9 Chromadb Jobs

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.

Python LLM Engineer (WFH) Experience: 3 - 5 Years Salary: INR 20,00,000-35,00,000 / year Preferred Notice Period : Within 15 days Shift : 10:30 AM to 7:30 PM IST Opportunity Type: Remote Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients.) Must have skills required : API, Communication, LangChain, LLMs, Pinecone/ Weaviate/ FAISS/ ChromaDB, rag, AWS, Python Good to have skills : CI/CD, multimodal AI, Prompt engineering, Reinforcement Learning, Voice AI Platformance (One of Uplers' Clients) is Looking for: Python LLM Engineer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description We are seeking a highly skilled Python LLM Engineer to join our AI team. The ideal candidate should have deep expertise in large language models (LLMs), experience in building Retrieval-Augmented Generation (RAG) systems, and a strong background in AI-driven applications. This role requires hands-on experience with LangChain, multimodal AI, vector databases, agentic AI, and cloud-based AI infrastructure, particularly AWS and AWS Bedrock. Python will be the primary development language for this role. Key Responsibilities: Design, develop, and optimize applications leveraging LLMs using LangChain and other frameworks. Build and fine-tune Retrieval-Augmented Generation (RAG) based AI systems for efficient information retrieval. Implement and integrate major LLM APIs such as OpenAI, Anthropic, Google Gemini, and Mistral. Develop and optimize AI-driven voice applications and conversational agents using Python. Research and apply the latest advancements in AI, multimodal models, and vector databases. Architect and deploy scalable AI applications using AWS services, including AWS Bedrock. Design and implement vector search solutions using Pinecone, Weaviate, FAISS, or similar technologies. Develop agentic AI products that leverage autonomous decision-making and multi-agent coordination. Write efficient and scalable backend services in Python for AI-powered applications. Develop and optimize AI model fine-tuning and inference pipelines in Python. Implement end-to-end MLOps pipelines for model training, deployment, and monitoring using Python-based tools. Optimize LLM inference for performance and cost efficiency using Python frameworks. Ensure the security, scalability, and reliability of AI systems deployed in cloud environments. Required Skills and Experience: Strong experience with Large Language Models (LLMs) and their APIs (OpenAI, Anthropic, Cohere, Google Gemini, Mistral, etc.). Proficiency in LangChain and experience in developing modular AI pipelines. Deep knowledge of Retrieval-Augmented Generation (RAG) and its implementation. Experience with voice AI technologies, ASR (Automatic Speech Recognition), and TTS (Text-to-Speech), using Python-based frameworks. Familiarity with multimodal AI models (text, image, audio, and video processing) and Python libraries such as OpenCV, PIL, and SpeechRecognition. Hands-on experience with vector databases (Pinecone, Weaviate, FAISS, ChromaDB, etc.). Strong background in developing agentic AI products and autonomous AI workflows. Expertise in Python for AI/ML development, including libraries like TensorFlow, PyTorch, Hugging Face, FastAPI, and LangChain. Experience with AWS cloud services, including AWS Bedrock, Lambda, S3, and API Gateway, with Python-based implementations. Strong understanding of AI infrastructure, model deployment, and cloud scalability. Preferred Qualifications: Experience in reinforcement learning and self-improving AI agents. Exposure to prompt engineering, chain-of-thought prompting, and function calling. Prior experience in building production-grade AI applications in enterprise environments. Familiarity with CI/CD pipelines for AI model deployment and monitoring, using Python-based tools such as DVC, MLflow, and Airflow. Why Join Us? Work with cutting-edge AI technologies and build next-gen AI products. Be part of a highly technical and innovative AI-driven team. Competitive salary, stock options, and benefits. Opportunity to shape the future of AI-driven applications and agentic AI systems. Engagement Type: Direct-hire on the TBD payroll on behalf of platformance Job Type: Permanent Location: Remote Working time: 10:30 AM to 7:30 PM IST Interview Process - The HR team will conduct an initial culture fit assessment before technical rounds. Initial Technical Discussion: Live discussion to assess core competencies. Technical Assignment: Candidates will be given 4 days to complete a hands-on coding test. Final Interview (Optional): Review of the coding test and further technical discussion if required. How to Apply? Easy 3-Step Process: Step 1: Click On Apply! And Register or Login on our portal Step 2: Upload updated Resume & Complete the Screening Form Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: Platformance is a Growth Technology Platform that helps brands connect with customers using a pay-per-outcome model. Platformance is a growth technology platform built to help advertisers achieve measurable business outcomes, not just marketing results. Our mission is to simplify the complexities of digital advertising while ensuring every campaign delivers tangible results. About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. ( Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

AI Engineer, for an early-stage Generative AI startup who can help us translate Product specs into a high-performing and scalable product. Also help in improving functionality of product. End goal is to achieve product-market objectives.

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.