Secondary Skillset - AWS, or Google Cloud Requirements Work closely with cross-functional teams to understand business requirements and translate them into machine learning solutions. Collect, clean, and pre-process large datasets to prepare them for machine learning models. Develop and implement machine learning algorithms and models for solving specific business problems. Collaborate with data engineers to ensure seamless integration of machine learning models into production systems. Fine-tune models for optimal performance and conduct thorough testing and validation. Stay updated on the latest advancements in machine learning and artificial intelligence and assess their potential impact on our projects. Effectively communicate complex technical concepts and findings to non-technical stakeholders. Monitor and maintain deployed models and update them as needed to adapt to changes in data or business requirements. Adhere to ethical standards and ensure that machine learning solutions comply with relevant regulations. Proficiency in Python with hands-on experience in cloud platforms including GCP, AWS, and Azure; strong skills in API integration.

Key Responsibilities: Design and Development: Design, architect, and deploy AI/GenAI models and solutions using various technologies and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum etc) on non-cloud infrastructure. Agentic AI: Lead the development and integration of agentic AI systems, enabling autonomous decision-making and action-taking capabilities in AI solutions. Vector Database: Design and implement vector databases (e.g., Faiss, Annoy, Hnswlib) for efficient similarity search and retrieval in AI applications. Technical Leadership: Provide technical guidance and mentorship to junior team members, ensuring high-quality deliverables and adherence to best practices. Security of LLMs: Design and implement robust security measures to prevent data poisoning, model inversion attacks, and membership inference attacks, including data encryption, access controls, model watermarking, and regular security audits. Client Engagement: Collaborate with clients to understand their AI requirements, develop tailored solutions, and deliver high-quality results. Act as a trusted technical advisor. Model Development: Develop and fine-tune AI/GenAI models for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation: Design and oversee thorough testing and validation of AI/GenAI models, including performance evaluation, bias detection, and explainability. Deployment and Maintenance: Lead the deployment of AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Knowledge Sharing: Share knowledge and expertise with the team, contributing to the development of best practices and staying up-to-date with industry trends. Lead training sessions for team members. Collaboration: Work closely with cross-functional teams, including data science, engineering, and product management, to ensure successful project delivery. Requirements: Education: Bachelor/Master's in Computer Science, AI, ML, or related fields. Experience: 8+ years of experience in engineering solutions, with a track record of delivering AI solutions. Technical Skills: Advanced Proficiency in AI/GenAI technologies, including deep learning frameworks, NLP, and computer vision. Experience with vector databases and similarity search algorithms. Experience with security measures for LLMs, including data encryption, access controls, and model watermarking. Programming Skills: Strong programming skills in languages like Python or R Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving: Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with containerization (Docker) and orchestration (Kubernetes) Nice to have: Experience with ReactJS for rapid prototyping

Role & responsibilities Design and develop AI-driven features for interactive or intelligent physical products. Implement voice interaction, automation routines, and adaptive control systems. Work on real-time data collection and use AI models to drive decisions or responses. Collaborate with hardware and embedded teams to integrate AI smoothly into product workflows. Optimize performance for edge devices or embedded systems using lightweight models. Ensure reliability, usability, and safety across all AI-enhanced product features Preferred candidate profile Bachelors or Masters degree in Computer Science, Electronics, AI/ML, or related fields. Strong experience in Python and/or C/C++. Familiarity with AI concepts such as NLP, speech recognition, computer vision, and sensor-based automation. Understanding of embedded system principles or IoT communication (e.g., MQTT, BLE) is a plus. Experience working on real-world AI product integration projects.

Role Purpose The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters Do Instrumental in understanding the requirements and design of the product/ software Develop software solutions by studying information needs, studying systems flow, data usage and work processes Investigating problem areas followed by the software development life cycle Facilitate root cause analysis of the system issues and problem statement Identify ideas to improve system performance and impact availability Analyze client requirements and convert requirements to feasible design Collaborate with functional teams or systems analysts who carry out the detailed investigation into software requirements Conferring with project managers to obtain information on software capabilities Perform coding and ensure optimal software/ module development Determine operational feasibility by evaluating analysis, problem definition, requirements, software development and proposed software Develop and automate processes for software validation by setting up and designing test cases/scenarios/usage cases, and executing these cases Modifying software to fix errors, adapt it to new hardware, improve its performance, or upgrade interfaces. Analyzing information to recommend and plan the installation of new systems or modifications of an existing system Ensuring that code is error free or has no bugs and test failure Preparing reports on programming project specifications, activities and status Ensure all the codes are raised as per the norm defined for project / program / account with clear description and replication patterns Compile timely, comprehensive and accurate documentation and reports as requested Coordinating with the team on daily project status and progress and documenting it Providing feedback on usability and serviceability, trace the result to quality risk and report it to concerned stakeholders Status Reporting and Customer Focus on an ongoing basis with respect to project and its execution Capturing all the requirements and clarifications from the client for better quality work Taking feedback on the regular basis to ensure smooth and on time delivery Participating in continuing education and training to remain current on best practices, learn new programming languages, and better assist other team members. Consulting with engineering staff to evaluate software-hardware interfaces and develop specifications and performance requirements Document and demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code Documenting very necessary details and reports in a formal way for proper understanding of software from client proposal to implementation Ensure good quality of interaction with customer w.r.t. e-mail content, fault report tracking, voice calls, business etiquette etc Timely Response to customer requests and no instances of complaints either internally or externally Stakeholder Interaction Stakeholder Type Stakeholder Identification Purpose of Interaction Internal Lead Software Developer and Project Manager Regular reporting & updates Software Developers For work coordination and support in providing testing solutions External Clients Provide apt solutions and support as per the requirement Display Lists the competencies required to perform this role effectively: Functional Competencies/ Skill Leveraging Technology Knowledge of current and upcoming technology along with expertise in programming (automation, tools and systems) to build efficiencies and effectiveness in own function/ Client organization Competent Process Excellence - Ability to follow the standards and norms to produce consistent results, provide effective control and reduction of risk Expert Technical knowledge knowledge of various programming languages, tools, quality management standards and processes - Expert Competency Levels Foundation Knowledgeable about the competency requirements. Demonstrates (in parts) frequently with minimal support and guidance. Competent Consistently demonstrates the full range of the competency without guidance. Extends the competency to difficult and unknown situations as well. Expert Applies the competency in all situations and is serves as a guide to others as well. Master Coaches others and builds organizational capability in the competency area. Serves as a key resource for that competency and is recognised within the entire organization. Behavioral Competencies Formulation & Prioritization Innovation Managing Complexity Execution Excellence Passion for Results Deliver / No. / Performance Parameter / Measure - 1. Continuous Integration, Deployment & Monitoring of Software 100% error free on boarding & implementation, throughput %, Adherence to the schedule/ release plan 2. Quality & CSAT On-Time Delivery, Manage software, Troubleshoot queries Customer experience, completion of assigned certifications for skill upgradation 3. MIS & Reporting 100% on time MIS & report generation Mandatory Skills: Python, GenAI, AWS Preferred Skills: NLP , AI/ML , LLM Architect and implement Al solutions utilizing cutting-edge technologies like LLM, Langchain, and Machine Learning. AIML solution development in Azure using Python Ability to build and finetune the model to improve the performance Create own technology if off-the-shelf technology is not solving the problem. E.g changes to traditional RAG approaches, finetune LLM, create architectures. Use experience and advise leadership and team of data scientists best approaches, architectures for complex ML use cases. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Create end to end AI systems with responsible AI principles Develop data pipelines using SQL to extract and transform data from Snowflake for Al model training and inference. Possess expertise in Natural Language Processing (NLP) & GenAI to integrate text-based data sources into the Al architecture. Collaborate with data scientists and engineers to ensure seamless integration of Al components into existing systems. Responsible for continuous communication about the team progress to keystakeholder.

Position: Prompt Engineer Location: Ahmedabad Work Model: Work from Office Job Summary: We are looking for a talented Prompt Engineer to develop, optimize, and fine-tune text-based inputs for AI models. The ideal candidate will have strong analytical skills, excellent English communication abilities, and keen listening and comprehension skills to collaborate effectively and deliver high-quality results. As a Prompt Writer & AI Response Evaluator, you will play a key role in shaping the performance of an AI system by crafting high-quality prompts and rating AI-generated responses. Key Responsibilities: Develop and refine text prompts to enhance AI model outputs across various applications. Analyze outcomes and iteratively improve prompts to increase accuracy and relevance. Collaborate with technical teams to understand project requirements and tailor prompts accordingly. Ensure clarity and consistency in prompt design to drive the intended model responses. Conduct A/B testing to evaluate prompt effectiveness and identify areas for improvement. Required Skills: Analytical Skills: Ability to evaluate and optimize prompt performance using critical thinking and problem-solving approaches. English Communication: Proficiency in both written and spoken English for creating clear and effective prompts. Comprehension Abilities: Ability t understand complex instructions, project goals, and user expectations. Listening Skills: Active listening to accurately capture team feedback and project needs, adjusting prompts as necessary. Strong attention to detail and ability to follow specific guidelines for prompt writing and response evaluation. Qualifications: Bachelors degree in any relevant field. Prior experience in NLP, machine learning, or related areas is a plus. What We Offer: Compensation commensurate with experience, competitive base salary plus bonus. A flexible comprehensive benefits package to suit your personal circumstances. A supportive work culture that gives you the freedom to experiment. A co-funded professional development program which aligns with your career growth. Job Types: Full-time, Permanent Pay: 20,000.00 - 35,000.00 per month Reach out for more information; HR Aditya: 9265798226 HR Lara - 8160687842 HR Jinal - 8780627704

Position: Prompt Engineer Location: Ahmedabad Work Model: Work from Office Job Summary: We are looking for a talented Prompt Engineer to develop, optimize, and fine-tune text-based inputs for AI models. The ideal candidate will have strong analytical skills, excellent English communication abilities, and keen listening and comprehension skills to collaborate effectively and deliver high-quality results. As a Prompt Writer & AI Response Evaluator, you will play a key role in shaping the performance of an AI system by crafting high-quality prompts and rating AI-generated responses. Key Responsibilities: Develop and refine text prompts to enhance AI model outputs across various applications. Analyze outcomes and iteratively improve prompts to increase accuracy and relevance. Collaborate with technical teams to understand project requirements and tailor prompts accordingly. Ensure clarity and consistency in prompt design to drive the intended model responses. Conduct A/B testing to evaluate prompt effectiveness and identify areas for improvement. Required Skills: Analytical Skills: Ability to evaluate and optimize prompt performance using critical thinking and problem-solving approaches. English Communication: Proficiency in both written and spoken English for creating clear and effective prompts. Comprehension Abilities: Ability t understand complex instructions, project goals, and user expectations. Listening Skills: Active listening to accurately capture team feedback and project needs, adjusting prompts as necessary. Strong attention to detail and ability to follow specific guidelines for prompt writing and response evaluation. Qualifications: Bachelors degree in any relevant field. Prior experience in NLP, machine learning, or related areas is a plus. What We Offer: Compensation commensurate with experience, competitive base salary plus bonus. A flexible comprehensive benefits package to suit your personal circumstances. A supportive work culture that gives you the freedom to experiment. A co-funded professional development program which aligns with your career growth. Job Types: Full-time, Permanent Pay: 20,000.00 - 35,000.00 per month Reach out for more information; HR Aditya: 9265798226 HR Lara - 8160687842 HR Jinal - 8780627704