118 Hugging Face Jobs - Page 4

Role Overview: We are looking for a ML/AI Gen AI Expert with 4-7 years of experience for executing AI/GenAI use cases as POCs . Media domain experience (OTT, DTH, Web) is a plus. Key Responsibilities: Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders. Design, develop, and deploy models (ML and GenAI) using Google Clouds Vertex AI platform. Fine-tune and evaluate LLMs for domain-specific applications, ensuring responsible AI practices. Collaborate with data engineers and architects to ensure robust, scalable, and secure data pipelines feeding ML models. Document solutions, workflows, and experiments to support reproducibility, transparency, and handover readiness. Core Skills: Strong foundation in machine learning and deep learning, including supervised, unsupervised, and reinforcement learning. Hands-on experience with Vertex AI, including AutoML, Pipelines, Model Registry, and Generative AI Studio. Experience with LLMs and GenAI workflows, including prompt engineering, tuning, and evaluation. Python and ML frameworks proficiency (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). Strong collaboration and communication skills to work cross-functionally with data, product, and business teams. Technical Skills: Vertex AI on Google Cloud Model training, deployment, endpoint management, and MLOps tooling. GenAI tools and APIs Hands-on with PaLM, Gemini, or other large language models via Vertex AI or open source. Python Proficient in scripting ML pipelines, data preprocessing, and model evaluation. ML/GenAI Libraries scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain. Cloud & DevOps Experience with GCP services (BigQuery, Cloud Functions, Cloud Storage), CI/CD for ML, and containerization (Docker/Kubernetes) Experience in the media domain (OTT, DTH, Web) and handling large-scale media datasets. Immediate Joiners.

You will work closely with data scientists, product teams, and developers to fine-tune LLM behavior for diverse applications including chatbots, code generation, creative writing, and data extraction.

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.

About the Role: We are seeking a skilled and motivated Python Developer with 23 years of hands-on experience to join our dynamic engineering team. The ideal candidate will have strong experience in Python and Django , with exposure to modern frontend technologies and a good grasp of systems design and cloud fundamentals. This is an exciting opportunity to work on scalable web applications in a collaborative and fast-paced environment. Key Responsibilities: Develop, maintain, and scale web applications using Python and Django. Design and optimize database schemas and queries using MySQL. Collaborate with frontend developers and contribute to UI components using HTML, CSS (Bootstrap), JavaScript, and jQuery (optional). Participate in code reviews, write unit and integration tests, and follow best practices for software development. Work with version control systems like Git and track tasks and bugs using Jira. Collaborate cross-functionally with product, design, and other engineering teams to deliver high-quality solutions. Maintain clear and effective communication with team members and stakeholders. Desired skills: 2 to 3 years of experience in backend development using Python and Django. Proficient in MySQL and working knowledge of relational database design and optimization. Familiarity with HTML, CSS (Bootstrap), and JavaScript; jQuery is a plus. Comfortable working in Linux-based operating systems for development and deployment. Experience with Git for version control and Jira for project tracking. Strong problem-solving skills and attention to detail. Excellent written and verbal communication skills. Ability to work independently and as part of a collaborative team. Good to have: Understanding of how to integrate Gen AI APIs (like OpenAI, Hugging Face) into web applications or backend systems. Education & Experience: 2 to 3 years of work experience.

My profile - linkedin.com/in/yashsharma1608 Position : AI Architect ( Gen AI ) Experience : 8 - 10 years Notice Period : Immediate to 15 days. Budget upto - 45 to 50 LPA Location : Bangalore. Note : - (any developer with minimum 3 to 4 years into AI), SaaS company mandatory. Product Based company Mandatory Discuss the feasibility of AI/ML use cases along with architectural design with business teams and translate the vision of business leaders into realistic technical implementation Play a key role in defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings Design and implement robust ML infrastructure and deployment pipelines Establish comprehensive MLOps practices for model training, versioning, and deployment Lead the development of HR-specialized language models (SLMs) Implement model monitoring, observability, and performance optimization frameworks Develop and execute fine-tuning strategies for large language models Create and maintain data quality assessment and validation processes Design model versioning systems and A/B testing frameworks Define technical standards and best practices for AI development Optimize infrastructure for cost, performance, and scalability Required Qualifications 7+ years of experience in ML/AI engineering or related technical roles 3+ years of hands-on experience with MLOps and production ML systems Demonstrated expertise in fine-tuning and adapting foundation models Strong knowledge of model serving infrastructure and orchestration Proficiency with MLOps tools (MLflow, Kubeflow, Weights & Biases, etc.) Experience implementing model versioning and A/B testing frameworks Strong background in data quality methodologies for ML training Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with cloud-based ML platforms (AWS, Azure, Google Cloud) Proven track record of deploying ML models at scale Preferred Qualifications Experience developing AI applications for enterprise software domains Knowledge of distributed training techniques and infrastructure Experience with retrieval-augmented generation (RAG) systems Familiarity with vector databases (Pinecone, Weaviate, Milvus) Understanding of responsible AI practices and bias mitigation Bachelor's or Master's degree in Computer Science, Machine Learning, or related field What We Offer Opportunity to shape AI strategy for a fast-growing HR technology leader Collaborative environment focused on innovation and impact Competitive compensation package Professional development opportunities Flexible work arrangements Qualified candidates who are passionate about applying cutting-edge AI to transform HR technology are encouraged to apply

Notice Period : Immediate - 30 days Job Summary : We are looking for a highly skilled Full Stack Developer with strong expertise in backend technologies like Python, Django, Flask/FastAPI, and frontend development using React.js. The ideal candidate will also have hands-on experience with SQL databases, familiarity with Generative AI concepts, and a foundational understanding of Microsoft Azure cloud services. Key Responsibilities : - Design, develop, test, and deploy scalable web applications using Django or FastAPI. - Build interactive UIs with React.js and integrate them with backend APIs. - Work with relational databases (e.g., PostgreSQL, MySQL) and write optimized SQL queries. - Develop and integrate AI-based features using Gen AI frameworks and tools (e.g., OpenAI APIs). - Follow Agile/Scrum methodologies and participate in sprint planning, reviews, and retrospectives. - Collaborate with DevOps teams for deployment and CI/CD setup on Azure. - Write clean, maintainable, and well-documented code. - Conduct code reviews and mentor junior developers if required. Mandatory Skills : - Strong Python programming experience. - Experience with Django and either Flask or FastAPI. - Proficiency in building RESTful APIs and backend services. - Solid frontend skills using React.js, HTML, CSS, and JavaScript. - Hands-on with SQL databases (PostgreSQL, MySQL, or equivalent). - Experience integrating Gen AI models or APIs (e.g., OpenAI, LangChain, Hugging Face). - Basic understanding of Azure cloud services (App Services, Azure Functions, Storage, etc.). Good to Have : - Experience with NoSQL databases (e.g., MongoDB). - Knowledge of containerization (Docker) and CI/CD pipelines. - Familiarity with authentication/authorization using OAuth, JWT, etc. - Exposure to cloud-native development or serverless architecture. - Knowledge of unit testing frameworks (pytest, unittest, etc.). Soft Skills : - Strong problem-solving and analytical skills. - Good communication and teamwork abilities. - Proactive attitude and willingness to take ownership.

Notice Period: Maximum 30 days Location: Bangalore, Chennai, Kolkata, Pune, and Hyderabad Note: Candidates based in Hyderabad must attend in-person interviews for the second round. Role Summary: Generative AI Specialist Mandatory Skills: Gen AI, LLMs, ML/DL/NLP, RAG, LangChain, Mistral, LLaMA, Hugging Face, Python, TensorFlow, PyTorch, Django, Vector DBs Preferred Skills: GCP/Azure/AWS, Databricks, MLOps (e.g., Kubeflow, MLflow), Kubernetes, GitHub/Bitbucket, Azure DevOps, GPT-4 Responsibilities: Design, develop, and deploy generative AI solutions using modern ML/DL techniques. Work with large-scale datasets; handle preprocessing and model optimization. Build applications using LLMs and frameworks like LangChain, leveraging models like Mistral, LLaMA, GPT-4. Research and implement cutting-edge GenAI algorithms and architectures. Ensure Responsible AI compliance and monitor model performance post-deployment. Collaborate with cross-functional teams for solution integration and data engineering. Drive innovation by staying up to date with AI trends. Provide technical leadership, mentorship, and contribute to project governance and stakeholder communication. If you meet the requirements and are looking for a new opportunity, we'd love to hear from you! Interested candidates can send their resumes to admin@spearheadps.com OR Contact us via call/WhatsApp at 9899080360

We are looking for a talented and driven Generative AI Engineer with 3 years of experience to join our AI team. You will work on designing, developing, and optimizing cutting-edge generative models for a variety of applications, including text, images, and audio Proficiency in Python and relevant ML/AI libraries (TensorFlow, PyTorch, Hugging Face, etc.),GANs, VAEs, Transformers, and Diffusion Models,NLP,computer vision, or audio synthesis,AWS, GCP, Azure,MLOps Develop and optimize generative models (e.g., GANs, VAEs, Diffusion Models, Transformer Models) for various use cases. Location: Chennai, Hyderabad, Kolkata, Pune, Ahmedabad, Remote

Position - Full Stack Developer( LLM & AI/ML/ Python NLP, Claude,Mistral,RAG ) Group Manager - RNA Design, fine-tune, and deploy LLM-based solutions (e.g., ChatGPT, LLaMA, Mistral, Claude).Integrate LLMs into modern web applications to deliver intelligent user experiences Develop end-to-end full-stack applications using modern web frameworks and RESTful APIs. Collaborate with data scientists and product managers to translate business problems into LLM-based applications. Build and optimize prompt engineering workflows for maximum model performance. Ensure performance, scalability, and security of deployed solutions Stay up to date with the latest advancements in generative AI and web development Must Have: LLM & AI/ML Skills: Deep experience with LLMs (OpenAI GPT, Claude, LLaMA, Mistral, etc.) Expertise in prompt engineering, model fine-tuning, and RAG (Retrieval-Augmented Generation) Familiarity with Hugging Face, LangChain, or similar AI frameworks Strong Python programming skills, especially in NLP libraries (e.g., Transformers, SpaCy, PyTorch, TensorFlow) Experience with vector databases (e.g., Pinecone, FAISS, Weaviate)Web Development: Proficiency in modern front-end frameworks (React, Angular, or Vue.js) Strong backend development experience (Node.js, Django, Flask, or FastAPI) Hands-on experience building and integrating RESTful APIs and GraphQL endpoints Strong understanding of web architecture, security, performance optimization.DevOps & Deployment: Experience with Docker, Kubernetes, or cloud services (AWS, Azure, GCP)CI/CD pipelines and code quality tools (e.g., GitHub Actions, Jenkins)General:Strong problem-solving and debugging skills. Excellent written and verbal communication.Ability to work independently in a fast-paced, innovative environment Ability to translate business needs into scalable tech solutions Leadership experience in mentoring or guiding technical teams Qualifications Masters or Bachelors in Computer Science, Artificial Intelligence, or a related field Experience with production-grade LLM applications (chatbots, agents, copilots, etc.) 8+ years of hands-on experience.

Role Overview We are seeking a highly skilled AI Engineer with 8-12 years of experience to lead the development of Generative AI (GenAI) and Machine learning solutions for internal projects. This role requires a self-driven leader with exceptional communication, strategic thinking, and expertise in data analytics and visualization to deliver innovative GenAI tools tailored to internal team needs while driving cross-functional collaboration. Key Responsibilities - GenAI Development: Design and develop advanced GenAI models (e.g., LLMs, DALL E models) and AI Agents to automate internal tasks and workflows. Exposure to LLMs: Utilize Azure Open AI APIs, experience on models like GPT4o, O3 , llama3 Enhance the existing RAG based application: In depth understanding of stages of RAG - chunking, retrieval etc. - Cloud Deployment: Deploy and scale GenAI solutions on Azure Cloud services (e.g., Azure Function App) for optimal performance. In depth understanding of ML models like linear regression, random forest, decision trees. In depth understanding on clustering and supervised models. - AI Agent Development: Build AI agents using frameworks like LangChain to streamline internal processes and boost efficiency. - Data Analytics: Perform advanced data analytics to preprocess datasets, evaluate model performance, and derive actionable insights for GenAI solutions. - Data Visualization: Create compelling visualizations (e.g., dashboards, charts) to communicate model outputs, performance metrics, and business insights to stakeholders. Stakeholder Collaboration: Partner with departments to gather requirements, align on goals, and present technical solutions and insights effectively to non-technical stakeholders. - Model Optimization: Fine-tune GenAI models for efficiency and accuracy using techniques like prompt engineering, quantization, and RAG (Retrieval-Augmented Generation). LLMOps Best Practices: Implement GenAI-specific MLOps, including CI/CD pipelines (Git, Azure DevOps) - Leadership: Guide cross-functional teams, mentor junior engineers, and drive project execution with strategic vision and ownership. Helicopters, strategic Thinking**: Develop innovative GenAI strategies to address business challenges, leveraging data insights to align solutions with organizational goals. - Self-Driven Execution: Independently lead projects to completion with minimal supervision, proactively resolving challenges and seeking collaboration when needed. - Continuous Learning: Stay ahead of GenAI, analytics, and visualization advancements, self-learning new techniques to enhance project outcomes. Required Skills & Experience - Experience: 8-12 years in AI/ML development, with at least 4 years focused on Generative AI and AI agent frameworks. - Education: BTech/BE in Computer Science, Engineering, or equivalent (Masters or PhD in AI/ML is a plus). - Programming: Expert-level Python proficiency, with deep expertise in GenAI libraries (e.g., LangChain, Hugging Face Transformers, PyTorch, Open AI SDK) and data analytics libraries (e.g., Pandas, NumPy), sk-learn. Mac - Data Analytics: Strong experience in data preprocessing, statistical analysis, and model evaluation to support GenAI development and business insights. - Data Visualization: Proficiency in visualization tools (e.g., Matplotlib, Seaborn, Plotly, Power BI, or Tableau) to create dashboards and reports for stakeholders. - Azure Cloud Expertise: Strong experience with Azure Cloud services (e.g., Azure Function App, Azure ML, serverless) for model training and deployment. - GenAI Methodologies: Deep expertise in LLMs, AI agent frameworks, prompt engineering, and RAG for internal workflow automation. - Deployment: Proficiency in Docker, Kubernetes, and CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production-grade GenAI systems. - LLMOps: Expertise in GenAI MLOps, including experiment tracking (e.g., Weights & Biases), automated evaluation metrics (e.g., BLEU, ROUGE), and monitoring. Soft Skills: - Communication: Exceptional verbal and written skills to articulate complex GenAI concepts, analytics, and visualizations to technical and non-technical stakeholders. - Strategic Thinking: Ability to align AI solutions with business objectives, using data-driven insights to anticipate challenges and propose long-term strategies. - Problem-Solving: Strong analytical skills with a proactive, self-starter mindset to independently resolve complex issues. - Collaboration: Collaborative mindset to work effectively across departments and engage colleagues for solutions when needed. Preferred Skills - Experience deploying GenAI models in production environments, preferably on Azure Familiarity with multi-agent systems, reinforcement learning, or distributed training (e.g., DeepSpeek). - Knowledge of DevOps practices, including Git, CI/CD, and infrastructure-as-code. Advanced data analytics techniques (e.g., time-series analysis, A/B testing) for GenAI applications. - Experience with interactive visualization frameworks (e.g., Dash, Streamlit) for real-time dashboards. - Contributions to GenAI or data analytics open-source projects or publications in NLP, generative modeling, or data scien

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Principal Consultant - Generative AI In this role, you will be responsible for creating cutting-edge artificial intelligence solutions that possess a broad understanding of diverse tasks and domains. You will contribute to the development of intelligent systems capable of adapting and learning across a wide range of applications. Responsibilities . experience in Cloud & Generative AI . Hands-on knowledge in Large Language Models from OpenAI, Meta, Google, Hugging Face etc. - demonstrate ability to implement solutions leveraging LLMs . Working knowledge of generative models, prompt engineering, fine-tuning - to implement innovative AI use cases . Collaborate with the architect to develop prototypes, conduct PoCs . Collaborate with service line teams to design, implement and manage Gen-AI solutions . Define and document best practices and strategies regarding deployment and infrastructure maintenance . Good understanding of AWS/Azure primarily focus on AI ecosystems such as Elasticsearch, Azure OpenAI/Cognitive services . Ability to write robust code in Python Java, React, RDBMS (Postgres) - Transactional and Analytical databases . (More than 1 language including Python is preferred) . Experience with Docker and Kubernetes . Experience with Agile Development. Qualifications we seek in you! Minimum Qualifications / Skills . BE/B.TECH . Strong understanding of generative AI models and algorithms. . Proficiency in at least one Generative AI Model (OpenAI ChatGPT, llama, Claude 2, etc.). Preferred Qualifications/ Skills . Self-starter . Highly motivated/passionate for new technologies, engineering mindset . Strong teamwork, problem-solving, and analytical skills . Good communication Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Get to know us at www.genpact.com and on X, Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Role : Data Scientist Experience: 610 Years Salary : 35 L Upto Location : Bangalore Notice Period: 30 Days max ( Immediate Joiners Preferred ) Note : We are Open for both Contract or FTE Job Description: We are seeking a Data Scientist with strong experience in natural language processing and generative AI to build intelligent systems that extract information from PDFs, power chatbots, and implement retrieval-augmented generation (RAG) solutions. The ideal candidate should have a solid foundation in machine learning, experience working with unstructured text data. Key Responsibilities: Design and implement pipelines for extracting structured data from PDF documents using tools like PyMuPDF, PDFPlumber, or OCR libraries. Develop and fine-tune RAG pipelines combining vector databases (e.g., FAISS, Chroma) with LLMs for document-based question answering. Build and optimize conversational agents (chatbots) that use domain-specific data and generative AI models. Train and evaluate machine learning and NLP models for classification, entity extraction, summarization, etc. Collaborate with engineering and product teams to integrate AI capabilities into production systems. Monitor model performance and continually improve accuracy and relevance of generated responses. Requirements: Strong Python skills and experience with libraries like Hugging Face Transformers, LangChain, or LlamaIndex. Strong knowledge of ABC cloud tools (AWS or Azure) Familiarity with vector databases and embedding models (OpenAI, Cohere, SentenceTransformers). Experience with PDF data extraction techniques and tools. Solid understanding of supervised/unsupervised ML, deep learning, and NLP techniques. Experience working with LLMs and knowledge of prompt engineering and fine-tuning. Bachelors or Masters degree in Computer Science, Data Science, or a related field.

Role Responsibilities: Build and deploy LLM-based NLP and content generation solutions Fine-tune models, develop RAG pipelines, and conduct prompt engineering Integrate AI workflows using Python, LangChain, and vector databases Optimize AI systems for production performance and cost Key Deliverables: Scalable GenAI solutions integrated into enterprise apps Custom LLMs with fine-tuning and embeddings Deployment-ready ML pipelines using AWS/Azure/GCP Documentation and collaboration on ethical AI practices

Role Responsibilities: Build and deploy LLM-based NLP and content generation solutions Fine-tune models, develop RAG pipelines, and conduct prompt engineering Integrate AI workflows using Python, LangChain, and vector databases Optimize AI systems for production performance and cost Key Deliverables: Scalable GenAI solutions integrated into enterprise apps Custom LLMs with fine-tuning and embeddings Deployment-ready ML pipelines using AWS/Azure/GCP Documentation and collaboration on ethical AI practices

Job Summary: We are looking for a highly capable and automation-driven MLOps Engineer with 2+ years of experience in building and managing end-to-end ML infrastructure. This role focuses on operationalizing ML pipelines using tools like DVC, MLflow, Kubeflow, and Airflow, while ensuring efficient deployment, versioning, and monitoring of machine learning and Generative AI models across GPU-based cloud infrastructure (AWS/GCP). The ideal candidate will also have experience in multi-modal orchestration, model drift detection, and CI/CD for ML systems. Key Responsibilities: Develop, automate, and maintain scalable ML pipelines using tools such as Kubeflow, MLflow, Airflow, and DVC. Set up and manage CI/CD pipelines tailored to ML workflows, ensuring reliable model training, testing, and deployment. Containerize ML services using Docker and orchestrate them using Kubernetes in both development and production environments. Manage GPU infrastructure and cloud-based deployments (AWS, GCP) for high-performance training and inference. Integrate Hugging Face models and multi-modal AI systems into robust deployment frameworks. Monitor deployed models for drift, performance degradation, and inference bottlenecks, enabling continuous feedback and retraining. Ensure proper model versioning, lineage, and reproducibility for audit and compliance. Collaborate with data scientists, ML engineers, and DevOps teams to build reliable and efficient MLOps systems. Support Generative AI model deployment with scalable architecture and automation-first practices. Qualifications: 2+ years of experience in MLOps, DevOps for ML, or Machine Learning Engineering. Hands-on experience with MLflow, DVC, Kubeflow, Airflow, and CI/CD tools for ML. Proficiency in containerization and orchestration using Docker and Kubernetes. Experience with GPU infrastructure, including setup, scaling, and cost optimization on AWS or GCP. Familiarity with model monitoring, drift detection, and production-grade deployment pipelines. Good understanding of model lifecycle management, reproducibility, and compliance. Preferred Qualifications : Experience deploying Generative AI or multi-modal models in production. Knowledge of Hugging Face Transformers, model quantization, and resource-efficient inference. Familiarity with MLOps frameworks and observability stacks. Experience with security, governance, and compliance in ML environments. Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

- Data Scientist -6+ years of experience in data science, with at least 2 years focused on LLMs or Generative AI. -Proven implementation experience in Data Science, Machine Learning, Deep Learning, and NLP for multiple domains. -Strong programming skills in Python, with experience in libraries such as Transformers (Hugging Face), PyTorch, or TensorFlow. -Hands-on experience with fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation. -Familiarity with vector databases and embedding techniques. -Experience deploying models using APIs, Docker, and cloud platforms -Strong analytical, problem-solving, and communication skills. -Experience in ML Ops, Model deployment, Model lifecycle and management

ONLY 30 DAYS JOINERS Hello I hope you're doing well. We are currently hiring for an exciting opportunity with one of our top clients in the field of Generative AI . Based on your background, I believe this role could be a strong match for your expertise. Role Highlights: Location: Bangalore/Chennai/Kolkata/Pune/Hyderabad Experience Required: 11 -16 Years Notice Period: Maximum 30 Days CTC: As per market standards Mandatory Skills: Gen AI, LLM, ML/DL/NLP, RAG, LangChain, Mistral, Llama, Hugging Face, Python, TensorFlow, PyTorch, Django, Vector DB Preferred Skills: GCP/Azure/AWS, Databricks, MLOps (Kubeflow/Mlflow), Kubernetes, GitHub/Bitbucket, ADO, GPT-4 Key Responsibilities: Develop and implement advanced Generative AI models. Apply ML/DL algorithms for real-world applications across NLP and vision domains. Collaborate on data preprocessing, model training, and deployment. Drive innovation by staying current with industry trends and R&D in Gen AI. Ensure responsible AI practices and performance monitoring post-deployment. Mentor junior members and lead AI-driven project initiatives. If you're interested or know someone who fits this role, please share your updated resume and current CTC/Notice Period details. WhatsApp: 987153039 Email: shweta.gupta@sspearhead.com Warm Regards SHWETA GUPTA || Senior Recruitment Specialist Spearhead Professional Services Call/ WhatsApp: 9871530393 LinkedIn Profile: shwetagupta1810

We are seeking a highly experienced and technically adept Lead AI/ML Engineer to spearhead the development and deployment of cutting-edge AI solutions, with a focus on Generative AI and Natural Language Processing (NLP). The ideal candidate will be responsible for leading a high-performing team, architecting scalable ML systems, and driving innovation across AI/ML projects using modern toolchains and cloud-native technologies. Key Responsibilities Team Leadership: Lead, mentor, and manage a team of data scientists and ML engineers; drive technical excellence and foster a culture of innovation. AI/ML Solution Development: Design and deploy end-to-end machine learning and AI solutions, including Generative AI and NLP applications. Conversational AI: Build LLM-based chatbots and document intelligence tools using frameworks like LangChain , Azure OpenAI , and Hugging Face . MLOps Execution: Implement and manage the full ML lifecycle using tools such as MLFlow , DVC , and Kubeflow to ensure reproducibility, scalability, and efficient CI/CD of ML models. Cross-functional Collaboration: Partner with business and engineering stakeholders to translate requirements into impactful AI solutions. Visualization & Insights: Develop interactive dashboards and data visualizations using Streamlit , Tableau , or Power BI for presenting model results and insights. Project Management: Own delivery of projects with clear milestones, timelines, and communication of progress and risks to stakeholders. Required Skills & Qualifications Languages & Frameworks: Proficient in Python and frameworks like TensorFlow , PyTorch , Keras , FastAPI , Django NLP & Generative AI: Hands-on experience with BERT , LLaMA , Spacy , LangChain , Hugging Face , and other LLM-based technologies MLOps Tools: Experience with MLFlow , Kubeflow , DVC , ClearML for managing ML pipelines and experiment tracking Visualization: Strong in building visualizations and apps using Power BI , Tableau , Streamlit Cloud & DevOps: Expertise with Azure ML , Azure OpenAI , Docker , Jenkins , GitHub Actions Databases & Data Engineering: Proficient with SQL/NoSQL databases and handling large-scale datasets efficiently Preferred Qualifications Masters or PhD in Computer Science, AI/ML, Data Science, or related field Experience working in agile product development environments Strong communication and presentation skills with technical and non-technical stakeholders

Responsibilities AI-Powered Software Development & API Integration Develop AI-driven applications, microservices, and automation workflows using FastAPI, Flask, or Django, ensuring cloud-native deployment and performance optimization. Integrate OpenAI APIs (GPT models, Embeddings, Function Calling) and Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval, classification, and decision-making. Data Engineering & AI Model Performance Optimization Design, build, and optimize scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake. Enhance AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings). Microservices, APIs & Security Develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT, and API Key Authentication. Implement AI-powered logging, observability, and monitoring to track data pipelines, model drift, and inference accuracy, ensuring compliance with AI governance and security best practices. AI & Data Engineering Collaboration Work with AI/ML, Data Engineering, and DevOps teams to optimize AI model deployments, data pipelines, and real-time/batch processing for AI-driven solutions. Engage in Agile ceremonies, backlog refinement, and collaborative problem-solving to scale AI-powered workflows in areas like fraud detection, claims processing, and intelligent automation. Cross-Functional Coordination and Communication Collaborate with Product, UX, and Compliance teams to align AI-powered features with user needs, security policies, and regulatory frameworks (HIPAA, GDPR, SOC2). Ensure seamless integration of structured and unstructured data sources (SQL, NoSQL, vector databases) to improve AI model accuracy and retrieval efficiency. Mentorship & Knowledge Sharing Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions. Education & Experience Required 12-18 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions. Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles. Bachelor's Degree or equivalent in Computer Science, Engineering, Data Science, or a related field. Proficiency in full-stack development with expertise in Python (preferred for AI), Java Experience with structured & unstructured data: SQL (PostgreSQL, MySQL, SQL Server) NoSQL (OpenSearch, Redis, Elasticsearch) Vector Databases (FAISS, Pinecone, ChromaDB) Cloud & AI Infrastructure: AWS: Lambda, SageMaker, ECS, S3 Azure: Azure OpenAI, ML Studio GenAI Frameworks & Tools: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, AutoGPT, CrewAI. Experience in LLM deployment, retrieval-augmented generation (RAG), and AI search optimization. Proficiency in AI model evaluation (BLEU, ROUGE, BERT Score, cosine similarity) and responsible AI deployment. Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams. Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI adoption.

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.

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams.

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Senior Data Scientist, Operations Mumbai, India About Argus: Argus is the leading independent provider of market intelligence to the global energy and commodity markets. We offer essential price assessments, news, analytics, consulting services, data science tools and industry conferences to illuminate complex and opaque commodity markets. Headquartered in London with 1,500 staff, Argus is an independent media organisation with 30 offices in the worlds principal commodity trading hubs. Companies, trading firms and governments in 160 countries around the world trust Argus data to make decisions, analyse situations, manage risk, facilitate trading and for long-term planning. Argus prices are used as trusted benchmarks around the world for pricing transportation, commodities and energy. Founded in 1970, Argus remains a privately held UK-registered company owned by employee shareholders and global growth equity firm General Atlantic. What were looking for: Join our Generative AI team as a Senior Data Scientist, reporting directly to the Lead Data Scientist in India. You will play a crucial role in building, optimizing, and maintaining AI-ready data infrastructure for advanced Generative AI applications. Your focus will be on hands-on implementation of cutting-edge data extraction, curation, and metadata enhancement techniques for both text and numerical data. You will be a key contributor to the development of innovative solutions, ensuring rapid iteration and deployment, and supporting the Lead in achieving the team's strategic goals. What will you be doing: AI-Ready Data Development : Design, develop, and maintain high-quality AI-ready datasets, ensuring data integrity, usability, and scalability to support advanced Generative AI models. Advanced Data Processing : Drive hands-on efforts in complex data extraction, cleansing, and curation for diverse text and numerical datasets. Implement sophisticated metadata enrichment strategies to enhance data utility and accessibility for AI systems. Algorithm Implementation & Optimization : Implement and optimize state-of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development : Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application : Apply advanced prompt engineering techniques to optimize LLM performance for specific data extraction, summarization, and generation tasks, working closely with the Lead's guidance. LLM Evaluation Support : Contribute to the systematic evaluation of Large Language Models (LLMs) outputs, analysing quality, relevance, and accuracy, and supporting the implementation of LLM-as-a-judge frameworks. Retrieval-Augmented Generation (RAG) Contribution : Actively contribute to the implementation and optimization of RAG systems, including working with embedding models, vector databases, and, where applicable, knowledge graphs, to enhance data retrieval for GenAI. Technical Mentorship : Act as a technical mentor and subject matter expert for junior data scientists, providing guidance on best practices in coding and PR reviews, data handling, and GenAI methodologies. Cross-Functional Collaboration : Collaborate effectively with global data science teams, engineering, and product stakeholders to integrate data solutions and ensure alignment with broader company objectives. Operational Excellence : Troubleshoot and resolve data-related issues promptly to minimize potential disruptions, ensuring high operational efficiency and responsiveness. Documentation & Code Quality : Produce clean, well-documented, production-grade code, adhering to best practices for version control and software engineering. Skills and Experience: Academic Background : Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks : 2+ years of hands-on experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools : 1+ years Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering : Deep expertise in prompt engineering, including prompt tuning, chaining, and optimization techniques. LLM Evaluation : Experience evaluating LLM outputs, including using LLM-as-a-judge methodologies to assess quality and alignment. RAG and Knowledge Graphs : Practical understanding and experience using vector databases. In addition, familiarity with graph-based RAG architectures and the use of knowledge graphs to enhance retrieval and reasoning would be a strong plus. Cloud : 2+ years of experience with Gemini/OpenAI models and cloud platforms such as AWS, Google Cloud, or Azure. Proficient with Docker for containerization. Data Engineering : Strong understanding of data extraction, curation, metadata enrichment, and AI-ready dataset creation. Collaboration and Communication : Excellent communication skills and a collaborative mindset, with experience working across global teams. Whats in it for you: Competitive salary Hybrid Working Policy (3 days in Mumbai office/ 2 days WFH once fully inducted) Group healthcare scheme 18 days annual leave 8 days of casual leave Extensive internal and external training Hours: This is a full-time position operating under a hybrid model, with three days in the office and up to two days working remotely. The team supports Argus key business processes every day, as such you will be required to work on a shift-based rota with other members of the team supporting the business until 8pm. Typically support hours run from 11am to 8pm with each member of the team participating up to 2/3 times a week. For more details about the company and to apply please make sure you send your CV and cover letter via our website: www.argusmedia.com/en/careers/open-positions By submitting your job application, you automatically acknowledge and consent to the collection, use and/or disclosure of your personal data to the Company. Argus is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.

Required technical and professional expertise Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another Document solution architectures, design decisions, implementation details, and lessons learned. Stay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Preferred technical and professional experience Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus Demonstrate a growth mindset to understand clients business processes and challenges