181 Pinecone Jobs - Page 4

You should have a minimum of 4 years of experience for this role. Your key responsibilities will include proficiency in Python (preferred), along with a working knowledge of TypeScript/Node.js, Go, or Java. You should have hands-on experience in developing REST APIs, GraphQL endpoints, and/or gRPC-based services. It is expected that you are familiar with integrating LLMs like GPT-4, Claude, Gemini, Mistral, or LLaMA. Additionally, exposure to frameworks such as LangChain, LlamaIndex, or CrewAI is desirable. A basic understanding of vector databases and semantic search tools (e.g., FAISS, Pinecone) is also required. Moreover, experience working in cloud environments (AWS, GCP, Azure) and with containerization tools (Docker, Kubernetes) is essential for this role. Ideally, you should have backend or full-stack development experience, with a focus on working with Generative or Agentic AI solutions.,

As a Generative AI Lead, you will be responsible for spearheading the design, development, and implementation of cutting-edge GenAI solutions within enterprise-grade applications. Your role will encompass leveraging your expertise in Large Language Models (LLMs), prompt engineering, and scalable AI system architecture, coupled with hands-on experience in MLOps, cloud technologies, and data engineering. Your primary responsibilities will include designing and deploying scalable and secure GenAI solutions utilizing LLMs such as GPT, Claude, LLaMA, or Mistral. You will lead the architecture of Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, Weaviate, FAISS, or ElasticSearch. Additionally, you will be involved in prompt engineering, evaluation frameworks, and collaborating with cross-functional teams to integrate GenAI into existing workflows and applications. Moreover, you will develop reusable GenAI modules for various functions like summarization, Q&A bots, and document chat, while leveraging cloud-native platforms such as AWS Bedrock, Azure OpenAI, and Vertex AI for deployment and optimization. You will ensure robust monitoring and observability across GenAI deployments and apply MLOps practices for CI/CD, model versioning, validation, and research into emerging GenAI trends. To be successful in this role, you must possess at least 8 years of overall AI/ML experience, with a focus of at least 3 years on LLMs/GenAI. Strong programming skills in Python and proficiency in cloud platforms like AWS, Azure, and GCP are essential. You should also have experience in designing and deploying RAG pipelines, summarization engines, and chat-based applications, along with familiarity with MLOps tools and evaluation metrics for GenAI systems. Preferred qualifications include experience with fine-tuning open-source LLMs, knowledge of multi-modal AI, familiarity with domain-specific LLMs, and a track record of published work or contributions in the GenAI field. In summary, as a Generative AI Lead, you will play a pivotal role in driving innovation and excellence in the development and deployment of advanced GenAI solutions, making a significant impact on enterprise applications and workflows.,

We are looking for a highly motivated and skilled Generative AI (GenAI) Developer to join our dynamic team. You will be responsible for building and deploying GenAI solutions using large language models (LLMs) to address real-world business challenges. The role involves working with cross-functional teams, applying prompt engineering and fine-tuning techniques, and building scalable AI-driven applications. A strong foundation in machine learning, NLP, and a passion for emerging GenAI technologies is essential. Responsibilities Design, develop, and implement GenAI solutions using large language models (LLMs) to address specific business needs using Python. Collaborate with stakeholders to identify opportunities for GenAI integration and translate requirements into scalable solutions. Preprocess and analyze unstructured data (text, documents, etc.) for model training, fine-tuning, and evaluation. Apply prompt engineering, fine-tuning, and RAG (Retrieval-Augmented Generation) techniques to optimize LLM outputs. Deploy GenAI models and APIs into production environments, ensuring performance, scalability, and reliability. Monitor and maintain deployed solutions, incorporating improvements based on feedback and real-world usage. Stay up to date with the latest advancements in GenAI, LLMs, and orchestration tools (e.g., LangChain, LlamaIndex). Write clean, maintainable, and well-documented code, and contribute to team-wide code reviews and best practices. Requirements: Minimum 2 years of relevant Proven experience as an AI Developer. Proficiency in Python. Good understanding multiple of Gen AI models (OpenAI, LLAMA2, Mistral) and ability to setup up local GPTs using ollama, lm studio etc. Experience with LLMs, RAG (Retrieval-Augmented Generation), and vector databases (e.g., FAISS, Pinecone). Multi agents frameworks to create workflows. Langchain or similar tools like lamaindex, langgraph etc. Knowledge of Machine Learning frameworks, libraries, and tools. Excellent problem-solving skills and solution mindset. Strong communication and teamwork skills. Ability to work independently and manage ones time effectively. Experience with any of cloud platforms (AWS, GCP, Azure).,

As a Lead Machine Learning Engineer, you will be responsible for leading the design, development, and deployment of cutting-edge ML models and systems. Your primary focus will be collaborating with the engineering and product teams to create solutions tailored to financial markets. You will work closely with cross-functional teams to seamlessly integrate ML solutions into various products. Your role will involve driving innovation through continuous research and application of the latest ML techniques and technologies. You will take the lead in developing end-to-end ML workflows, emphasizing LLM-based architectures and applications. Fine-tuning and optimizing both open-source and proprietary LLMs for practical use cases will be a key aspect of your responsibilities. You will also apply advanced techniques such as retrieval-augmented generation (RAG), prompt engineering, and model compression to enhance performance and efficiency. Additionally, you will collaborate with product and engineering teams to incorporate LLMs into customer-facing applications. Guiding data collection, setting up training pipelines, and deploying infrastructure will be integral parts of your role. It is crucial to stay updated on the latest advancements in the LLM and generative AI space to evaluate their relevance to ongoing projects. To excel in this role, you should possess strong expertise in Python, ML frameworks (such as TensorFlow, PyTorch), and cloud platforms (AWS/GCP/Azure). A solid background in ML/NLP, especially in developing and delivering LLM-powered products, is essential. Familiarity with tools like Hugging Face Transformers, LangChain, OpenAI/Anthropic APIs, vector databases (e.g., Pinecone, Weaviate), and orchestration frameworks is highly beneficial. Furthermore, a deep understanding of model evaluation, performance optimization, and responsible AI principles is required. The ability to thrive in fast-paced, cross-functional environments is crucial for success in this role. While not mandatory, knowledge and exposure to financial markets would be advantageous for this position.,

As a member of our team, you will play a key role in supporting the design and refinement of prompts for large language models (LLMs) to ensure accurate outputs. Your responsibilities will include assisting in data labeling, text preprocessing, and data preparation for NLP workflows. Additionally, you will help evaluate prompt performance, suggest improvements based on testing results, and contribute to small-scale NLP experiments and proof-of-concept studies. It will be essential for you to document prompt variations and results clearly for future reference and collaborate effectively with senior engineers and data scientists to integrate prompts into applications. You will also assist in maintaining prompt libraries, managing version control, and participate in team brainstorming sessions for new NLP features or improvements. To excel in this role, you must have at least 1 year of experience in natural language processing and prompt engineering focused on LLMs. Hands-on experience in Python, with a proficiency in leveraging NLTK or spaCy for text processing, is a must. Exposure to OpenAI API or similar LLM services for prompt design and testing, as well as familiarity with Hugging Face Transformers for basic fine-tuning and experimentation, will be valuable assets. Additionally, having an understanding of LangChain (basic) and Pinecone for vector-based retrieval tasks, along with experience using tools like Streamlit or Gradio for simple NLP demos, will be considered a definite advantage in this role.,

At InfoBeans, we believe in making other people's lives better through our work and everyday interactions. As an AI ML Lead based in Indore/Pune with over 10 years of experience in Artificial Intelligence, your role will involve designing AI solutions using both traditional ML and GenAI approaches based on problem needs. You will lead the end-to-end implementation of ML projects, including data preparation, model development, deployment, and monitoring. Additionally, you will be responsible for building GenAI-based applications using LLMs, embeddings, and multi-step reasoning frameworks like LangChain and LangGraph. Your responsibilities will also include conducting research and proof-of-concepts to evaluate emerging GenAI models and techniques, guiding and mentoring junior engineers, and reviewing designs, architecture, and code quality. You will develop fine-tuned and instruction-tuned LLMs using platforms like Hugging Face, OpenAI, and Cohere, and build agentic AI systems involving tool use, memory, and reasoning frameworks. Furthermore, you will ensure that AI models are robust, explainable, and cost-efficient in production and collaborate with stakeholders to understand business goals and translate them into technical solutions. Communication of complex AI concepts to both technical and non-technical audiences is also a key aspect of this role. This strategic position will allow you to play a crucial part in shaping the AI offerings of the company, guiding teams, and solving complex problems using both modern and established AI techniques. In this role, you will enjoy a competitive package and work in an open workspace surrounded by smart and pragmatic team members. You will have ample opportunities for professional and personal growth in a learning culture that values teamwork, collaboration, diversity, excellence, compassion, openness, and ownership. To excel in this role, we are looking for an experienced AI/ML Engineer with a strong background in both traditional Machine Learning and Generative AI. You should have extensive experience in classical AI/ML and at least 3 years in GenAI, totaling 10 years of experience with the ability to design, research, and build scalable AI solutions across domains. Your expertise should include 6-7 years in traditional ML/DL and 2-3 years in Generative AI. Proficiency with Python, scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers is essential, along with an understanding of the ML lifecycle and deep experience with LLMs and related tools. Strong communication, presentation skills, and a research mindset are also important for this role. If you possess the ability to quickly learn and adapt to new GenAI technologies, assess trade-offs between classic and generative AI techniques, and recommend the best-fit approach, we would like you to join our team and contribute to our AI initiatives.,

You should have a minimum of 5 years of experience in AI/ML with at least 2+ years in NLP, LLMs, and Generative AI. Your expertise should include ML architecture design, end-to-end model development, and deployment in production systems. Proficiency in Python is essential, along with deep experience in ML libraries and frameworks like TensorFlow, PyTorch, Hugging Face, and LangChain. A sound knowledge of transformer models, embeddings, tokenization, and vector databases such as FAISS and Pinecone is required. Experience with cloud-native AI solutions on AWS, Azure, or GCP is preferred. Familiarity with MLOps, model versioning, containerization using Docker, and orchestration tools like Kubeflow and MLflow is a plus. Your responsibilities will include architecting and implementing end-to-end machine learning and Generative AI solutions for real-world applications. You will design, fine-tune, and deploy models using transformers, embeddings, tokenization, and LLMs for tasks like summarization, classification, question answering, and content generation. Developing and maintaining high-quality, production-grade ML code in Python using libraries such as TensorFlow, PyTorch, Hugging Face, and LangChain is crucial. Furthermore, you will be responsible for building and optimizing retrieval-augmented generation (RAG) pipelines by integrating LLMs with structured and unstructured data. Working with vector databases like FAISS and Pinecone to manage semantic search and context retrieval efficiently will be part of your role. Utilizing cloud-native AI services for model training, deployment, and scaling on platforms like AWS, GCP, and Azure is expected. Implementing MLOps best practices, including model versioning, containerization using Docker, orchestration with tools like Kubeflow and MLflow, and following CI/CD procedures are also key responsibilities. Strong problem-solving skills, architectural thinking, and the ability to lead complex AI initiatives, along with excellent communication, stakeholder management, and technical leadership capabilities, are essential for this role.,

As a Lead AI Engineer at Opkey, you will be at the forefront of disrupting the ERP transformation testing space with our AI-powered No Code Testing platform for Enterprise business applications. With our headquarters in Dublin, California, and additional offices in Pittsburgh, NYC, and India, we are a fast-growing VC-backed company trusted by 250+ enterprise customers, including GAP, Pfizer, and KPMG. Join our team and be a part of the test automation market that is estimated to reach $50 billion by 2026. Your role will involve architecting, building, and deploying AI/ML models for SaaS products at scale. You will lead the end-to-end lifecycle of AI projects, collaborate with cross-functional teams, and integrate AI capabilities into our next-generation platforms. Embrace the opportunity to define and uphold best practices in AI model development, MLOps, and scalable deployment while mentoring a team of AI/ML engineers. As a seasoned professional with 10-12 years of experience in AI/ML engineering within SaaS and product-based environments, you will bring expertise in Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Generative AI. Your hands-on experience with frameworks like TensorFlow, PyTorch, and Hugging Face Transformers will be invaluable in designing scalable AI architectures and deploying models in production environments. Your strong programming skills in Python, along with familiarity with languages like Java, Go, or Scala, will be essential as you navigate ambiguous technical challenges and drive innovative AI solutions. Stay abreast of advancements in AI, contribute thought leadership internally and externally, and partner with stakeholders to define AI strategies aligned with overall technology roadmaps and business objectives. Preferred qualifications include a Masters or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field, experience in Go-to-Market Strategy for AI-powered products, and contributions to open-source AI projects or published research papers. If you have experience integrating AI into customer-facing SaaS products with measurable outcomes, this could be an exciting opportunity for you to make a significant impact. Join Opkey as we revolutionize the world of AI-powered testing and be part of a dynamic team driving innovation and excellence in the AI space.,

As an AI Simulation Engineer at our company, you will be part of a team that is creating an AI-powered platform to deliver highly interactive, role-specific user experiences. Your main responsibility will be to design and implement the core simulation engine, which is an AI system capable of producing dynamic, multi-step interactions that evolve over time based on user actions. Your tasks will include developing context-aware AI agents that maintain interaction history and adapt responses over extended user journeys, building systems that allow character/persona-driven conversations with nuanced, role-specific behaviors, architecting long-term state management and storyline progression for complex multi-session experiences, designing automated task generation and evaluation workflows for different user profiles, implementing robust feedback loops and adaptive learning flows within simulations, and optimizing AI model usage for scalability, accuracy, and cost efficiency. To be successful in this role, you should have at least 7 years of experience in AI/ML or NLP-heavy product engineering. You should also have strong hands-on experience with LLM APIs such as OpenAI, Claude, Gemini, and frameworks like LangChain or LlamaIndex. Expertise in Python, backend architecture, and API development is essential, along with familiarity with vector databases like Pinecone, Weaviate, FAISS for context retrieval. Experience in building persistent conversational systems with multi-agent capabilities is also required, and any experience with simulation, gamification, or adaptive learning platforms would be a bonus. Joining our team will give you a founding-level role with high product ownership, the opportunity to work at the cutting edge of AI-driven, interactive environments, a competitive salary, and the chance to shape a product from the ground up with global market potential.,

About Birlasoft: At Birlasoft, we are a powerhouse where domain expertise, enterprise solutions, and digital technologies converge to redefine business processes. We take pride in our consultative and design thinking approach, driving societal progress by enabling our customers to run businesses with unmatched efficiency and innovation. As part of the CKA Birla Group, a multibillion-dollar enterprise, we boast a 12,500+ professional team committed to upholding the Group's 162-year legacy. Our core values prioritize Diversity, Equity, and Inclusion (DEI) initiatives, along with Corporate Sustainable Responsibility (CSR) activities, demonstrating our dedication to building inclusive and sustainable communities. Join us in shaping a future where technology seamlessly aligns with purpose. We are looking for an experienced technical lead to implement an enterprise-grade conversational AI interface leveraging technologies like NodeJS, Python, LangChain, Azure OpenAI, and Azure Cognitive Services. Responsibilities: - Implement conversational AI application using NodeJS, Azure OpenAI, and Python. - Integrate various AI technologies like OpenAI models, LangChain, Azure Cognitive Services (Cognitive Search, Indexes, Indexers, and APIs, etc.) to enable sophisticated natural language capabilities. - Implementation of private endpoints across the Azure services leveraged for the application. - Implement schemas, APIs, frameworks, and platforms to operationalize AI models and connect them to conversational interfaces. - Implement app logic for conversation workflows, context handling, personalized recommendations, sentiment analysis, etc. - Build and deploy the production application on Azure while meeting security, reliability, and compliance standards. - Create tools and systems for annotating training data, monitoring model performance, and continuously improving the application. - Mentor developers and provide training on conversational AI development best practices. - Build and productionize vector databases for the application on Azure cloud. Key Responsibilities: - 6-8 years of overall technology experience in core application development. - 2+ years of experience leading the development of AI apps and conversational interfaces. - Hands-on implementation-centric knowledge of generative AI tools on Azure cloud. - Deep, hands-on, and development proficiency in Python and NodeJS. - Hands-on expertise of SharePoint indexes and data/file structures (Azure SQL). - Hands-on knowledge of Azure Form Recognizer tools. - Experience with LangChain, Azure OpenAI, and Azure Cognitive Search. - Retrieval Augmented Generation (RAG) and RLHF (Reinforcement Learning from Human Feedback) using Python. - Vector databases on Azure cloud using PostgreSQL. - Pinecone, FAISS, Weaviate, or ChromaDB. - Prompt Engineering using LangChain or Llama Index. - Knowledge of NLP techniques like transformer networks, embeddings, intent recognition, etc. - Hands-on skills on Embedding and fine-tuning Azure OpenAI using MLOPS/LLMOPS pipelines. - Good to have - Strong communication, DevOps, and collaboration skills.,

As an engineer specializing in Generative AI and AI agent development at PubMatic, you will play a key role in building and optimizing advanced AI agents that utilize cutting-edge technologies such as Retrieval-Augmented Generation (RAG), vector databases, and large language models (LLMs). Your primary responsibilities will involve developing state-of-the-art solutions to enhance Generative AI capabilities, enabling the platform to handle complex information retrieval, contextual generation, and adaptive interactions. You will collaborate closely with a cross-functional team of engineers, architects, product managers, and UX designers to innovate AI solutions for new customer use-cases. Working independently, you will iterate rapidly based on customer feedback to refine product features. Your tasks will include implementing and optimizing LLMs for specific use cases, integrating RAG systems to enhance content accuracy, designing and optimizing vector databases for efficient search, and fine-tuning prompts to improve LLM performance. In this role, you will leverage evaluation frameworks and metrics to assess and enhance the performance of generative models and AI systems. Additionally, you will work with data scientists, engineers, and product teams to integrate AI-driven capabilities into both customer-facing products and internal tools. Staying updated with the latest research and trends in LLMs, RAG, and generative AI technologies will be essential to driving innovation within the company's offerings. To be successful in this role, you must possess a strong understanding of large language models, transformer architecture, and hyper-parameter tuning. You should have proven experience in building AI agents using Retrieval-Augmented Generation and working with external data sources. Proficiency in Python, experience with machine learning libraries such as TensorFlow and PyTorch, and familiarity with technologies like FAISS, Pinecone, and Weaviate are required. A bachelor's degree in engineering (CS/IT) or an equivalent degree from a reputable institute is necessary for this position. Additionally, experience with graph-based architectures, cloud platforms (AWS, GCP, Azure), and containerization technologies (Docker, Kubernetes) would be beneficial. Publication or contributions to research in AI-related fields are considered a plus. PubMatic offers a hybrid work schedule allowing employees to work 3 days in the office and 2 days remotely, aiming to maximize collaboration and productivity. The benefits package includes paternity/maternity leave, healthcare insurance, broadband reimbursement, and other perks such as a kitchen stocked with snacks and catered lunches. Join PubMatic, a leading digital advertising platform, and contribute to driving better business outcomes through transparent advertising solutions on the open internet.,

As a Senior Machine Learning Engineer with expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), you will play a critical role in supporting a high-impact Proof of Concept (PoC) focused on legacy code analysis, transformation, and modernization. Your primary responsibility will be to enable intelligent code migration and documentation through the implementation of advanced AI/ML tooling. You will be expected to develop and integrate LLM-based pipelines, utilizing tools such as Claude Sonnet 3.7 or 4 on AWS Bedrock. Additionally, you will design and implement RAG-based systems for code understanding, leveraging Vector Databases like Milvus or Pinecone. Your expertise in Abstract Syntax Tree (AST) techniques will be crucial for parsing, analyzing, and transforming legacy code for migration and documentation purposes. You will also apply CodeRAG techniques to facilitate context-aware retrieval and transformation of code artifacts. Iterative validation and correction of AI-generated outputs will be part of your routine to ensure the production of high-quality code assets. Data preprocessing and metadata enrichment, including embeddings, structured knowledge, or fine-tuning for LLM input optimization, will also be within your scope of work. Collaboration with domain experts and engineering teams is essential to ensure alignment with architecture and business logic. You will utilize version control systems like Git to manage changes, support collaboration, and ensure reproducibility. Additionally, you will contribute to QA strategies and help define testing protocols for model output validation. To excel in this role, you must have at least 5 years of experience in Machine Learning, with a strong focus on LLM applications and code understanding. Proficiency in Python and solid software engineering principles are a must, as well as experience working with AWS Bedrock for model deployment and orchestration. You should possess a strong understanding and hands-on experience with AST-based code parsing and transformation, familiarity with RAG architectures, and experience working with vector databases like Milvus, Pinecone, or similar. Experience in preprocessing legacy codebases, enriching metadata for LLM consumption, and using Git or other version control systems in collaborative environments are crucial skills. A solid understanding of code migration, modernization processes, and business logic documentation is also required. Nice-to-have skills include ensuring compliance with architectural and code specifications, documenting code flows, aligning with business requirements, familiarity with QA and testing strategies in AI/ML or code-generation workflows, and a collaborative mindset with strong communication skills and a proactive attitude essential for working in a fast-paced PoC environment with tight feedback loops.,

As an MLOps Engineer at Barclays, you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions. Your main focus will be on ensuring scalable, secure, and efficient deployment across the infrastructure. Collaborating closely with data scientists, ML engineers, and business stakeholders, you will build and maintain robust MLOps pipelines. These pipelines will enable rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems. To excel in this role, you should have strong programming skills in Python and hands-on experience with ML libraries such as scikit-learn, TensorFlow, and PyTorch. Additionally, familiarity with automation tools like Jenkins, GitHub Actions, or GitLab CI/CD for automating ML pipelines is essential. Proficiency in Docker and Kubernetes for scalable deployments, along with deep experience in utilizing AWS services like SageMaker, Bedrock, Lambda, and CloudFormation, is crucial. Your responsibilities will also involve managing infrastructure for training and inference using AWS services such as S3, EC2, EKS, and Step Functions. Experience with Infrastructure as Code tools like Terraform and AWS CDK, as well as model lifecycle management tools like MLflow and SageMaker Model Registry, will be beneficial. Understanding DevOps principles applied to ML workflows is key to success in this role. Additionally, highly valued skills may include experience with Snowflake, Databricks for collaborative ML development, and knowledge of data engineering tools like Apache Airflow, Kafka, and Spark. An understanding of model interpretability, responsible AI, and governance will further enhance your contributions. Involvement in open-source MLOps tools or communities, strong leadership, communication, and cross-functional collaboration skills, as well as knowledge of data privacy, model governance, and regulatory compliance in AI systems, will be advantageous. This role is based out of Pune and aims to build and maintain infrastructure platforms and products that support applications and data systems. Your accountability will involve developing, delivering, and maintaining high-quality infrastructure solutions that meet business requirements. You will play a crucial role in incident management, automation, security implementation, teamwork, and continuous learning to ensure the reliability, availability, and scalability of systems and platforms. If you are an Assistant Vice President in this role, you will be expected to advise and influence decision-making, contribute to policy development, and ensure operational effectiveness. Collaboration with other functions/business divisions, leadership of complex tasks, and coaching employees towards objectives will be part of your responsibilities. For individual contributors, leading collaborative assignments, guiding team members, identifying new directions for projects, and consulting on complex issues will be key tasks. All colleagues are expected to demonstrate Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, along with the Barclays Mindset of Empower, Challenge, and Drive.,

The next step of your career starts here, where you can bring your own unique mix of skills and perspectives to a fast-growing team. Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities. With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas. Being part of Metyis means you can speak your mind and be creative with your knowledge. Imagine the things you can achieve with a team that encourages you to be the best version of yourself. We are Metyis. Partners for Impact. Interact with C-level at our clients on a regular basis to drive their business towards impactful change. Lead your team in creating new business solutions. Seize opportunities at the client and at Metyis in our entrepreneurial environment. Become part of a fast-growing international and diverse team. Lead and manage the delivery of complex data science projects, ensuring quality and timelines. Engage with clients and business stakeholders to understand business challenges and translate them into analytical solutions. Design solution architectures and guide the technical approach across projects. Align technical deliverables with business goals, ensuring data products create measurable business value. Communicate insights clearly through presentations, visualizations, and storytelling for both technical and non-technical audiences. Promote best practices in coding, model validation, documentation, and reproducibility across the data science lifecycle. Collaborate with cross-functional teams to ensure smooth integration and deployment of solutions. Drive experimentation and innovation in AI/ML techniques, including newer fields - Generative AI. 6+ years of experience in delivering full-lifecycle data science projects. Proven ability to lead cross-functional teams and manage client interactions independently. Strong business understanding with the ability to connect data science outputs to strategic business outcomes. Experience with stakeholder management, translating business questions into data science solutions. Track record of mentoring junior team members and creating a collaborative learning environment. Familiarity with data productization and ML systems in production, including pipelines, monitoring, and scalability. Experience managing project roadmaps, resourcing, and client communication. Strong hands-on experience in Python/R and SQL. Good understanding and Experience with cloud platforms such as Azure, AWS, or GCP. Experience with data visualization tools in python like Seaborn, Plotly. Good understanding of Git concepts. Good experience with data manipulation tools in python like Pandas and Numpy. Must have worked with scikit learn, NLTK, Spacy, transformers. Experience with dashboarding tools such as Power BI and Tableau to create interactive and insightful visualizations. Proficient in using deployment and containerization tools like Docker and Kubernetes for building and managing scalable applications. Core Competencies: Strong foundation in machine learning algorithms, predictive modeling, and statistical analysis. Good understanding of deep learning concepts, especially in NLP and Computer Vision applications. Proficiency in time-series forecasting and business analytics for functions like marketing, sales, operations, and CRM. Exposure to tools like Mlflow, model deployment, API integration, and CI/CD pipelines. Hands-on experience with MLOps and model governance best practices in production environments. Experience in developing optimization and recommendation system solutions to enhance decision-making, user personalization, and operational efficiency across business functions. Generative AI Experience with text and Image data. Familiarity with LLM frameworks such as LangChain and hubs like Hugging Face. Exposure to vector databases (e.g., FAISS, Pinecone, Weaviate) for semantic search or retrieval-augmented generation (RAG).,

Senior GenAI & Agentic AI Expert (Architect) Relocation to Abu Dhabi, UAE Location: Abu Dhabi Client: Abu Dhabi Government About The Role Our client, a global consulting firm with distributed teams across the US, Canada, UAE, India, and PK, is hiring a high-caliber Senior Generative AI Expert with proven hands-on experience in building Agentic AI applications . This role is ideal for someone who has a total of 12 to 20+ years of software engineering and AI/ML experience and is now focused on autonomous AI agents, tool-using LLMs, LangChain, AutoGPT, or similar frameworks . Key Responsibilities Design and develop Agentic AI applications using LLM frameworks (LangChain, AutoGPT, CrewAI, Semantic Kernel, or similar) Architect and implement multi-agent systems for enterprise-grade solutions Integrate AI agents with APIs, databases, internal tools, and external SaaS products Lead and mentor a cross-functional team across global time zones Optimize performance, context retention, tool usage, and cost efficiency Build reusable pipelines and modules to support GenAI use cases at scale Ensure enterprise-grade security, privacy, and compliance standards in deployments Collaborate directly with clients and senior stakeholders Ideal Candidate Profile 10 to 15+ years of professional experience in software engineering and AI/ML 3+ years of practical experience in LLM-based application development Strong track record of delivering Agentic AI systems (not just chatbot interfaces) Hands-on experience with: LangChain, AutoGPT, CrewAI, ReAct, Semantic Kernel OpenAI, Claude, Gemini, Mistral, or Llama2 Embedding models, vector databases (FAISS, Pinecone, Weaviate, etc.) Prompt engineering, RAG, memory/context management Serverless, Python, Node.js, AWS/GCP/Azure cloud Experience leading engineering teams and working with enterprise clients Excellent communication, documentation, and stakeholder management skills Must be open to relocation to UAE Why Join Work on UAE Government project(s) Lead cutting-edge Agentic AI projects at enterprise scale Collaborate with senior teams across US, Canada, UAE, India, and PK Competitive compensation + long-term career roadmap Skills: memory/context management,apis integration,enterprise-grade security,crewai,saas products integration,aws,semantic kernel,prompt engineering,openai,node.js,multi-agent systems,azure,databases integration,gemini,cost efficiency,embedding models,rag,autogpt,performance optimization,llm frameworks,agentic ai,generative ai,langchain,gcp,python,vector databases Show more Show less

In-depth experience with the Eliza framework and its agent coordination capabilities In-depth experience with the Agentic AI Practical implementation experience with vector databases (Pinecone, Weaviate, Milvus, or Chroma) Hands-on experience with embedding models (e.g., OpenAI, Cohere, or open-source alternatives) Deep knowledge of LangChain/LlamaIndex for agent memory and tool integration Experience designing and implementing knowledge graphs at scale Strong background in semantic search optimization and efficient RAG architectures Experience with Model Control Plane (MCP) for both LLM orchestration and enterprise system integration Advanced Pythondevelopment with expertise in async patterns and API design

You will be responsible for building and deploying scalable LLM-based systems using technologies such as OpenAI, Claude, LLaMA, or Mistral for contract understanding and legal automation. Additionally, you will design and implement Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases like FAISS, Pinecone, and Weaviate. Your role will involve fine-tuning and evaluating foundation models for domain-specific tasks such as clause extraction, dispute classification, and document QA. Furthermore, you will be expected to create recommendation models that offer suggestions for similar legal cases, past dispute patterns, or clause templates through collaborative and content-based filtering. Developing inference-ready APIs and backend microservices using FastAPI/Flask and integrating them into production workflows will also be part of your responsibilities. You will need to optimize model latency, prompt engineering, caching strategies, and accuracy using A/B testing and hallucination checks. Collaboration with Data Engineers and QA team members to convert ML prototypes into production-ready pipelines will be essential. Continuous error analysis, evaluation metric design (F1, BLEU, Recall@K), and prompt iterations will also fall under your purview. Participation in model versioning, logging, and reproducibility tracking using tools like MLflow or LangSmith is expected. Additionally, staying up-to-date with research on GenAI, prompting techniques, LLM compression, and RAG design patterns will be crucial. Qualifications: - Bachelors or Masters degree in Computer Science, AI, Data Science, or a related field. - 2+ years of experience in applied ML/NLP projects with real-world deployments. - Experience with LLMs like GPT, Claude, Gemini, Mistral, and techniques like fine-tuning, few-shot prompting, and context window optimization. - Strong knowledge of Python, PyTorch, Transformers, LangChain, and embedding models. - Hands-on experience integrating vector stores and building RAG pipelines. - Understanding of NLP techniques such as summarization, token classification, document ranking, and conversational QA. - Bonus: Experience with Neo4j, recommendation systems, or graph embeddings.,

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, were a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future. We are looking forward to hire AI/ML Professionals in the following areas : Designation: AI Engineer Experience: 24 Years Job Type: Full-time We are seeking a highly skilled and motivated Data Scientist to join our dynamic team. In this role, you will leverage your advanced analytical and technical expertise to solve complex business problems and drive impactful data-driven decisions. You will design, develop, and deploy sophisticated machine learning models, conduct in-depth data analyses, and collaborate with cross-functional teams to deliver actionable insights. Responsibilities Build and deploy ML models for classification, regression, and clustering tasks. Apply foundational GenAI concepts such as embeddings, summarization, and RAG. Use APIs and tools like LangChain, vector databases (e.g., Pinecone, FAISS). Prepare documentation and results interpretation. Required Skills Strong hands-on experience in Python, Scikit-learn, Pandas. Knowledge of model evaluation, feature engineering, and model tuning. Exposure to LangChain and vector DBs. Basic exposure to FastAPI or Flask. At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our Hyperlearning workplace is grounded upon four principles Flexible work arrangements, Free spirit, and emotional positivity Agile self-determination, trust, transparency, and open collaboration All Support needed for the realization of business goals, Stable employment with a great atmosphere and ethical corporate culture Show more Show less

About The Role Masai, in academic collaboration with a premier institute, is seeking a Teaching Assistant (TA) for its New Age Software Engineering program. This advanced 90-hour course equips learners with Generative AI foundations, production-grade AI engineering, serverless deployments, agentic workflows, and vision-enabled AI applications. The TA will play a key role in mentoring learners, resolving queries, sharing real-world practices, and guiding hands-on AI engineering projects. This role is perfect for professionals who want to contribute to next-generation AI-driven software engineering education while keeping their technical skills sharp. Key Responsibilities (KRAs) Doubt-Solving Sessions Conduct or moderate weekly sessions to clarify concepts across: Generative AI & Prompt Engineering AI Lifecycle Management & Observability Serverless & Edge AI Deployments Agentic Workflows and Vision-Language Models (VLMs) Share industry insights and practical examples to reinforce learning. Q&A and Discussion Forum Support Respond to student questions through forums, chat, or email with detailed explanations and actionable solutions. Facilitate peer-to-peer discussions on emerging tools, frameworks, and best practices in AI engineering. Research & Project Support Assist learners in capstone project design and integration, including vector databases, agent orchestration, and performance tuning. Collaborate with the academic team to research emerging AI frameworks like LangGraph, CrewAI, Hugging Face models, and WebGPU deployments. Learner Engagement Drive engagement via assignment feedback, interactive problem-solving, and personalized nudges to keep learners motivated. Encourage learners to adopt best practices for responsible and scalable AI engineering. Content Feedback Loop Collect learner feedback and recommend updates to curriculum modules for continuous course improvement. Candidate Requirements 2+ years of experience in Software Engineering, AI Engineering, or Full-Stack Development. Strong knowledge of Python/Node.js, cloud platforms (AWS Lambda, Vercel, Cloudflare Workers), and modern AI tools. Hands-on experience with LLMs, Vector Databases (Pinecone, Weaviate), Agentic Frameworks (LangGraph, ReAct), and AI observability tools. Understanding of AI deployment, prompt engineering, model fine-tuning, and RAG pipelines. Excellent communication and problem-solving skills; mentoring experience is a plus. Familiarity with online learning platforms or LMS tools is advantageous. Engagement Details Time Commitment: 6 to 8 hours per week Location: Remote (online) Compensation: ?8,000 to ?10,000 per month Why Join Us Benefits and Perks Contribute to a cutting-edge AI & software engineering program with a leading ed-tech platform. Mentor learners on next-generation AI applications and engineering best practices. Engage in flexible remote working while influencing future technological innovations. Access to continuous professional development and faculty enrichment programs. Network with industry experts and professionals in the AI and software engineering domain. Skills: edge,llms,rag pipelines,communication,online,aws lambda,databases,cloudflare workers,ai observability tools,vercel,prompt,learning,model fine-tuning,vector databases,prompt engineering,software,new age,agentic frameworks,mentoring,problem-solving,python,models,learners,node.js Show more Show less

STAND 8 provides end-to-end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India. We are seeking a Senior AI Engineer / Data Engineer to join our engineering team and help build the future of AI-powered business solutions. In this role, you&aposll be developing intelligent systems that leverage advanced large language models (LLMs), real-time AI interactions, and cutting-edge retrieval architectures. Your work will directly contribute to products that are reshaping how businesses operate-particularly in recruitment, data extraction, and intelligent decision-making. This is an exciting opportunity for someone who thrives in building production-grade AI systems and working across the full stack of modern AI technologies. Responsibilities Design, build, and optimize AI-powered systems using multi-modal architectures (text, voice, visual). Integrate and deploy LLM APIs from providers such as OpenAI, Anthropic, and AWS Bedrock. Build and maintain RAG (Retrieval-Augmented Generation) systems with hybrid search, re-ranking, and knowledge graphs. Develop real-time AI features using streaming analytics and voice interaction tools (e.g., ElevenLabs). Build APIs and pipelines using FastAPI or similar frameworks to support AI workflows. Process and analyze unstructured documents with layout and semantic understanding. Implement predictive models that power intelligent business recommendations. Deploy and maintain scalable solutions using AWS services (EC2, S3, RDS, Lambda, Bedrock, etc.). Use Docker for containerization and manage CI/CD workflows and version control via Git. Debug, monitor, and optimize performance for large-scale data pipelines. Collaborate cross-functionally with product, data, and engineering teams. Qualifications 5+ years of experience in AI/ML or data engineering with Python in production environments. Hands-on experience with LLM APIs and frameworks such as OpenAI, Anthropic, Bedrock, or LangChain. Production experience using vector databases like PGVector, Weaviate, FAISS, or Pinecone. Strong understanding of NLP, document extraction, and text processing. Proficiency in AWS cloud services including Bedrock, EC2, S3, Lambda, and monitoring tools. Experience with FastAPI or similar frameworks for building AI/ML APIs. Familiarity with embedding models, prompt engineering, and RAG systems. Asynchronous programming knowledge for high-throughput pipelines. Experience with Docker, Git workflows, CI/CD pipelines, and testing best practices. Preferred Background in HRTech or ATS integrations (e.g., Greenhouse, Workday, Bullhorn). Experience working with knowledge graphs (e.g., Neo4j) for semantic relationships. Real-time AI systems (e.g., WebRTC, OpenAI Realtime API) and voice AI tools (e.g., ElevenLabs). Advanced Python development skills using design patterns and clean architecture. Large-scale data processing experience (1-2M+ records) with cost optimization techniques for LLMs. Event-driven architecture experience using AWS SQS, SNS, or EventBridge. Hands-on experience with fine-tuning, evaluating, and deploying foundation models. Show more Show less

Level AI was founded in 2019 and is a Series C startup headquartered in Mountain View, California. Level AI revolutionizes customer engagement by transforming contact centers into strategic assets. Our AI-native platform leverages advanced technologies such as Large Language Models to extract deep insights from customer interactions. By providing actionable intelligence, Level AI empowers organizations to enhance customer experience and drive growth. Consistently updated with the latest AI innovations, Level AI stands as the most adaptive and forward-thinking solution in the industry. Empowering contact center stakeholders with real-time insights, our tech facilitates data-driven decision-making for contact centers, enhancing service levels and agent performance. As a vital team member, your work will be cutting-edge technologies and will play a high-impact role in shaping the future of AI-driven enterprise applications. You will directly work with people who&aposve worked at Amazon, Facebook, Google, and other technology companies in the world. With Level AI, you will get to have fun, learn new things, and grow along with us. Ready to redefine possibilities Join us! We&aposll love to explore more about you if you have B.E/B.Tech/M.E/M.Tech/PhD from Tier 1 engineering institutes only with relevant work experience with a top technology company in computer science or mathematics-related fields. 3+ years of experience in AI/ML Strong coding skills in Python and familiarity with libraries like LangChain or Transformers Interest in LLMs, agents, and the evolving open-source AI ecosystem Eagerness to learn, experiment, and grow in a fast-paced environment. Your role at Level AI includes but is not limited to Assist in building LLM-powered agents for internal tools and customer-facing products Support prompt engineering, retrieval-augmented generation (RAG), and tool integrations Collaborate on experiments with open-source and commercial LLMs (e.g., GPT, Claude, Mistral) Help implement and evaluate reasoning, planning, and memory modules for agents Work closely with senior engineers to deploy and monitor AI features in production Bonus Points Experience with open-source LLMs (LLaMA, Mistral, etc.) Basic understanding of vector search, RAG, and prompt engineering concepts Contributions to AI side projects or GitHub repos Exposure to vector databases or retrieval pipelines (e.g., FAISS, Pinecone) To Apply- https://jobs.lever.co/levelai/cc04ab77-6ee3-4078-9cfd-110cda0b1438 To learn more visit : https://thelevel.ai/ Funding : https://www.crunchbase.com/organization/level-ai LinkedIn : https://www.linkedin.com/company/level-ai/ Show more Show less

???? We&aposre Hiring: Artificial Intelligence Consultant! ???? We&aposre seeking a highly motivated and technically adept Artificial Intelligence Consultant to join our growing Artificial Intelligence and Business Transformation practice. This role is ideal for a strategic thinker with a strong blend of leadership, business consulting acumen, and technical expertise in Python, LLMs, Retrieval-Augmented Generation (RAG), and agentic systems. Experience Required: Minimum 6+ Years Location: Remote/ Work From Home Job Type: Contract to hire (1 Year /Renewable Contract) Notice Period: Immediate to 15 Days Max Mode of Interview: Virtual Roles And Responsibilities AI Engagements: Independently manage end-to-end delivery of AI-led transformation projects across industries, ensuring value realization and high client satisfaction. Strategic Consulting & Roadmapping: Identify key enterprise challenges and translate them into AI solution opportunities, crafting transformation roadmaps that leverage RAG, LLMs, and intelligent agent frameworks. LLM/RAG Solution Design & Implementation: Architect and deliver cutting-edge AI systems using Python, LangChain, LlamaIndex, OpenAI function calling, semantic search, and vector store integrations (FAISS, Qdrant, Pinecone, ChromaDB). Agentic Systems: Design and deploy multi-step agent workflows using frameworks like CrewAI, LangGraph, AutoGen or ReAct, optimizing tool-augmented reasoning pipelines. Client Engagement & Advisory: Build lasting client relationships as a trusted AI advisor, delivering technical insight and strategic direction on generative AI initiatives. Hands-on Prototyping: Rapidly prototype PoCs using Python and modern ML/LLM stacks to demonstrate feasibility and business impact. Thought Leadership: Conduct market research, stay updated with the latest in GenAI and RAG/Agentic systems, and contribute to whitepapers, blogs, and new offerings. Essential Skills Education : Bachelor&aposs or Masters in Computer Science, AI, Engineering, or related field. Experience : Minimum 6 years of experience in consulting or technology roles, with at least 3 years focused on AI & ML solutions. Leadership Quality: Proven track record in leading cross-functional teams and delivering enterprise-grade AI projects with tangible business impact. Business Consulting Mindset: Strong problem-solving, stakeholder communication, and business analysis skills to bridge technical and business domains. Python & AI Proficiency: Advanced proficiency in Python and popular AI/ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, spaCy, NLTK). Solid understanding of NLP, embeddings, semantic search, and transformer models. LLM Ecosystem Fluency: Experience with OpenAI, Cohere, Hugging Face models; prompt engineering; tool/function calling; and structured task orchestration. Independent Contributor: Ability to own initiatives end-to-end, take decisions independently, and operate in fast-paced environments. Preferred Skills Cloud Platform Expertise: Strong familiarity with Microsoft Azure (preferred), AWS, or GCP including compute instances, storage, managed services, and serverless/cloud-native deployment models. Programming Paradigms: Hands-on experience with both functional and object-oriented programming in AI system design. Hugging Face Ecosystem: Proficiency in using Hugging Face Transformers, Datasets, and Model Hub. Vector Store Experience: Hands-on experience with FAISS, Qdrant, Pinecone, ChromaDB. LangChain Expertise: Strong proficiency in LangChain for agentic task orchestration and RAG pipelines. MLOps & Deployment: CI/CD for ML pipelines, MLOps tools (MLflow, Azure ML), containerization (Docker/Kubernetes). Cloud & Service Architecture: Knowledge of microservices, scaling strategies, inter-service communication. Programming Languages: Proficiency in Python and C# for enterprise-grade AI solution development. Show more Show less

Responsibilities Design and fine-tune LLMs (Large Language Models) for BFSI use-cases: intelligent document processing, report generation, chatbots, advisory tools. Evaluate and apply prompt engineering, retrieval-augmented generation (RAG), and fine-tuning methods. Implement safeguards, red-teaming, and audit mechanisms for LLM usage in BFSI. Work with data privacy, legal, and compliance teams to align GenAI outputs with industry regulations. Collaborate with enterprise architects to integrate GenAI into existing digital platforms. Qualifications 35 years in AI/ML; 13 years hands-on in GenAI/LLM-based solutions. BFSI-specific experience in document processing, regulatory reporting, or virtual agents using GenAI is highly preferred. Exposure to prompt safety, model alignment, and RAG pipelines is critical. Essential Skills Tech Stack LLMs: GPT (OpenAI), Claude, LLaMA, Mistral, Falcon Tools: LangChain, LlamaIndex, Pinecone, Weaviate Frameworks: Transformers (Hugging Face), PEFT, DeepSpeed APIs: OpenAI, Cohere, Anthropic, Azure OpenAI Cloud: GCP GenAI Studio, GCP Vertex AI Others: Prompt engineering, RAG, vector databases, role-based guardrails Experience 35 years in AI/ML; 13 years hands-on in GenAI/LLM-based solutions. Show more Show less

As a Python Developer specializing in Generative AI, you will play a key role in designing, developing, and deploying intelligent AI-powered systems during the night shift in Bangalore. Your primary responsibility will involve building and maintaining Python-based APIs and backends integrated with cutting-edge Generative AI models. You will collaborate with global teams to implement prompt engineering, fine-tuning, and model deployment pipelines using tools such as GPT, Claude, LLaMA, DALLE, and Stable Diffusion. Your expertise in PyTorch, TensorFlow, Hugging Face, LangChain, or OpenAI API will be crucial in optimizing model performance for latency, accuracy, and scalability. Additionally, you will deploy models using FastAPI, Flask, Docker, or cloud platforms while ensuring thorough testing, monitoring, and documentation of AI integrations. To excel in this role, you should possess at least 4 years of Python development experience along with 1 year of hands-on experience with Generative AI tools and models. Familiarity with vector databases such as FAISS, Pinecone, and Weaviate is also desirable. Exposure to GPU-based training or inference, MLOps tools like MLflow, Airflow, or Kubeflow, and a strong understanding of AI ethics, model safety, and bias mitigation are considered advantageous. This full-time, permanent position offers health insurance, Provident Fund benefits, and requires working in person during the night shift. If you are passionate about leveraging AI to address real-world challenges and thrive in a fast-paced environment, we encourage you to apply and contribute to innovative GenAI and ML projects.,

As a Python Backend Engineer specializing in AWS with a focus on GenAI & ML, you will be responsible for designing, developing, and maintaining intelligent backend systems and AI-driven applications. Your primary objective will be to build and scale backend systems while integrating AI/ML models using Django or FastAPI. You will deploy machine learning and GenAI models with frameworks like TensorFlow, PyTorch, or Scikit-learn, and utilize Langchain for GenAI pipelines. Experience with LangGraph will be advantageous in this role. Collaboration with data scientists, DevOps, and architects is essential to integrate models into production. You will be working with AWS services such as EC2, Lambda, S3, SageMaker, and CloudFormation for infrastructure and deployment purposes. Additionally, managing CI/CD pipelines for backend and model deployments will be a key part of your responsibilities. Ensuring the performance, scalability, and security of applications in cloud environments will also fall under your purview. To be successful in this role, you should have at least 5 years of hands-on experience in Python backend development and a strong background in building RESTful APIs using Django or FastAPI. Proficiency in AWS cloud services is crucial, along with a solid understanding of ML/AI concepts and model deployment practices. Familiarity with ML libraries like TensorFlow, PyTorch, or Scikit-learn is required, as well as experience with Langchain for GenAI applications. Experience with DevOps tools such as Docker, Kubernetes, Git, Jenkins, and Terraform will be beneficial. An understanding of microservices architecture, CI/CD workflows, and agile development practices is also desirable. Nice to have skills include knowledge of LangGraph, LLMs, embeddings, and vector databases, as well as exposure to OpenAI APIs, AWS Bedrock, or similar GenAI platforms. Additionally, familiarity with MLOps tools and practices for model monitoring, versioning, and retraining will be advantageous. This is a full-time, permanent position with benefits such as health insurance and provident fund. The work location is in-person, and the schedule involves day shifts from Monday to Friday in the morning. If you are interested in this opportunity, please contact the employer at +91 9966550640.,