19 Chromadb Jobs

???? Senior AI/ML Engineer Multi-Agent & MCP Architect Location: Mumbai (Hybrid) Company: Fin 100X.AI Indias Protocol-Governed AI Financial OS ???? Company Description Fin 100X.AI is Indias first protocol-governed, AI-powered Financial Operating System built for Bharats 100 crore underserved citizens. We are reimagining finance through: Multi-agent AI orchestration (MCP protocol-driven) Explainable and trustworthy AI Regulatory-first design (RBI, SEBI, IRDAI, PFRDA aligned) Backed by IIT Bombay alumni and top fintech leaders, we are building AI for Bharat that blends technology, trust, and inclusion. ???? Role Overview As a Senior AI/ML Engineer (MCP + Multi-Agent Orchestration), you will be part of the founding tech braintrust that defines the core AI architecture of Fin 100X.AI. Your mission: Design and deploy a world-class, multi-agent AI stack powered by MCP (Model Context Protocol) to deliver scalable, explainable, and reliable AI-driven financial advisory modules for 100 crore users. You will directly influence: AI Laxmi orchestration Credit Booster, SIP Planner, Fraud Shield National-scale agentic financial intelligence ???? Key Responsibilities Architect and implement multi-agent AI systems using MCP protocol Build LLM orchestration pipelines (LangChain, AutoGen, CrewAI, MCP) Design retrieval-augmented pipelines (RAG) with vector memory & routing Deploy neural models (NLP, NLU, recommendation engines) at scale Create fallback, routing, and governance layers for explainable AI Integrate real-time financial intelligence APIs (OpenAI, Gemini, HuggingFace, etc.) Mentor junior AI engineers; enforce best practices in ML Ops and agent orchestration Collaborate with backend/frontend teams for end-to-end AI productionization ? Required Qualifications Core Technical Skills Strong foundation in ML/DL architectures, NLP, and LLMs Expertise in multi-agent orchestration frameworks: MCP, AutoGen, CrewAI, LangGraph Advanced experience with Python (TensorFlow, PyTorch, HuggingFace, FastAPI) Proficient in vector search systems (Pinecone, FAISS, ChromaDB) Deep knowledge of RAG pipelines, memory graphs, prompt chaining Experience deploying models in cloud-native and microservice architectures Preferred Exposure FinTech AI systems or regulated AI environments Agent evaluation, explainability, and safety-first design Scaling AI in hybrid production (cloud + edge) environments ???? What We Value Architect mindset with hands-on coding skills Self-driven innovation and ownership from concept ? deployment Experience building AI systems for 10M+ scale Passion for financial inclusion, Bharat-first AI, and AI for Good ???? Perks Shape Indias AI Financial OS from Day 0 ESOP track + leadership growth National showcase at Global FinTech Fest 2025 Mentorship with IIT Bombay alumni & top AI architects Solve real Bharat-scale problems with MCP-first AI innovation Show more Show less

Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, the mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. In collaboration with leading academics, industry experts, and highly skilled engineers, the goal is to equip customers to generate sophisticated new insights from the biggest of big data. Join the team to do the best work of your career and make a profound social impact as an Advisor on the Data Science Team in Bangalore. As a Data Science Advisor, you will contribute to the business strategy and influence decision-making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. Designing processes to consolidate and examine unstructured data to generate actionable insights will be part of your responsibilities. Additionally, you will partner with business leaders, engineers, and industry experts to construct predictive models, algorithms, and probability engines. You will: - Partner with internal and external teams to understand customer requirements and develop proposals. - Conduct interactions with external customers to gather project requirements, provide status updates, and share analytical insights. - Implement preliminary data exploration and data preparation steps for model development/validation. - Apply a broad range of techniques and theories from statistics, machine learning, and business intelligence to deliver actionable business insights. - Solution, build, deploy, and set up monitoring for models. Qualifications: - 6+ years of related experience with proficiency in NLP, Machine Learning, Computer Vision, and GenAI. - Working experience in data visualization (e.g., Power BI, matplotlib, plotly). - Hands-on experience with CNN, LSTM, YOLO, and database skills including SQL, Postgres SQL, PGVector, and ChromaDB. - Proven experience in MLOps and LLMOps, with a strong understanding of ML lifecycle management. - Expertise with large language models (LLMs), prompt engineering, fine-tuning, and integrating LLMs into applications for natural language processing (NLP) tasks. Desirable Skills: - Strong product/technology/industry knowledge and familiarity with streaming/messaging frameworks (e.g., Kafka, RabbitMQ, ZeroMQ). - Experience with cloud platforms (e.g., AWS, Azure, GCP). - Experience with web technologies and frameworks (e.g., HTTP/REST/GraphQL, Flask, Django). - Skilled in programming languages like Java or JavaScript. Dell Technologies is committed to providing equal employment opportunities for all employees and creating a work environment free of discrimination and harassment. If you are looking for an opportunity to grow your career with advanced technology and some of the best minds in the industry, this role might be the perfect fit for you. Join Dell Technologies to build a future that works for everyone because Progress Takes All of Us.,

You should have 3 to 10 years of experience in AI development and be located in Coimbatore. Immediate joiners are preferred. A minimum of 2 years of experience in core Gen AI is required. As an AI Developer, your responsibilities will include designing, developing, and fine-tuning Large Language Models (LLMs) for various in-house applications. You will implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Additionally, you will develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Building and managing data pipelines for processing, transforming, and feeding structured/unstructured data into AI models will be part of your role. It is essential to ensure scalability, performance, and security of AI-driven solutions in production environments. Collaboration with cross-functional teams, including data engineers, software developers, and product managers, is expected. You will conduct experiments and evaluations to improve AI system accuracy and efficiency while staying updated with the latest advancements in AI/ML research, open-source models, and industry best practices. You should have strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases such as Pinecone, ChromaDB, Weaviate, OpenSearch, and FAISS, is required. Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks is preferred. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow is necessary. Experience in Python web frameworks such as FastAPI, Django, or Flask is expected. You should also have experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes) is essential. Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications is a plus. A strong understanding of vector search, embedding models, and hybrid retrieval techniques is required. Experience with optimizing inference and serving AI models in real-time production systems is beneficial. Experience with multi-modal AI (text, image, audio) and familiarity with privacy-preserving AI techniques and responsible AI frameworks are desirable. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation, is a plus. Skills required for this role include PyTorch, RAG architectures, OpenSearch, Weaviate, Docker, LLM fine-tuning, ChromaDB, Apache Airflow, LoRA, Python, hybrid retrieval techniques, Django, GCP, CrewAI, OpenAI, Hugging Face, Gen AI, Pinecone, FAISS, AWS, AutoGPT, embedding models, Flask, FastAPI, LLM APIs, DeepSpeed, vector search, PEFT, LangChain, Azure, Spark, Kubernetes, AI Gen, TensorFlow, real-time production systems, LangGraph, and Kafka.,

You are looking for a Lead AI Engineer with at least 8 years of experience to join UST at Trivandrum. As a Lead AI Engineer, you will be responsible for designing and implementing end-to-end AI/ML solutions using Python and deep learning frameworks like Keras. Your role will involve working with Generative AI and LLM architectures such as GPT-3 and BERT, as well as leading AI/ML teams and mentoring junior engineers. Your key responsibilities will include developing data pipelines and infrastructure using tools like Kafka, Big Data tools, Aurora DB, and ELK Stack. You will also be expected to deploy and optimize ML models on cloud platforms such as AWS, Azure, or GCP. Your expertise in Time Series Forecasting, Predictive Analytics, and Deep Learning will be crucial in translating business requirements into scalable AI solutions. In addition to hands-on experience in AI and Machine Learning, you should have a strong programming background in Python, Keras, and Pandas. Knowledge of advanced ML models like LangChain, GPT-3, and Transformers, as well as analytical models such as Time Series Forecasting, will be highly beneficial. Familiarity with databases like ChromaDB/Pinecone is also desired. Experience with PoC creation, model experimentation, and AI governance principles will be an advantage. You should also keep abreast of emerging trends and tools in the AI/ML space to evaluate their strategic fit and contribute to AI roadmap planning. UST is a global digital transformation solutions provider known for partnering with leading companies to drive real impact through innovation. With a workforce of over 30,000 employees in 30 countries, UST is committed to embedding innovation and agility into its clients" organizations, touching billions of lives in the process.,

As a Senior Data Engineer + AI, you will play a crucial role in designing and optimizing distributed data pipelines using PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. Your expertise in PySpark, Apache Spark, and Databricks for batch and streaming data pipelines will be instrumental in contributing to high-impact programs with clients. Your strong SQL skills for data analysis, transformation, and modeling will enable you to drive data-driven decision-making and facilitate rapid insight generation. Your responsibilities will involve supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications, as well as creating and maintaining interactive dashboards and BI reports using tools such as Power BI, Tableau, or Looker. You will collaborate with cross-functional teams, including AI scientists, analysts, and business teams, to ensure the successful delivery of use cases. In this role, you will need to have a solid understanding of data warehouse design, relational databases such as PostgreSQL, Snowflake, SQL Server, as well as data lakehouse architectures. Your familiarity with cloud services for data and AI, such as Azure, AWS, or GCP, will be essential for ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments. Furthermore, your exposure to Generative AI, RAG, embedding models, and vector databases like FAISS, Pinecone, ChromaDB, as well as experience with Agentic AI frameworks such as LangChain, Haystack, CrewAI, will be beneficial. Your knowledge of MLflow, Delta Live Tables, or other Databricks-native AI tools, CI/CD, Git, Docker, and DevOps pipelines will also be advantageous in this role. If you have a background in consulting, enterprise analytics, or AI/ML product development, it will further enhance your ability to excel in this position. Your excellent problem-solving and collaboration skills, coupled with your ability to bridge engineering and business needs, will be key to your success as a Senior Data Engineer + AI.,

We are searching for a skilled and adaptable Data Engineer with proficiency in PySpark, Apache Spark, and Databricks, combined with knowledge in analytics, data modeling, and Generative AI/Agentic AI solutions. This position suits individuals who excel at the convergence of data engineering, AI systems, and business insights, contributing to impactful programs with clients. Your responsibilities will include designing, constructing, and enhancing distributed data pipelines utilizing PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. You will also be tasked with supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications. Additionally, creating and maintaining interactive dashboards and BI reports using tools like Power BI, Tableau, or Looker for business stakeholders and consultants will be part of your role. Furthermore, your duties will involve conducting adhoc data analysis to facilitate data-driven decision-making and rapid insight generation. You will be expected to develop and sustain robust data warehouse schemas, star/snowflake models, and provide support for data lake architecture. Integration with and support for LLM agent frameworks like LangChain, LlamaIndex, Haystack, or CrewAI for intelligent workflow automation will also fall under your purview. In addition, ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments (Azure/AWS/GCP) will be important aspects of your work. Collaboration with cross-functional teams, including AI scientists, analysts, and business teams to drive use-case delivery, is key. Lastly, maintaining robust data governance, lineage, and metadata management practices using tools such as Azure Purview or DataHub will also be part of your responsibilities.,

You will be working as an AI Engineer with expertise in Speech-to-text and Text Generation to tackle a Conversational AI challenge for a client in EMEA. The project aims to transcribe conversations and utilize generative AI-powered text analytics for enhancing engagement strategies and decision-making processes. Your main responsibilities will include developing Conversational AI & Call Transcription solutions, creating NLP & Generative AI Applications, performing Sentiment Analysis & Decision Support tasks, and handling AI Deployment & Scalability aspects. You will be expected to work on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key technical skills required for this role include a strong background in Speech-to-Text (ASR), NLP, and Conversational AI, along with hands-on experience in tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text, Python, PyTorch, TensorFlow, Hugging Face Transformers, LLM fine-tuning, RAG-based architectures, LangChain, and Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB). Experience in deploying AI models using Docker, Kubernetes, FastAPI, Flask will be essential. In addition to technical skills, soft skills such as translating AI insights into business impact, problem-solving abilities, and effective communication skills to collaborate with cross-functional teams will be crucial for success in this role. Preferred qualifications include experience in healthcare, pharma, or life sciences NLP use cases, a background in knowledge graphs, prompt engineering, and multimodal AI, as well as familiarity with Reinforcement Learning (RLHF) for enhancing conversation models.,

We are seeking a dedicated Data Scientist with a strong background in Natural Language Processing (NLP) and expertise in Large Language Models (LLMs). As a part of our team, you will play a crucial role in the development, optimization, and implementation of open-source and API-based LLMs to address real-world challenges. Your primary responsibilities will revolve around constructing resilient GenAI pipelines, innovative internal tools, and customer-centric applications. This position offers you a remarkable chance to be at the forefront of Artificial Intelligence advancements and make significant contributions to the evolution of intelligent systems through the utilization of Retrieval-Augmented Generation (RAG) frameworks, vector databases, and real-time inference APIs. Your responsibilities will include fine-tuning and enhancing open-source LLMs tailored to specific business sectors, building and managing RAG pipelines utilizing tools like LangChain, FAISS, and ChromaDB, creating LLM-powered APIs for applications like chatbots, Q&A systems, summarization, and classification, as well as designing effective prompt templates and implementing chaining strategies to augment LLM performance across diverse contexts. To excel in this role, you must possess a deep understanding of NLP principles and advanced deep learning techniques for text data, hands-on experience with LLM frameworks like Hugging Face Transformers or OpenAI APIs, familiarity with tools such as LangChain, FAISS, and ChromaDB, proficiency in developing REST APIs for machine learning models, proficiency in Python along with expertise in libraries such as PyTorch or TensorFlow, and a solid grasp of data structures, embedding techniques, and vector search systems. Desirable qualifications include prior experience in LLM fine-tuning and evaluation, exposure to cloud-based ML deployment on platforms like AWS, GCP, or Azure, and a background in information retrieval, question answering, or semantic search. If you are passionate about generative AI and eager to work with cutting-edge NLP and LLM technologies, we are excited to connect with you.,

You will be responsible for designing, building, and deploying scalable NLP/ML models for real-world applications. Your role will involve fine-tuning and optimizing Large Language Models (LLMs) using techniques like LoRA, PEFT, or QLoRA. You will work with transformer-based architectures such as BERT, GPT, LLaMA, and T5, and develop GenAI applications using frameworks like LangChain, Hugging Face, OpenAI API, or RAG (Retrieval-Augmented Generation). Writing clean, efficient, and testable Python code will be a crucial part of your tasks. Collaboration with data scientists, software engineers, and stakeholders to define AI-driven solutions will also be an essential aspect of your work. Additionally, you will evaluate model performance and iterate rapidly based on user feedback and metrics. The ideal candidate should have a minimum of 3 years of experience in Python programming with a strong understanding of ML pipelines. A solid background and experience in NLP, including text preprocessing, embeddings, NER, and sentiment analysis, are required. Proficiency in ML libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers, and spaCy is essential. Experience with GenAI concepts, including prompt engineering, LLM fine-tuning, and vector databases like FAISS and ChromaDB, will be beneficial. Strong problem-solving and communication skills are highly valued, along with the ability to learn new tools and work both independently and collaboratively in a fast-paced environment. Attention to detail and accuracy is crucial for this role. Preferred skills include theoretical knowledge or experience in Data Engineering, Data Science, AI, ML, RPA, or related domains. Certification in Business Analysis or Project Management from a recognized institution is a plus. Experience in working with agile methodologies such as Scrum or Kanban is desirable. Additional experience in deep learning and transformer architectures and models, prompt engineering, training LLMs, and GenAI pipeline preparation will be advantageous. Practical experience in integrating LLM models like ChatGPT, Gemini, Claude, etc., with context-aware capabilities using RAG or fine-tuning models is a plus. Knowledge of model evaluation and alignment, as well as metrics to calculate model accuracy, is beneficial. Data curation from sources for RAG preprocessing and development of LLM pipelines is an added advantage. Proficiency in scalable deployment and logging tooling, including skills like Flask, Django, FastAPI, APIs, Docker containerization, and Kubeflow, is preferred. Familiarity with Lang Chain, LlamaIndex, vLLM, HuggingFace Transformers, LoRA, and a basic understanding of cost-to-performance tradeoffs will be beneficial for this role.,

As a Data Scientist specializing in Natural Language Processing (NLP) and Large Language Models (LLMs), you will play a crucial role in designing, fine-tuning, and deploying cutting-edge open-source and API-based LLMs to address real-world challenges. Your primary focus will be on creating robust GenAI pipelines, innovative internal tools, and engaging client-facing applications. You will have the exciting opportunity to work at the forefront of AI technology, contributing to the advancement of intelligent systems through the utilization of Retrieval-Augmented Generation (RAG) frameworks, vector databases, and real-time inference APIs. Your responsibilities will include fine-tuning and optimizing open-source LLMs for specific business domains, constructing and managing RAG pipelines using tools like LangChain, FAISS, and ChromaDB, as well as developing LLM-powered APIs for diverse applications such as chat, Q&A, summarization, and classification. Additionally, you will be tasked with designing effective prompt templates and implementing chaining strategies to enhance LLM performance across various contexts. To excel in this role, you should possess a strong foundation in NLP fundamentals and deep learning techniques for text data, hands-on experience with LLM frameworks like Hugging Face Transformers or OpenAI APIs, and familiarity with tools such as LangChain, FAISS, and ChromaDB. Proficiency in developing REST APIs to support ML models, expertise in Python programming with knowledge of libraries like PyTorch or TensorFlow, and a solid grasp of data structures, embedding techniques, and vector search systems are also essential. Preferred qualifications include prior experience in LLM fine-tuning and evaluation, exposure to cloud-based ML deployment (AWS, GCP, Azure), and a background in information retrieval, question answering, or semantic search. If you are passionate about generative AI and eager to contribute to the latest developments in NLP and LLMs, we are excited to connect with you.,

4+ years of experience in implementing and deploying Django applications in an enterprise-grade environment Experts in using source control management tools like Git and GitHub Experience in creating and scaling highly performing REST APIs Experience working with PostgreSQL, My SQL, and MS SQL A good understanding of AWS and the core services they offer Must have a hands-on experience with the OpenAI model (such as GPT4 / 4o mini) Must know LLM Model Training & Fine-tuning. Must know OpenCV and Pytorch / TensorFlow Knowledge of software development methodologies, such as Agile or Scrum Good to have, Hands-on experience on generative AI projects in real-world applications Experience in optimizing and fine-tuning generative models to improve performance, efficiency, and scalability, considering factors such as model size, computational requirements, and memory constraints knowledge of LangChain; And different chain types like ConversationalRetrieval Chain, SQLDatabase Chain etc. Knowledge of ChromaDb or Pinecone Vector Db Design, develop and refine AI-generated text prompts for various applications. Familiarity with cloud platforms such as Azure

Proficiency in Python, LangChain, LangGraph and GenAI APIs. Hands-on experience with vector databases (Pinecone, FAISS, ChromaDB). Understanding of Agentic AI, LLMs, transformers, and orchestration frameworks. Exposure to cloud services (AWS/GCP/Azure) and CI/CD practices. Stay current with AI trends and toolsSourcing & Screening US profiles.

Dear Candidate, A Warm Greeting for SAIS IT Services! We are hiring for of product development for our client. Interested people can share your CV to Jyoti.r@saisservices.com, For more queries, kindly reach me on 8360298749 with the below mentioned details; Please fill the below details: Total Exp- CTC- ECTC- Notice Period- Current Location- Comfortable for Work from Office- Job Description: Were Hiring: of product development Location: Remote Job Title: of product development Experience 2+ years Location Hyderabad Work mode: Remote Notice Period: immediate -15 Days JOB DESCRIPTION SENIOR FULL STACK DEVELOPER Required - Using vector stores (e.g., Pinecone, ChromaDB) and embedding models. Role specifics Be a part of the core scrum team involved in the development of the flagship health care suite Ready to collaborate with cross-functional teams to define, design, and ship new features comprising of creating new interfaces and REST APIs and integrations Unit-test code for robustness, including edge cases, usability, and general reliability Implement AI workflows including prompt engineering, vector databases, embedding models, and fine-tuning where applicable. Optimize applications for performance, scalability, and security. Implement user stories through high quality code Passionate about technology, self-motivated, and eager to continue learning as well as collaborate with others Participate in bug fixes and grooming sessions Regards, Jyoti Rani 8360298749 Jyoti.r@saisservices.com

Here's a detailed overview of the Manager, Machine Learning Engineering (Specializing in Generative AI) role at Publicis Sapient in Hyderabad, Telangana, India: Company Description Publicis Sapient is a digital transformation partner that helps established organizations achieve their future, digitally-enabled state, both in how they work and how they serve their customers. They unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and creative problem-solving . United by their core values and purpose of helping people thrive in the brave pursuit of next, their 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate their clients businesses by designing the products and services their customers truly value. Overview: Manager, Machine Learning Engineering (Generative AI Specialist) Publicis Sapient is seeking an experienced Manager, Machine Learning Engineering to lead their talented team of AI and data science experts. In this influential role, you will be responsible for developing and implementing solutions that address complex business challenges across a wide range of industries, empowering clients to revolutionize their businesses by harnessing the potential of advanced technology. As a Manager, Machine Learning Engineering, you will collaborate with cross-functional teams to strategize, develop, and deliver machine learning models tailored to meet specific business objectives. You will be responsible for overseeing the entire lifecycle of these models, from data preprocessing and algorithm selection to performance evaluation and seamless integration into production systems. This role has a specific focus on Generative AI . Your Impact: What You'll Achieve As a Manager, Data Science specializing in Generative AI, you will: Lead AI-Driven Innovations: Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences. Strategic Collaboration: Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data-driven solutions aligned with organizational goals. Foster a High-Performance Team: Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning. Deliver Business Impact: Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP , ensuring measurable outcomes. Optimize AI Pipelines: Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real-time data processing challenges. Customize AI Models: Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain-specific requirements. Promote Data-Driven Decision-Making: Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact. Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions. Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation. Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS, and Azure to address real-world business problems with precision and efficiency. Stay at the Cutting Edge: Keep up-to-date with emerging trends and innovations in AI and data science, identifying opportunities to incorporate the latest advancements into projects. Responsibilities Design AI Systems: Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization. Develop NLP Pipelines: Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation. Integrate Multi-Modal Systems: Combine data modalities such as text, images, and metadata for enriched user interactions and insights. Optimize AI Pipelines: Innovate in latency reduction, scalability, and real-time responsiveness for AI systems in production. Collaborate on AI Innovation: Work with business stakeholders to identify opportunities and deliver impactful AI-driven solutions. Qualifications: Your Skills & Experience Overall Experience: 8 to 15 years of experience. Generative AI Experience: At least 2 years of Gen AI experience . LLM Fine-tuning: Fine-tuning experience with Large Language Models (LLMs, VLLMs, or Vision models) . Distributed Training/Inference: Experience with distributed training or inference frameworks like Ray, vllm, openllm, bentoML etc. Generative AI Frameworks: Experience with frameworks like LangChain, Llamaindex for building maintainable, scalable Generative AI applications. LLM Deployment/Optimization: Deployment experience or optimized hosting experience of Large Language Models (LLMs, VLLMs, or Vision models) . Vector Databases: Experience working with any Vector database like Milvus, FAISS, ChromaDB etc. Agent Development: Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc. Prompt Engineering: Experience with prompt engineering. Market Trends: Keeping up with latest market trends. Open Source LLMs: Experience working with open-source large language models from HuggingFace . Cloud Providers: Experience working with at least one public cloud provider such as Azure, AWS, or GCP . Container Technology: Experience working with container technology like Docker, ECS etc. DevOps & CI/CD: Experience with DevOps practices and CI/CD pipelines for data solutions. Production Deployment: Experience in deploying solutions to production with Kubernetes or OpenShift . ML Workflow Management: Experience with managing ML workflows with MLFlow or KubeFlow .

Tech stack required: Programming languages: Python Public Cloud: AzureFrameworks: Vector Databases such as Milvus, Qdrant/ ChromaDB, or usage of CosmosDB or MongoDB as Vector stores. Knowledge of AI Orchestration, AI evaluation and Observability Tools. Knowledge of Guardrails strategy for LLM. Knowledge on Arize or any other ML/LLM observability tool. Experience: Experience in building functional platforms using ML, CV, LLM platforms. Experience in evaluating and monitoring AI platforms in production Nice to have requirements to the candidate Excellent communication skills, both written and verbal. Strong problem-solving and critical-thinking abilities. Effective leadership and mentoring skills. Ability to collaborate with cross-functional teams and stakeholders. Strong attention to detail and a commitment to delivering high-quality solutions. Adaptability and willingness to learn new technologies. Time management and organizational skills to handle multiple projects and priorities.

BMC is looking for a talented Python Developer to join our family working on complex and distributed software, developing, and debugging software products, implementing features, and assisting the firm in assuring product quality. Here is how, through this exciting role, YOU will contribute to BMC's and your own success: We are seeking a Python with AI/ML Developer to join a highly motivated team responsible for developing and maintaining innovation for mainframe capacity and cost management. As an Application Developer at BMC, you will be responsible for: Developing and integrating AI/ML models with a focus on Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Vector Databases to enhance intelligent decision-making. Building scalable AI pipelines for real-time and batch inference, optimizing model performance, and deploying AI-driven applications. Implementing RAG-based architectures using LLMs (Large Language Models) for intelligent search, chatbot development, and knowledge management. Utilizing vector databases (e.g., FAISS, ChromaDB, Weaviate, Pinecone) to enable efficient similarity search and AI-driven recommendations. Developing modern web applications using Angular to create interactive and AI-powered user interfaces. To ensure youre set up for success, you will bring the following skillset experience: 7+ years of experience in designing and implementing AI/ML-driven applications Strong proficiency in Python and AI/ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers, LangChain. Experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone) for semantic search and embeddings. Hands-on expertise in LLMs (GPT, LLaMA, Mistral, Claude, etc.) and fine-tuning/customizing models. Proficiency in Retrieval-Augmented Generation (RAG) and prompt engineering for AI-driven applications. Experience with Angular for developing interactive web applications. Experience with RESTful APIs, FastAPI, Flask, or Django for AI model serving. Working knowledge of SQL and NoSQL databases for AI/ML applications. Hands-on experience with Git/GitHub, Docker, and Kubernetes for AI/ML model deployment.

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

Role Overview Join our Pune AI Center of Excellence to drive software and product development in the AI space. As an AI/ML Engineer, youll build and ship core components of our AI products—owning end-to-end RAG pipelines, persona-driven fine-tuning, and scalable inference systems that power next-generation user experiences. Key Responsibilities Model Fine-Tuning & Persona Design Adapt and fine-tune open-source large language models (LLMs) (e.g. CodeLlama, StarCoder) to specific product domains. Define and implement “personas” (tone, knowledge scope, guardrails) at inference time to align with product requirements. RAG Architecture & Vector Search Build retrieval-augmented generation systems: ingest documents, compute embeddings, and serve with FAISS, Pinecone, or ChromaDB. Design semantic chunking strategies and optimize context-window management for product scalability. Software Pipeline & Product Integration Develop production-grade Python data pipelines (ETL) for real-time vector indexing and updates. Containerize model services in Docker/Kubernetes and integrate into CI/CD workflows for rapid iteration. Inference Optimization & Monitoring Quantize and benchmark models for CPU/GPU efficiency; implement dynamic batching and caching to meet product SLAs. Instrument monitoring dashboards (Prometheus/Grafana) to track latency, throughput, error rates, and cost. Prompt Engineering & UX Evaluation Craft, test, and iterate prompts for chatbots, summarization, and content extraction within the product UI. Define and track evaluation metrics (ROUGE, BLEU, human feedback) to continuously improve the product’s AI outputs. Must-Have Skills ML/AI Experience: 3–4 years in machine learning and generative AI, including 18 months on LLM- based products. Programming & Frameworks: Python, PyTorch (or TensorFlow), Hugging Face Transformers. RAG & Embeddings: Hands-on with FAISS, Pinecone, or ChromaDB and semantic chunking. Fine-Tuning & Quantization: Experience with LoRA/QLoRA, 4-bit/8-bit quantization, and model context protocol (MCP). Prompt & Persona Engineering: Deep expertise in prompt-tuning and persona specification for product use cases. Deployment & Orchestration: Docker, Kubernetes fundamentals, CI/CD pipelines, and GPU setup. Nice-to-Have Multi-modal AI combining text, images, or tabular data. Agentic AI systems with reasoning and planning loops. Knowledge-graph integration for enhanced retrieval. Cloud AI services (AWS SageMaker, GCP Vertex AI, or Azure Machine Learning)

About the job: The Red Hat, Experience Engineering (XE) team is looking for a skilled Python Developer with 2+ years of experience to join our Software Engineering team. In this role, the ideal candidate should have a strong background in Python development, a deep understanding of LLMs, and the ability to debug and optimize AI applications. Your work will directly impact our product development, helping us drive innovation and improve the customer experience. What will you do? Develop and maintain Python-based applications, integrating LLMs and AI-powered solutions. Collaborate with cross-functional teams (product managers, software engineers, and data teams) to understand requirements and translate them into data-driven solutions. Assist in the development, testing, and optimization of AI-driven features. Optimize performance and scalability of applications utilizing LLMs. Debug and resolve Python application errors, ensuring stability and efficiency. Conduct exploratory data analysis and data cleaning to prepare raw data for modelling. Optimize and maintain data storage and retrieval systems for model input/output. Research and experiment with new LLM advancements and AI tools to improve existing applications. Document workflows, model architectures, and code to ensure reproducibility and knowledge sharing across the team. What will you bring? Bachelor's degree in Computer Science, Software Engineering, or a related field with 2+ years of relevant experience. Strong proficiency in Python, including experience with frameworks like FastAPI/ Flask, or Django. Understanding of fundamental AI/ML concepts, algorithms, techniques and implementation of workflows. Familiarity with DevOps/MLOps practices and tools for managing the AI/ML lifecycle in production environments. Understanding of LLM training processes and data requirements. Experience in LLM fine-tuning, RAG and prompt engineering. Hands-on experience with LLMs (e.g., OpenAI GPT, Llama, or other transformer models) and their integration into applications(e.g. LangChain or Llama Stack). Familiarity with REST APIs, data structures, and algorithms. Strong problem-solving skills with the ability to analyze and debug complex issues. Experience with Git, CI/CD pipelines, and Agile methodologies. Experience working with cloud-based environments (AWS, GCP, or Azure) is a plus. Knowledge of vector databases (e.g., Pinecone, FAISS, ChromaDB) is a plus.