138 Gpt Jobs - Page 6

Role: Gen AI Engineer Exp: 5 to 8 yrs. Loc: Bangalore, Pune, Hyderabad NP: Immediate joiners, who can join in 30 days. Required Skills: Python, Large Language Models (LLM), Machine Learning (ML), Generative AI

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

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

Job Type: Full Time Job Description: We are seeking an experienced AI Engineer with 4-5 years of hands-on experience in designing and implementing AI solutions. The ideal candidate should have a strong foundation in developing AI/ML-based solutions, including expertise in Computer Vision (OpenCV). Additionally, proficiency in developing, fine-tuning, and deploying Large Language Models (LLMs) is essential. As an AI Engineer, candidate will work on cutting-edge AI applications, using LLMs like GPT, LLaMA, or custom fine-tuned models to build intelligent, scalable, and impactful solutions. candidate will collaborate closely with Product, Data Science, and Engineering teams to define, develop, and optimize AI/ML models for real-world business applications. Key Responsibilities: Research, design, and develop AI/ML solutions for real-world business applications, RAG is must. Collaborate with Product & Data Science teams to define core AI/ML platform features. Analyze business requirements and identify pre-trained models that align with use cases. Work with multi-agent AI frameworks like LangChain, LangGraph, and LlamaIndex. Train and fine-tune LLMs (GPT, LLaMA, Gemini, etc.) for domain-specific tasks. Implement Retrieval-Augmented Generation (RAG) workflows and optimize LLM inference. Develop NLP-based GenAI applications, including chatbots, document automation, and AI agents. Preprocess, clean, and analyze large datasets to train and improve AI models. Optimize LLM inference speed, memory efficiency, and resource utilization. Deploy AI models in cloud environments (AWS, Azure, GCP) or on-premises infrastructure. Develop APIs, pipelines, and frameworks for integrating AI solutions into products. Conduct performance evaluations and fine-tune models for accuracy, latency, and scalability. Stay updated with advancements in AI, ML, and GenAI technologies. Required Skills & Experience: AI & Machine Learning: Strong experience in developing & deploying AI/ML models. Generative AI & LLMs: Expertise in LLM pretraining, fine-tuning, and optimization. NLP & Computer Vision: Hands-on experience in NLP, Transformers, OpenCV, YOLO, R-CNN. AI Agents & Multi-Agent Frameworks: Experience with LangChain, LangGraph, LlamaIndex. Deep Learning & Frameworks: Proficiency in TensorFlow, PyTorch, Keras. Cloud & Infrastructure: Strong knowledge of AWS, Azure, or GCP for AI deployment. Model Optimization: Experience in LLM inference optimization for speed & memory efficiency. Programming & Development: Proficiency in Python and experience in API development. Statistical & ML Techniques: Knowledge of Regression, Classification, Clustering, SVMs, Decision Trees, Neural Networks. Debugging & Performance Tuning: Strong skills in unit testing, debugging, and model evaluation. Hands-on experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone). Good to Have: Experience with multi-modal AI (text, image, video, speech processing). Familiarity with containerization (Docker, Kubernetes) and model serving (FastAPI, Flask, Triton).

We are looking for a GenAI Leader with 12+ years of experience and a strong background in pharma/life sciences to join our team. As a key leader, you will drive innovation in the pharma commercial and clinical space by designing cutting-edge AI solutions, leading high-performing teams, and delivering impactful results. If you have a proven track record in Generative AI, hands-on experience with models like GPT, DALL-E, and Stable Diffusion, and a passion for mentoring and thought leadership, we want to hear from you! Must have skills & competencies Enhance the go-to-market strategy by designing new and relevant solution frameworks to accelerate our clients journeys for impacting patient outcomes. Pitch for these opportunities and craft winning proposals to grow the Data Science Practice. Build and lead a team of data scientists and analysts, fostering a collaborative and innovative environment. Oversee the design and delivery of the models, ensuring projects are completed on time and meet business objectives. Engaging in consultative selling with clients to grow/deliver business. Develop and operationalize scalable processes to deliver on large & complex client engagements. Proven experience in building and productizing GenAI app at an enterprise level Ensure profitable delivery and great customer experience design the end-to-end solution, put together the right team and help them deliver as per established processes. Build an A team hire the required skills sets and nurture them in a supporting environment to develop strong delivery leaders for the Data Science Practice. Train and mentor staff and establish best practices and ways of working to enhance data science capabilities at Axtria. Operationalize an eco-system for continuous learning & development. Write white papers, collaborate with academia and participate in relevant speaker opportunities to continuously upgrade learning & establish Axtria's thought leadership in this space. Research, develop, evaluate and optimize newly emerging algorithms and technologies for relevant use cases in pharma commercial & clinical space. Extensive hands-on experience with Python, R, or Julia, focusing on data science and generative AI frameworks. Expertise in working with generative models such as GPT, DALL-E, Stable Diffusion, Codex, and MidJourney for various applications. Proficiency in fine-tuning and deploying generative models using libraries like Hugging Face Transformers, Diffusers, or PyTorch Lightning. Strong understanding of generative techniques, including GANs, VAEs, diffusion models, and autoregressive models. Experience in prompt engineering, zero-shot, and few-shot learning for optimizing generative AI outputs across different use cases. Expertise in managing generative AI data pipelines, including preprocessing large-scale multimodal datasets for text, image, or code generation. Experience in leveraging APIs and SDKs for generative AI services from OpenAI, Anthropic, Cohere, and Google AI. Expertise in defining generative AI strategies, aligning them with business objectives, and implementing solutions for scalable deployment. Knowledge of real-world applications of generative AI, such as text generation, code generation, image generation, chatbots, and content creation. Awareness of ethical considerations in generative AI, including bias mitigation, data privacy, and safe deployment practices. Good to have skills & competencies Proven ability to collaborate with cross-functional teams, including product managers, data scientists, and DevOps engineers, to deliver end-to-end generative AI solutions. Proven experience in leading teams focused on generative AI projects, mentoring ML engineers, and driving innovation in AI applications. Possessing robust analytical skills to address and model intricate business needs is highly advantageous, especially for those with a background in life sciences or pharmaceuticals.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Role description We are seeking an experienced Gen AI and LLM Developer to design, develop, and deploy generative AI models and large language models (LLMs) for advanced natural language processing (NLP) tasks. The ideal candidate will have 6-9 years of experience with LLM architectures (e.g., GPT, BERT), deep learning frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, GCP, Azure). Responsibilities include training and fine-tuning models, optimizing for performance, collaborating with cross-functional teams, and staying updated on the latest AI trends. Strong technical skills in Python, NLP techniques, model optimization, and distributed training are essential.Experience designing scalable system with Generative AI" and "Exposure to full stack development on .net or Java based platform

Hiring GenAI Python Developer with experience range 3 to 8 Years of experience Mandatory Skills: Python, LangChain techniques, LLM architectures, GPT, BERT, Streamlit, RAG mechanism Education: Btech/BE, BCA/MCA,Bsc/MSc

Immediate opening for "AI Architect (Generative AI)" Location : Remote Experience :- 15 to 23 yrs Quantaleap INC. is seeking a highly experienced AI Architect with deep expertise in Generative AI to drive innovative solution design and architecture for enterprise use cases. This role requires a strategic thinker with a strong foundation in AI/ML technologies and a proven ability to lead high-impact AI initiatives across diverse domains. Key Responsibilities: Architect end-to-end AI solutions leveraging Generative AI technologies (LLMs, diffusion models, transformers, etc.). Evaluate and recommend cutting-edge tools, frameworks, and models suitable for enterprise-grade deployments. Collaborate with cross-functional teams for RFP responses, technical proposals, and client presentations. Lead the development of scalable AI solutions from POC to production across multiple industry verticals. Guide technical teams on best practices in AI model development, fine-tuning, and deployment. Must-Have Skills: 15+ years of overall experience with a strong focus on AI/ML architecture In-depth knowledge of Generative AI technologies, including LLMs (GPT, BERT), GANs, and foundation models Experience in deploying AI models in cloud-native and on-prem environments Strong understanding of MLOps, data pipelines, and model lifecycle management Proven track record in presales, RFP responses, and enterprise solutioning Excellent stakeholder management and client-facing communication skills Interested can share their updated resume to anitha.mudaliyar@quantaleap.com

About the role PubMatic is looking for engineers with expertise in Generative AI and AI agent development. You will be responsible for building and optimizing advanced AI agents that leverage the latest technologies in Retrieval-Augmented Generation (RAG), vector databases, and large language models (LLMs). You will work on developing state-of-the-art solutions that enhance Generative AI capabilities and enable our platform to handle complex information retrieval, contextual generation, and adaptive interactions. What You'll Do Be the decision maker for using right set of tools & technology to solve specific problems. Guide & Mentor different team members for using generative AI tools and help the teams build various agents. Provide technical leadership and mentorship to engineering teams while collaborating with architects, product managers, and UX designers to create innovative AI solutions that address complex customer challenges. Lead the design, development, and deployment of AI-driven features. Drive end-to-end ownershipfrom feasibility analysis and design specifications to execution and releasewhile ensuring quick iterations based on customer feedback in a fast-paced Agile environment. Spearhead technical design meetings and produce detailed design documents that outline scalable, secure, and robust AI architectures. Ensure that the solutions are aligned with long-term product strategy and technical roadmaps. Implement and optimize LLMs for specific use cases, including fine-tuning models, deploying pre-trained models, and evaluating their performance. Develop AI agents powered by RAG systems, integrating external knowledge sources to improve the accuracy and relevance of generated content. Design, implement, and optimize vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient and scalable vector search, and work on various vector indexing algorithms. Create sophisticated prompts and fine-tune them to improve the performance of LLMs in generating precise and contextually relevant responses. Utilize evaluation frameworks and metrics (e.g., Evals) to assess and improve the performance of generative models and AI systems. Work with data scientists, engineers, and product teams to integrate AI-driven capabilities into customer-facing products and internal tools. Stay up to date with the latest research and trends in LLMs, RAG, and generative AI technologies to drive innovation in the company’s offerings. Continuously monitor and optimize models to improve their performance, scalability, and cost efficiency. We'd Love for You to Have Must Have Strong understanding of large language models (GPT, BERT, T5, etc.) and their underlying principles, including transformer architecture and attention mechanisms. Proven experience building AI agents with Retrieval-Augmented Generation to enhance model performance using external data sources (documents, databases). In-depth knowledge of vector databases, vector indexing algorithms, and experience with technologies like FAISS, Pinecone, Weaviate, or Milvus. Ability to craft complex prompts to guide the output of LLMs for specific use cases, enhancing model understanding and contextuality. Familiarity with Evals and other performance evaluation tools for measuring model quality, relevance, and efficiency. Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Experience with data preprocessing, vectorization, and handling large-scale datasets. Ability to present complex technical ideas and results to both technical and non-technical stakeholders. Curiosity to learn new things and be up to date with market trends in Gen AI technology. Nice-to-Have Experience in building AI agents using graph-based architectures, including knowledge graph embeddings and graph neural networks (GNNs). Experience with training small base models using custom data, including data collection, pre-processing, and fine-tuning models to specific domains or tasks. Familiarity with deploying AI models on cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Publication or contributions to research in AI, LLMs, or related fields. Proven record of building enterprise scale generative AI application with specific emphasis on accuracy & cost. Qualifications Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities.