138 Gpt Jobs - Page 4

Prompt Engineer & Generative AI Specialist (2-5 Years Experience - can be less experience too) Job Summary: We are seeking a skilled Prompt Engineer & Generative AI Specialist to optimize interactions with advanced language models and generative systems. You will work closely with AI product managers, data scientists, and software developers to craft and refine prompts, ensuring that model outputs align with business requirements and user expectations. Key Responsibilities: Prompt Development & Optimization: Design, test, and iterate on prompts for generative AI models to achieve accurate, relevant, and contextually appropriate outputs. Continuously refine and improve prompt strategies based on performance metrics and user feedback. Cross-Functional Collaboration: Partner with AI product managers, data scientists, and software engineers to integrate prompt engineering best practices into the product lifecycle. Translate business requirements into effective prompt frameworks and fine-tuning strategies. Research & Innovation: Stay up-to-date with the latest advancements in natural language processing (NLP) and generative AI methodologies. Experiment with novel prompt engineering techniques and contribute to internal knowledge bases and best practice guidelines. Quality & Ethical Oversight: Ensure ethical and responsible usage of generative AI by minimizing biases and adhering to established guidelines. Monitor and evaluate the performance of deployed prompts, making adjustments as needed to maintain high standards of quality and compliance. Documentation & Reporting: Document prompt engineering processes, experiments, and results to support knowledge sharing and continuous improvement. Provide regular updates and technical reports to stakeholders on performance and enhancement initiatives. Qualifications: Bachelors or Masters degree in Computer Science, Computational Linguistics, Data Science, or a related field. 25 years of experience in roles involving natural language processing, prompt engineering, or generative AI applications. Strong familiarity with large language models (e.g., GPT, ChatGPT) and generative AI frameworks. Proficiency in Python or other scripting languages for interacting with AI models. Proven experience in designing, testing, and optimizing prompts for various applications. Excellent analytical, problem-solving, and communication skills, with the ability to work effectively in cross-functional teams. A strong commitment to ethical AI practices and a deep understanding of AI fairness and bias mitigation strategies.

ROLE : Technical Lead & Mentor for AI Agent development • Ability to receive a project request, define a development plan, and identify the necessary tools and technologies. • Experience with LLMs (LLaMA, Mistral, GPT-like), RAG, fine-tuning, prompt engineering. • Agent architecture: task decomposition, memory, tool orchestration. • Languages: Python Preferred Skills Handling a team and deliver it with support and guidance. Agent Building Expertise : Hands-on experience in developing and deploying LLM agents with advanced features like tool integration, contextual memory systems, and feedback-driven learning us

Research & Development - AI Prompt Engineer Company Overview : We are Motive - the worlds leading provider of device management for mobile, fixed and IOT as well as managing the omni-channel customer experience which through its business logic drives actions, runs proactive care campaigns and improves customer satisfaction. Deployed by leading service providers worldwide, Motives device management and service management platform drive revenue, reduce customer care costs and automate each customer interaction. A relaunched brand with a long history and pedigree, at Motive we differentiate ourselves by creating innovative technical solutions, packaging them in ways that simplify operational complexity and time to market, and we never forget that we only succeed when our customers succeed. As a member of the Motive team, you will share a passion for being part of an exciting team of talented individuals, with a focus on building sustained long-term growth, and a fantastic place to work. Surrounded by individuals of exceptional ability and commitment, you will have the opportunity both to contribute to our continued business success, and to also invest in your own personal development. At Motive we hire only passionate team orientated people to join our business. Are you one of them? Position Summary: As a Research and Development AI Prompt Engineer, you will be at the forefront of creating and enhancing our software products. You will maximize the value of the R&D team’s delivery in research, design, prototyping, and development of new features and solutions. In this role, you will focus on developing, optimizing, and fine-tuning AI prompts for various natural language processing (NLP) and generative AI systems. You will work closely with software engineers to improve model outputs, refine AI understanding, and ensure the quality and accuracy of generated content. As an AI Prompt Engineer, you’ll play a key role in creating effective and efficient prompts that maximize the performance of AI models, particularly those focused on tasks such as anomaly detection, prediction, question answering, summarization, and more. Main Responsibility Areas: Prompt Design and Optimization Develop, test, and optimize natural language prompts for a variety of tasks, ensuring that AI models produce accurate, contextually relevant, and high-quality responses Experiment with different prompt engineering techniques, strategies, and styles to improve AI model outputs in various scenarios (e.g., anomaly detection, chatbot interactions, code generation, etc.) Analyze and refine existing prompts to ensure the desired AI model behavior AI Model Fine-tuning Collaborate with R&D and Professional Services software engineers to fine-tune pre-trained models using custom prompts for specific business requirements or user needs. Conduct prompt-based testing and validation to assess model performance and quality. Develop feedback loops to iteratively improve prompt designs based on model output quality. Performance Optimization: Analyze AI model outputs and fine tune prompts to improve accuracy and performance. Work closely with R&D software engineers to integrate prompt-engineered models into production systems and applications. Partner with product managers and UX/UI designers to understand user needs and ensure that AI-generated content aligns with user expectations and business goals. Document prompt engineering strategies, guidelines, and best practices. Maintain detailed records of model performance metrics and improvements over time. Provide regular updates to stakeholders on prompt optimization results and model performance. Stay up-to-date with the latest trends and techniques in AI, NLP, and prompt engineering. Create prototypes and proof-of-concept models to demonstrate the feasibility and potential of new ideas. Key Skills & Competencies: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Linguistics, AI, Data Science, or a related field. Advanced degrees and relevant certifications are a plus. Strong understanding of natural language processing (NLP) techniques and machine learning models (e.g., GPT, BERT, T5). Experience with AI prompt engineering, fine-tuning, and content generation tasks. Familiarity with large-scale pre-trained models, including transformers and generative models. Proficiency in programming languages such as Python, with a focus on libraries like Hugging Face, TensorFlow, PyTorch, or OpenAI’s API. Troubleshooting skills. Familiarity with AI platforms and cloud computing services (e.g., AWS, GCP, Azure). Expertise in Atlassian Jira and Confluence tools as well as Microsoft SharePoint Excellent verbal and written communication skills. Ability to articulate technical concepts to both technical and non-technical stakeholders. Ability to work effectively in a collaborative team environment. Strong interpersonal skills and a proactive attitude. Ability to quickly learn and apply new technologies. Flexibility to adapt to changing priorities and project requirements. Work Experience Requirements: Experience working with generative models such as GPT-3/4, BERT, or T5. Familiarity with conversational AI, chatbots, and interactive AI systems. Experience with data labeling, model evaluation, and data annotation. A strong portfolio showcasing previous work in prompt design or AI-driven NLP systems. Knowledge of AI ethics, bias mitigation, and content moderation techniques. Limitations and Disclaimer The above job description is meant to describe the general nature and level of work being performed; it should not be construed as an exhaustive list of all responsibilities, duties and skills required for the position. All job requirements are subject to possible modification to reasonably accommodate individuals with disabilities. Some requirements may exclude individuals who pose a direct threat or significant risk to the health and safety of themselves or other employees. This job description in no way states or implies that these are the only duties to be performed by the employee occupying this position. Employees will be required to follow any other job-related instructions and to perform other job-related duties requested by their manager.

Roles and Responsibilities: Model Expertise : Work with transformer models such as GPT , BERT , T5 , RoBERTa , and others for a variety of NLP tasks, including text generation, summarization, classification, and translation. Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering. Prompt Engineering : Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. Iterate on prompts to optimize model performance. Instruction-Based Prompting : Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives. Zero-shot, Few-shot, Many-shot Learning : Utilize zero-shot , few-shot , and many-shot learning techniques to improve model performance without the need for full retraining. Chain-of-Thought (CoT) Prompting : Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations. Model Evaluation : Use evaluation metrics such as BLEU , ROUGE , and other relevant metrics to assess and improve the performance of models for various NLP tasks. Model Deployment : Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications. Bias Awareness : Be aware of and mitigate issues related to bias , hallucinations , and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs. Collaboration : Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions. Must Have Skill Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks , with a focus on text generation , summarization , question answering , classification , and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer) , BERT (Bidirectional Encoder Representations from Transformers) , T5 (Text-to-Text Transfer Transformer) , RoBERTa , and similar models. Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation , summarization , question answering , classification , and translation . Familiarity with concepts like attention mechanisms , context windows , tokenization , and embedding layers . Awareness of biases , hallucinations , and knowledge cutoffs that can affect LLM performance and output quality. Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. Experience in instruction-based prompting Use of zero-shot , few-shot , and many-shot learning techniques for maximizing model performance without retraining. Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. Experience in training, fine-tuning, and deploying machine learning models in an NLP context. Understanding of model evaluation metrics (e.g., BLEU, ROUGE) Qualification: BE/B.Tech or Equivalent degree in Computer Science or related field. Excellent communication skills in English, both verbal and written

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Pune Location-12th July 2025(Saturday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Pune Date of drive- 12th July 2025(Saturday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

Job Description: We are looking for an experienced Data Scientist with over 5 years of hands-on expertise in machine learning , particularly in clustering and classification tasks . The ideal candidate will have practical experience working with Large Language Models (LLMs) such as GPT, especially in areas like prompt engineering, summarization, and fine-tuning . Exposure to life sciences or biomedical datasets is highly desirable. Key Responsibilities: Design and implement machine learning models for clustering and classification. Work with LLMs for experimentation, evaluation, and fine-tuning. Apply data science techniques to healthcare or biomedical datasets. Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions. Communicate findings clearly through reports, dashboards, and presentations. Must-Have Skills: 5+ years of experience in data science and machine learning. Strong proficiency in clustering and classification techniques. Hands-on experience with Python and libraries like Scikit-learn, Pandas, NumPy. Experience working with LLMs (e.g., GPT) for real-world use cases. Exposure to healthcare, clinical, or life sciences datasets (preferred). Strong statistical analysis and data interpretation skills. Excellent communication and problem-solving abilities. Preferred Candidate Profile: Immediate joiners or candidates with a notice period of 015 days . Passionate about applying AI/ML to real-world problems in life sciences. Comfortable working in a fast-paced, collaborative environment.

Role & responsibilities Skill - AI/ML python Engineer Exp - 5+ Location - Gurgaon Notice period - Immediate joiners We are hiring a senior Software Engineer with 5+ years of strong experience in Python development and a solid foundation in AI/ML concepts and practical implementation. The role requires hands-on work with Generative AI libraries and Large Language Models (LLMs), along with a good understanding of the machine learning lifecycle. Experience with AWS cloud services is preferred. Key Responsibilities: Develop AI/ML applications using Python with a focus on Generative AI. Work with libraries like OpenAI, Hugging Face Transformers, and related GenAI tools. Apply concepts related to Large Language Models (LLMs) such as GPT, Claude, etc. Build and manage ML workflows including data preprocessing, model training, evaluation, and deployment. Collaborate with cross-functional teams to integrate AI features into scalable solutions. Required Skills: Strong Python development experience with a focus on AI/ML. Hands-on experience with GenAI libraries like OpenAI, Hugging Face Transformers, etc. Understanding and practical knowledge of LLMs (e.g., GPT, Claude) and associated concepts. Familiarity with the ML lifecycle preprocessing, training, evaluation, and deployment. Preferred: Experience working with AWS cloud platform and its services.

About the role We are seeking a skilled Social Media Manager to join our team and elevate JLL's digital presence in the B2B space. In this role, you will develop and execute content strategies across various social media channels, supporting our global real estate services brand. You'll craft compelling, on-brand copy for platforms like LinkedIn, Facebook, Instagram, and Twitter, while adhering to JLL's brand voice guidelines. Collaborating with cross-functional teams, you'll create engaging content that aligns with our marketing objectives and resonates with our target audience of commercial real estate professionals, investors, and corporate clients. You'll also coordinate social media campaigns, analyze performance metrics, and optimize our content strategy. Your expertise in B2B social media strategies and ability to translate complex real estate concepts into engaging social content will be crucial in showcasing JLL's industry leadership. Responsibilities: Develop compelling, on-brand post copy, video scripts and description copy for various social media platforms including but not limited to LinkedIn, Facebook, Instagram, Twitter, etc. Ensure adherence to JLL's brand voice/tone guidelines, governances, and processes for social media Collaborate with the marketing team to align social media content with overall marketing strategies and JLL's business objectives Adapt tone and style to suit different platforms and target audiences from a B2B perspective, focusing on commercial real estate professionals, investors, and corporate clients Write and edit blog posts, articles, and other long-form content for social sharing, highlighting JLL's expertise in real estate services, market trends, and industry insights Monitor social media trends in the commercial real estate and professional services sectors, incorporating them into content strategies Analyze social media metrics and adjust content strategies accordingly to improve engagement and reach within our target B2B audience Create content that showcases JLL's thought leadership in areas such as workplace strategy, sustainability in real estate, and PropTech innovations Collaborate with regional teams to ensure social media content is relevant and localized when necessary Support the promotion of JLL's research reports, whitepapers, and market analyses through social media channels Coordinate and support social media campaigns, ensuring alignment with broader marketing initiatives and business goals Manage day-to-day social media activities, including content scheduling, community engagement, and platform-specific optimizations Requirements: Bachelor's degree in marketing, communications, or a related field. Proven experience of 2-3 years in a copywriting or similar role. Strong understanding of current social media & content landscape and B2B best practices across that landscape Familiar with GPT & AI for efficient content creation through reusable prompts to create efficient process Excellent writing and editing skills with a strong grasp of grammar and punctuation Proven ability to write engaging, concise copy for various social media platforms Strong project management and organizational skills, with the ability to manage multiple initiatives simultaneously. Ability to collaborate effectively with cross-functional teams. Attention to detail and a commitment to delivering high-quality content. Self-motivated, with a passion for staying up-to-date with industry trends and emerging technologies.

We are seeking a highly skilled and innovative Data Scientist with a strong focus on Generative AI, NLP, and Large Language Models (LLMs). The ideal candidate will design, develop, and deploy end-to-end data science solutions that harness the power of advanced ML, deep learning, and Gen AI technologies to drive real-world impact. Key Responsibilities: Design and implement scalable data science solutions using Generative AI, NLP, and ML techniques. Develop, fine-tune, and evaluate Large Language Models (LLMs) such as GPT, BERT, and similar architectures. Analyze structured and unstructured data to generate actionable insights for business problems. Collaborate cross-functionally with engineering, product, and business teams to integrate AI models into production systems. Conduct cutting-edge research in Gen AI and deep learning; evaluate and apply recent advancements. Build and maintain robust pipelines for model training, evaluation, monitoring, and deployment. Communicate complex technical findings clearly to technical and non-technical stakeholders. Required Skills & Qualifications: Strong hands-on experience with Generative AI, LLMs (e.g., OpenAI, Hugging Face Transformers, etc.). Proven expertise in core NLP tasks: text classification, summarization, named entity recognition, sentiment analysis, etc. Proficient in Python and related libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch. Experience developing, validating, and deploying ML models in production environments. Familiarity with vector databases (e.g., FAISS, Pinecone), embeddings, and semantic search. Exposure to cloud platforms like AWS, Azure, or GCP, and MLOps tools/workflows (CI/CD, model monitoring, etc.). Preferred Qualifications: Experience in prompt engineering, Retrieval-Augmented Generation (RAG), or fine-tuning/customizing LLMs. Contributions to AI research papers, open-source projects, or participation in ML competitions (e.g., Kaggle) is a plus. Knowledge of responsible AI practices, model interpretability, and bias mitigation techniques.

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.

Position Overview : We are seeking an experienced NLP & LLM Specialist to join our team. The ideal candidate will have deep expertise in working with transformer-based models, including GPT, BERT, T5,RoBERTa, and similar models. This role requires experience in fine-tuning these pre-trained models on domain-specific tasks, as well as crafting and optimizing prompts for natural language processing tasks such as text generation, summarization, question answering, classification, and translation. The candidate should be proficient in Python and familiar with NLP libraries like Hugging Face, SpaCy, and NLTK, with a solid understanding of model evaluation metrics. Roles and Responsibilities : - Model Expertise : - Work with transformer models such as GPT, BERT, T5, RoBERTa, and others for a variety of NLP tasks, including text generation, summarization, classification, and translation. - Model Fine-Tuning: Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering. - Prompt Engineering: Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. - Iterate on prompts to optimize model performance. - Instruction-Based Prompting: Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives. - Zero-shot, Few-shot, Many-shot Learning: Utilize zero-shot, few-shot, and many-shot learning techniques to improve model performance without the need for full retraining. - Chain-of-Thought (CoT) Prompting: Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations. - Model Evaluation: Use evaluation metrics such as BLEU, ROUGE, and other relevant metrics to assess and improve the performance of models for various NLP tasks. - Model Deployment: Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications. - Bias Awareness: Be aware of and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs. - Collaboration: Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions. Must Have Skill : - Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks, with a focus on text generation, summarization, question answering, classification, and similar tasks. - Expertise in transformer models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), T5 (Text-to-Text Transfer Transformer), RoBERTa, and similar models. - Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. - Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation, summarization, question answering, classification, and translation. - Familiarity with concepts like attention mechanisms, context windows, tokenization, and embedding layers. - Awareness of biases, hallucinations, and knowledge cutoffs that can affect LLM performance and output quality. - Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. - Experience in instruction-based prompting - Use of zero-shot, few-shot, and many-shot learning techniques for maximizing model performance without retraining. - Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. - Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. - Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. - Proficiency in Python and experience with NLP libraries (e.g , Hugging Face, SpaCy, NLTK). - Experience with transformer-based models (e.g , GPT, BERT, T5) for text generation tasks. - Experience in training, fine-tuning, and deploying machine learning models in an NLP context. - Understanding of model evaluation metrics (e.g , BLEU, ROUGE) Qualification : - BE/B.Tech or Equivalent degree in Computer Science or related field. - Excellent communication skills in English, both verbal and written.

Role: Artificial Intelligence Engineer Location Bangalore (Ashok Nagar) Experience : 3 to 5 years Education : Bachelor's/Masters Degree in Technology. Salary : Negotiable Job Type : Full Time (On Role) Mode of Work : Work from Office Job Description We are looking for an experienced AI Engineer to join our team and develop advanced AI solutions. The role involves designing, training, and deploying machine learning models to address complex business challenges. Proficiency in Python, TensorFlow, and experience working with large datasets are critical for success. Preferred Skills: Proficiency in Python and NLP libraries such as OpenAIs GPT, LangChain, etc. Knowledge of Large Language Models (LLMs) and fine-tuning techniques Retrieval-Augmented Generation (RAG) for improving AI response Experience in API development and hosting (IIS preferred) Basic understanding of SQL Expertise in training, tuning, deploying, and leveraging models with SQL databases Technical Skills: Proficiency in programming languages such as Python, R, or Java Ability to integrate AI models into existing systems and applications Strong knowledge of machine learning algorithms (e.g., regression, classification, clustering) Experience with deep learning frameworks such as TensorFlow and PyTorch Expertise in data manipulation and cleaning techniques Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment Interested candidates kindly share your CV and below details to usha.sundar@adecco.com 1) Present CTC (Fixed + VP) - 2) Expected CTC - 3) No. of years experience - 4) Notice Period - 5) Offer-in hand - 6) Reason of Change - 7) Present Location -

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.

Experience: 4 + years Expected Notice Period: 15 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Office (Bengaluru) Placement Type: Full Time Indefinite Contract(40 hrs a week/160 hrs a month) What do you need for this opportunity? Must have skills required: Design patterns, Scalable Systems, Software Architecture, APIS, GPT, AWS, Django, Postgre SQL, Python What Were Looking For Strong Python & Django expertise Youve built scalable backend systems and APIs using Django & Django REST Framework and have at least 4 years of experience Scalable core platform development You write scalable and maintainable core platform code by leveraging appropriate design patterns and software architecture principles. Platform integration experience Youve worked with integrating multiple third-party platforms and APIs. PostgreSQL & data modeling expertise You are highly skilled in PostgreSQL and can design efficient, scalable data models. Cloud-native mindset Comfortable working with AWS, deploying, and managing cloud infrastructure. Founder Mindset You focus on impact, ensuring your build is reliable, efficient, and scalable Collaborative & accountable You take ownership, communicate clearly, and work well across teams. What Youll Do Build and optimize backend services for Saturn AI. Obsess over performance, security, and reliability across our systems. Own projects end-to-end, from design to deployment. Orbit together Candor, impact, and teamwork at the core.

Title: ML Engineer Location: Chennai (Hybrid) Experience: 3 - 12 Years Notice Period: 15-20 Days Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Lang chain/ Lang graph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

We seek a Senior AI Scientist with strong ML fundamentals and data engineering expertise to lead the development of scalable AI/LLM solutions. You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices. Key Responsibilities 1. AI/LLM Development: o Fine-tune and optimize LLMs (e.g., GPT, Llama) and traditional ML models for production. o Implement retrieval-augmented generation (RAG), vector databases, and orchestration tools (e.g., LangChain). 2. Data Engineering: o Build scalable data pipelines for unstructured/text data (e.g., Spark, Kafka, Airflow). o Optimize storage/retrieval for embeddings (e.g., pgvector, Pinecone). 3. MLOps & Deployment: o Containerize models (Docker) and deploy on cloud (AWS/Azure/GCP) using Kubernetes. o Design CI/CD pipelines for LLM workflows (experiment tracking, monitoring). 4. Collaboration: o Work with DevOps to optimize latency/cost trade-offs for LLM APIs. o Mentor junior team members on ML engineering best practices. Required Skills & Qualifications Education: MS/PhD in CS/AI/Data Science (or equivalent experience). Experience: 6+ years in ML + data engineering, with 2+ years in LLM/GenAI projects.

JOB DESCRIPTION Job Title - Product Manager Department/Group - Product Management Location - Bangalore Experience - 6 - 10 Years Looking for candidates with Experience in HR Tech, and B2C Product Experience Summary entomo is an Equal Opportunity Employer. The company promotes and supports a diverse workforce at all levels across the Company. The Company ensures that its associates or potential hires, third-party support staff and suppliers are not discriminated against, directly or indirectly, as a result of their colour, creed, cast, race, nationality, ethnicity or national origin, marital status, pregnancy, age, disability, religion or similar philosophical belief, sexual orientation, gender or gender reassignment, etc. Product Manager who is passionate about building products that customers love. You will join a dynamic and fast-paced environment and work with cross-functional teams to design, build and roll-out products that deliver the companys vision and strategy. As a product manager on our dynamic and driven team, you will be responsible for owning the development and delivery of new features and enhancements in our SaaS product. Develops products by identifying potential products; conducting market research; generating product requirements; determining specifications, production timetables, pricing, and time-integrated plans for product introduction, developing marketing strategies. Responsibilities Gain a deep understanding of customer experience, identify and fill product gaps and generate new ideas that grow market share, improve customer experience and drive growth. Create buy-in for the product vision both internally and with key external partners. Work with Product Owners and Engineering team to Translate product strategy into detailed requirements and prototypes. Scope and prioritize features and releases based on business and customer impact. Work closely with engineering teams to deliver with quick time-to-market and optimal resources. Drive product Releases including working with Front end teams Customer success, Sales team, executives, and other product management team members. • Evaluate promotional plans to ensure that they are consistent with product line strategy and that the message is effectively conveyed. Act as a product evangelist to build awareness and understanding. Represent the company by visiting customers to solicit feedback on company products and services. Drives the product and is responsible for the feature releases are in the product both on Mobile and Web Platforms. Determine customers' needs and desires by specifying the research needed to obtain market information. Recommend the nature and scope of present and future product lines by reviewing product specifications and requirements, appraising new product ideas and/or product or packaging changes. Assess market competition by comparing the company's product to competitors' products. Obtain feedback from customers/Customer Success teams and enhance product. Have clear short term and long-term roadmap of the overall product. Brings new products to market by analysing proposed product requirements and product development programs, preparing effort estimates, establishing time schedules with engineering. Maintains professional and technical knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; participating in professional societies. Contributes to team effort by accomplishing related results as needed. Essential Skills Experience working with Generative AI technologies such as GPT (Generative Pretrained Transformer) models is highly desirable. Proven track record of managing all aspects of a successful product throughout its lifecycle in BI & Analytics space. Expertise in any of the leading BI & Analytics tools Tableau, Qlikview, Sisense, Power BI or similar. Expertise in Data Engineering, Data modelling, Data / Text Analytics, Data visualization, Data connectors. Sound knowledge or experience in Machine learning, Deep Learning, Python, or any of the ML products Proven ability to develop product and marketing strategies and effectively communicate recommendations to executive management. Expertise in Product Management, Product Development, Requirements Analysis, Planning, Competitive Analysis and Strategy in BI & Analytics space Expertise in SDLC, Agile Scrum methodology in product development & product support. Expert in creating User Stories in Task management tools like Jira. Excellent analytical and problem-solving skills. Passionate about building class products on both web and mobile. Strong leader, self-starter and proven team player in a high achievement-oriented environment Excellent relationship skills, ability to establish credibility and rapport with technical and non-technical team members and to work collaboratively and cross functionally. Good understanding of developing Performance Management/HRMS products and technologies. Must be tech-savvy with the ability to understand technology capabilities and processes. Ability to juggle multiple priorities and thrive in a fast-paced environment. Team player Competenc Strategy Development Team Management Technical Competence Leadership skills Educational Qualification and Experience Required MS/ME/BS/BE degree in Computer Science, Engineering or equivalent preferred. MBA Graduate Minimum 6 - 10 years of Product experience

Job Overview: 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. Eligibility Criteria Masters/PhD in CSE/IT from Tier 1 institute Minimum 12+ years of relevant experience in building software applications in data and analytics field. We will provide– (Employee Value Proposition) Offer an inclusive environment that encourages diverse perspectives and ideas Delivering challenging and unique opportunities to contribute to the success of a transforming organization Opportunity to work on technical challenges that may impact on geographies Vast opportunities for self-development: online Axtria Institute, knowledge sharing opportunities globally, learning opportunities through external certifications Sponsored Tech Talks & Hackathons Possibility of relocating to any Axtria office for short and long-term projects Benefit package: -Health benefits -Retirement benefits -Paid time off -Flexible Benefits -Hybrid /FT Office/Remote Axtria is an equal-opportunity employer that values diversity and inclusiveness in the workplace. Who we are Axtria 14 years journey Axtria, Great Place to Work Life at Axtria Axtria Diversity

Should have exp with Agen c frameworks like Crew AI, Lang, graph, Swarm AI etc. Must have contributed significantly to the development of at least 2 Gen AI projects. Must have worked with mul ple Gen AI models including GPT, Claude, Qwen, Lama etc.

Here is how, through this exciting role, YOU will contribute to BMC's and your own success: Assist in developing AI-powered QA automation tools using LLMs Collaborate with QA engineers to understand test requirements and translate them into automated scripts Use LLMs to generate test cases, validation scripts, and test data automatically Maintain, debug, and optimize automated test scripts and frameworks Integrate LLM-based solutions into existing CI/CD pipelines and QA workflows Document automation processes and assist with training teams on new AI-driven QA tools Continuously research and apply advancements in LLMs and AI for QA improvements To ensure youre set up for success, you will bring the following skillset & experience: You have 3-5 years for software development experience You have experince of basic programming skills in Python, JavaScript, or relevant languages for automation You have understanding of software testing concepts and QA automation tools (e.g., Selenium, Cypress, JUnit) You have some experience in AI, NLP, or machine learning concepts You are familiarity with version control systems such as Git You have strong problem-solving skills and ability to learn quickly in a dynamic environment Whilst these are nice to have, our team can help you develop in the following skills: Experience with AI/ML frameworks like PyTorch or TensorFlow Familiarity with Large Language Models such as GPT, BERT, or OpenAI APIs Knowledge of continuous integration tools (Jenkins, GitHub Actions) Exposure to writing or maintaining automated test frameworks Understanding of cloud environments for deploying automation solutions

8+ years of total experience with 5+ years of professional experience in AI, ML or a related field. Master's or PhD in Computer Science, Mathematics, AI or a related field. Good mathematical understanding of machine learning and deep learning algorithms. Advanced knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability. Experience with Natural Language Processing, Deep Learning, and Computer Vision techniques. Proficiency in programming languages such as Python or Scala, along with experience using DL frameworks like TensorFlow, PyTorch etc. Experience working with large data sets and writing efficient code capable of processing large data streams at speed. Experience in program leadership, governance, and change enablement Understand client challenges and propose solutions based on AI/GenAI capabilities. Analyze and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards. Work on functional design, process design, prototyping, testing, training, and defining support procedures, in collaboration with data engineering team and executive leadership. Train and deploy AI models to solve complex business problems or automate processes. Convert AI/ML models into APIs to be used in other applications. Manage a team in implementing AI solutions and developing products. Collaborate with external partners, such as research institutions or universities, to explore innovative AI approaches and foster collaborative research projects. Ensure compliance with data privacy regulations and ethical guidelines while working with sensitive and confidential data. Stay up to date with the latest developments in machine learning and AI. Experience working with Azure Data & AI services. Experience with MLOps tools like MLFLow, Azure MLOps or similar tools. High level of ownership and creative problem solving under resource constraints. Excellent verbal and written communication skills. Ability to interact with C-Level executives

Curious about the role ? Generative AI & NLP Development : Design, develop, and deploy advanced applications and solutions using Generative AI models (e.g., GPT, LLaMA, Mistral) and NLP algorithms to solve business challenges and unlock new opportunities for our clients. Model Customization & Fine-Tuning: Apply state-of-the-art techniques like LoRA, PEFT, and fine-tuning of large language models to adapt solutions to specific use cases, ensuring high relevance and impact. Innovative Problem Solving : Leverage advanced AI methodologies to tackle real-world business problems, providing creative and scalable AI-powered solutions that drive measurable results. Data-Driven Insights: Conduct deep analysis of large datasets, uncovering insights and trends that guide decisionmaking, improve operational efficiencies, and fuel innovation. Cross-Functional Collaboration: Work closely with Consulting, Engineering, and other teams to integrate AI solutions into broader business strategies, ensuring the seamless deployment of AI-powered applications. Client Engagement: Collaborate with clients to understand their unique business needs, provide tailored AI solutions, and educate them on the potential of Generative AI to drive business transformation. What do we expect? Generative AI & NLP Expertise: Extensive experience in developing and deploying Generative AI applications and NLP frameworks, with hands-on knowledge of LLM fine-tuning, model customization, and AI-powered automation. Hands-On Data Science Experience: 6+ years of experience in data science, with a proven ability to build and operationalize machine learning and NLP models in real-world environments. AI Innovation: Deep knowledge of the latest developments in Generative AI and NLP, with a passion for experimenting with cutting-edge research and incorporating it into practical solutions. Problem-Solving Mindset: Strong analytical skills and a solution-oriented approach to applying data science techniques to complex business problems. Communication Skills: Exceptional ability to translate technical AI concepts into business insights and recommendations for non-technical stakeholders.

Role & responsibilities Develop, test, and maintain backend services using Python and frameworks such as FastAPI or Flask . Implement and optimize LLM-based applications using models like OpenAI (GPT-4o) , Gemini , LLaMA , etc. Work on RAG implementations , including integration with vector databases and prompt engineering strategies. Design, build, and maintain database connectivity using SQL for infrastructure-level applications. Develop and deploy containerized applications using Docker , Git , GitHub , and integrate with CI/CD pipelines . Deploy and manage applications on cloud platforms ( AWS , Azure , GCP ). Ensure clean code practices including unit testing , error handling , Python best practices , and design patterns . Collaborate with cross-functional teams including Product, Data Science, and DevOps for end-to-end solution delivery. Preferred candidate profile Strong proficiency in Python programming . Familiarity with FastAPI , Flask , or similar web frameworks. Experience with SQL databases and connection management. Hands-on with LLMs and RAG workflows (OpenAI GPT, Gemini, LLaMA, etc.). Understanding of vector databases such as FAISS, Pinecone, or similar. Proficiency with Git , GitHub , and CI/CD pipelines . Experience with Docker for containerization. Exposure to any of the major cloud platforms AWS , Azure , or GCP . Ability to write unit test cases , implement robust error handling , and follow design patterns . Clear understanding of enterprise software development best practices . Someone who have experience working with Banking or Financial Services projects/clients. Immediate Joiner or someone serving notice period.

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 Collaborate with engineers, architects, product managers, and UX designers to develop innovative AI solutions for new customer use-cases. Work independently and iterate quickly based on customer feedback to make product tweaks. 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 companys 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. 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. Qualifications Should have a bachelors degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities. If interested, please visit the link below to apply: https://pubmatic.com/job/?gh_jid=4615220008

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 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 companys 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. 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. Qualifications Should have a bachelors degree in engineering (CS / IT) or equivalent degree from a well-known Institutes / Universities. If interested, please visit the link below to apply: https://pubmatic.com/job/?gh_jid=4615235008