25 Vector Search Jobs

You have 5+ years of backend or full-stack development experience, including a minimum of 3 years specializing in Generative and Agentic AI. Your expertise lies in creating APIs utilizing REST, GraphQL, and gRPC, emphasizing on performance, versioning, and security. Proficiency in Python is required, with additional knowledge in TypeScript/Node.js, Go, or Java. You should possess a deep understanding of LLM integration and orchestration (OpenAI, Claude, Gemini, Mistral, LLaMA, etc.). Moreover, you must have hands-on experience with frameworks like LangChain, LlamaIndex, CrewAI, and Autogen. Familiarity with vector search, semantic memory, and retrieval-based augmentation tools such as FAISS or Qdrant is preferred. A solid grasp of cloud infrastructure (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes) is also essential for this role.,

Role: Senior AI/ML Engineer Function: Machine Learning / AI Engineering Industry: Fintech, SaaS, Artificial Intelligence About Company The client is an early-stage, venture-backed fintech using AI to simplify cash-flow analytics for high-volume B2C businesses. Its platform pairs natural-language queries with machine learning to deliver real-time insights and friction-free reconciliation. You join a small, fast-moving team that prizes ownership, experimentation, and transparent collaboration. The mission is clear: give operators instant, accurate financial visibility so they can scale with confidence. Position Overview You lead the end-to-end AI charter that powers financial automation, intelligent reconciliation, and anomaly detection. You shape the GenAI roadmap, productionize cutting-edge ML systems, and build a world-class teamall while delivering reliable, compliant, and low-latency solutions for transactional finance. Role & Responsibilities Define the AI and GenAI vision for reconciliation, document understanding, financial classification, and payment behavior intelligence. Translate product problems into scalable ML systems and GenAI workflows. Research, experiment, and productionize LLM-based pipelines tailored to enterprise financial operations. Deploy and maintain ML and LLM pipelines in production, including observability, retries, retraining, and versioning. Implement feedback loops that continuously learn from user actions and corrections. Optimize performance and latency of GenAI systems in high-throughput transactional environments. Ensure data privacy, regulatory compliance, and explainability of AI outputs in financial contexts. Lead, hire, mentor, and grow a team of ML and GenAI engineers. Collaborate with product managers, backend engineers, and data engineers to ship AI-powered features. Evangelize responsible AI practices and an experimentation culture across the organization. Must have Criteria 5+ years in AI/ML with at least 12 years hands-on with LLMs and GenAI. Deep knowledge of ML algorithms, NLP, transformers, vector search, embeddings, classification, and unsupervised learning. Proven track record building and deploying GenAI applications using OpenAI APIs, HuggingFace, LangChain, or LlamaIndex. Strong coding skills in Python and experience with PyTorch or TensorFlow, scikit-learn, pandas, and MLOps tools such as MLflow or Airflow. Hands-on experience fine-tuning LLMs (LoRA, QLoRA, PEFT) and crafting prompts for deterministic outputs. Expertise with OCR/NLP tools for semi-structured document extraction and parsing. Ability to work with unstructured, noisy financial data at scale. End-to-end ownership of ML systems from research through deployment and monitoring. Nice to Have Familiarity with open-source LLMs like Mistral, Claude, LLaMA, or Zephyr. Experience with chunking strategies, prompt templates, and hybrid search in RAG systems. Background in enterprise SaaS or fintech domains such as banking, reconciliation, ERP, or accounting. Knowledge of graph-based ML or probabilistic models for complex transaction flows. Past experience building AI systems in an early-stage startup or as a founding team member. Fintech domain expertise. What We Offer Foundational role where you define how AI evolves at the company. High impact on real-world financial decisions requiring accuracy and auditability. Ownership of deep ML and cutting-edge GenAI problems. Product-first, collaborative culture that values high agency and technical depth. Show more Show less

As an ML Engineer at an early-stage, US-based venture-backed technology company in Gurgaon, you will be responsible for designing and deploying the core recommendation and personalization systems that power the matchmaking experience. Your role will involve engineering the full lifecycle - from design, R&D, to deployment - while laying the foundation for scalable, real-time ranking infrastructure. You will be developing match-making, recommendation, ranking, and personalization systems. Specifically, you will work on creating a novel real-time adaptive matchmaking engine that learns from user interactions and other signals. Your tasks will also include designing ranking and recommendation algorithms that make each user feed feel curated for them. Additionally, you will build user embedding systems, similarity models, and graph-based match scoring frameworks, and deploy models to production using fast iteration loops, model registries, and observability tooling. The ideal candidate for this role is an ML engineer with 3-6 years of experience working on ML Engineering or Data Science. You should have prior experience working in personalization, recommendations, search, or ranking at scale. Exposure to a variety of popular recommendation and personalization techniques, including collaborative filtering, deep retrieval models, learning-to-rank, embeddings with ANN search, and LLM approaches for sparse data personalization is desirable. Experience with end-to-end ML pipelines, vector search, graph-based algorithms, and LLM based approaches would be a significant advantage. Joining this company's founding team will allow you to play a core role in shaping the future of how humans connect in the AI era. The compensation offered includes a range of 30-50 LPA along with ESOPs, providing an opportunity for wealth creation.,

As a Senior Backend Engineer/ Technical Architect on our B2C Platform team in Thane, Maharashtra, you will play a crucial role in designing and developing scalable backend services. With over 5 years of experience in backend development, you will leverage your expertise in Java (Spring Boot) and Python (FastAPI/Django) to make architectural decisions related to infrastructure, real-time data pipelines, and platform observability. Your responsibilities will include integrating Large Language Models (LLMs) and AI-driven workflows into backend systems, collaborating with cross-functional teams, leading system design reviews, and mentoring junior engineers. You will have a deep hands-on experience in building microservices, event-driven architectures, and streaming pipelines, along with proficiency in databases and caching tools such as Redis, PostgreSQL, and PGVector. Preferred skills include working with real-time infrastructure, exposure to AI-driven product features, and a track record of building high-performance consumer platforms from scratch. Additionally, familiarity with frontend tools like ReactJS, DevOps practices (e.g., Docker/Kubernetes, Prometheus, Grafana), and cloud platforms like AWS/GCP is desired. In this role, you will contribute to building a robust and scalable backend for our next-gen B2C platform, implementing intelligent, real-time features that personalize the user experience, and establishing a strong technical foundation to support long-term innovation and growth. If you are passionate about shaping the future of technology and solving meaningful problems at scale, we would love to hear from you.,

As a React Developer at our company, you will be responsible for building modern, scalable UIs and integrating AI-powered features into our product. You will collaborate closely with design, product, and backend teams to deliver high-impact user experiences. Your main responsibilities will include: - Building advanced UIs using React, Hooks, and TypeScript - Managing state with Redux Toolkit, Zustand, or similar tools - Working with REST & GraphQL APIs - Integrating AI features using OpenAI APIs such as ChatGPT and DALLE - Utilizing modern styling tools like Tailwind CSS or Styled Components - Writing clean and testable code with tools like Jest and RTL - Collaborating effectively within Agile teams To excel in this role, you should have the following skills: - Strong proficiency in JavaScript (ES6+) and TypeScript - Experience with AI API integration, specifically with platforms like OpenAI and LangChain - Familiarity with build tools such as Vite/Webpack, CI/CD practices, and Git - Good UX/product thinking abilities and effective communication skills - Bonus points for experience with Next.js, knowledge of vector search, and familiarity with chatbots or streaming AI UIs We are looking for candidates with a minimum of 4 years of relevant experience. This is a full-time position based in Kochi. If you are interested in this opportunity, please send your resume to careers@cabotsolutions.com.,

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

About Zwende: An ISB Alumni Venture, approved by DIPP under Startup India. Zwende is the worlds first creator-to-consumer platform which offers unique creative products, learning and entertainment from independent artists/makers, boutique designers, and rural artisans. Zwende is built to offer the unlimited creativity of the creators and match it to the need, of todays consumers, for individuality and self-expression. Zwende is the only Indian start-up featured by Amazon&aposs Global CTO, Werner Vogels, on his show Now Go Build (NGB). NGB tells stories of global entrepreneurs using cloud-based technologies to solve hard, real-world problems. Watch the show here: https://www.youtube.com/watchv=2n7bm0mteG0 At Zwende, we&aposre not just building products we&aposre reimagining how theyre built. Were crafting a world-class, AI-first product and technology team, and we&aposre on the hunt for an AI Product Analyst whos ready to redefine what this role means. This isn&apost your typical analyst gig. Youll be part of a new generation of product thinkers those who blend data, instinct, and cutting-edge AI to shape decisions, automate insights, and accelerate product velocity. You wont just support the product; youll co-create it, using AI as your co-pilot. If you&aposre excited about operating at 10x speed, impact, and creativity and building the muscle to lead AI-native product roles across the tech ecosystem this is your launchpad. If this has got you excited, lets dive deeper. Here are all the things that the AI Product Analyst would do: Combine data across Google Analytics, Meta Ads & Shopify to come up with unique product/business hypothesis that will move the business forward Spin up automated A/B testing frameworks using tools like GrowthBook or PostHog, powered by AI agents to monitor results, adjust hypotheses, and even auto-suggest next test variations. Learn vibe coding on Replit/Cursor etc, to be able to prototype new product ideas and validate them in a matter of days, before they get into regular product development Build Agents using n8n or Agent builder toolkits which can automate workflows for the entire organization Train and deploy lightweight recommender systems (e.g., using embeddings + Shopify data) that surface relevant products or bundles dynamically. Lead AI onboarding sessions for other team members, making AI-first thinking part of the org DNA from designers and marketers to CX and ops. To become successful in this role, you will need: Core Analytical & Product Skills Strong grounding in data analysis fluency in SQL, Excel/Sheets, and experience with tools like GA4, Shopify analytics, and Meta Ads Manager. Ability to connect the dots across platforms and datasets to uncover user behavior insights, marketing ROI, and conversion gaps. Comfort with rapid experimentation running A/B tests, interpreting results, and suggesting actionable changes. Experience working closely with product teams to inform feature prioritization and validate product hypotheses with data. AI-Native Thinking Hands-on experience (or deep curiosity) with tools like Replit, Cursor, n8n, or LangChain to automate, prototype, or build internal tools. Familiarity with how LLMs work, and how they can be used for analysis, summarization, ideation, and UX (even if you haven&apost fine-tuned one yourself). Ability to design, prompt, or configure AI agents to automate workflows (internal dashboards, reporting agents, CX support agents, etc). Bonus: Exposure to embeddings, vector search, or recommendation systems in any side project or course. Mindset & Traits Youre a builder-analyst someone who doesn&apost just observe problems but wants to solve them by creating scrappy tools or internal agents. You learn by doing youre excited to ship rough prototypes, learn from real-world signals, and iterate quickly. You think from first principles, not just playbook. You&aposre not afraid to question default tools or methods if you see a better way. Youre deeply curious about AI and how it can be applied creatively to real business and user problems. Youre comfortable with ambiguity this role wont come with rigid requirements, but with room to invent and define it. Additional Information: Flexible Working Hours. Indicative timing: 9 AM to 7 PM. Monday to Saturday. Location: Work from Home, might convert to work from office Work closely with the leadership team at Zwende Exponential career growth based on performance A flat org and informal structure where performance and superiority of thought drive all decisions Show more Show less

As a Senior Machine Learning Engineer at our AI/ML team, you will be responsible for designing and building intelligent search systems. Your focus will be on utilizing cutting-edge techniques in vector search, semantic similarity, and natural language processing to create innovative solutions. Your key responsibilities will include designing and implementing high-performance vector search systems using tools like FAISS, Milvus, Weaviate, or Pinecone. You will develop semantic search solutions that leverage embedding models and similarity scoring for precise and context-aware retrieval. Additionally, you will be expected to research and integrate the latest advancements in ANN algorithms, transformer-based models, and embedding generation. Collaboration with cross-functional teams, including data scientists, backend engineers, and product managers, will be essential to bring ML-driven features from concept to production. Furthermore, maintaining clear documentation of methodologies, experiments, and findings for technical and non-technical stakeholders will be part of your role. To qualify for this position, you should have at least 3 years of experience in Machine Learning, with a focus on NLP and vector search. A deep understanding of semantic embeddings, transformer models (e.g., BERT, RoBERTa, GPT), and hands-on experience with vector search frameworks is required. You should also possess a solid understanding of similarity search techniques such as cosine similarity, dot-product scoring, and clustering methods. Strong programming skills in Python and familiarity with libraries like NumPy, Pandas, Scikit-learn, and Hugging Face Transformers are necessary. Exposure to cloud platforms, preferably Azure, and container orchestration tools like Docker and Kubernetes is preferred. This is a full-time position with benefits including health insurance, internet reimbursement, and Provident Fund. The work schedule consists of day shifts, fixed shifts, and morning shifts, and the work location is in-person. The application deadline for this role is 18/04/2025.,

AI Explorer / Curator Location: Remote (South or Southeast Asia preferred) Reports to: Director of Development, Singapore Language: English (professional fluency required) Note: We are not able to offer visa sponsorship or relocation Job Description Help Us Discover What AI Can Actually Do for Real Work, Right Now Were looking for someone who thrives on curiosity and fast learning. Someone who tracks whats emerging, experiments with whats useful, and helps others find practical value in the ever-changing world of AI. This role is about identifying which tools, methods, or models are worth exploringthen helping internal teams understand how they could apply them. Its a cross between applied research, internal enablement, and being a trusted first-mover. You dont need to build full systems. But you do need to spot patterns, translate whats possible into whats usable, and guide others in how to get started. What Youll Work On Testing new tools, workflows, models, or agentsand identifying which ones are useful for internal teams Prototyping small examples that show how a tool might support strategy, design, engineering, or operations Summarizing what a new method can do, where it fits, and how it could be adapted Working closely with tool builders and platform leads to inform whats built next Sharing recommendations with clear reasoning and attention to real-world use What You Bring Curiosity about how AI tools actually behavenot just what they claim to do Confidence exploring unstructured spaces and translating them for others A mindset that focuses on usefulness, not hype Interest in helping others get more value from AIeven if theyre new to it Comfort documenting and presenting findings clearly Technologies You May Work With ChatGPT, Claude, Gemini, and other LLM interfaces LangChain, vector search, RAG patterns, multi-agent frameworks No-code or semi-code tools like Zapier, Notion, or AI-enhanced work platforms Lightweight scripting if needed, but this is not primarily a development role Why This Role Matters There are more tools than anyone can keep up withbut also more potential than most teams know how to unlock. This role helps ensure we explore whats possible without losing focus. It supports internal teams by identifying what works, why it matters, and how to apply it thoughtfully. Youll be helping shape how generative AI is adoptednot by building everything, but by helping us choose what to build next. Show more Show less

Role & responsibilities Develop and maintain search functionality in the Fusion Lucidworks platform. Experience - 3 years to 6 years Connect databases for pulling data into Fusion from various types of data sources. Implement real time indexing of large-scale data sets residing in database files and other sources, using Fusion as the search platform Proven experience in implementing and maintaining enterprise search solutions in large-scale environments. Experience developing and deploying Search solutions in a public cloud such as AWS. Proficient in high-level programming languages: Java, Scala, Python. Familiarity with containerization, scripting, cloud platforms, and CI/CD. Work with Business analyst and customers to translate business needs into software solutions Have understanding of the software development process, version control, etc.

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.,

We are looking for a passionate and experienced Full Stack Developer with Python expertise to join our core product development team. This role is perfect for someone who has independently built or led full stack projects and has the leadership potential to guide other developers. If you're excited about AI tools like ChatGPT , Claude , GitHub Copilot , and Tabnine , and want to build smart, scalable web applications is the opportunity for you. Responsibilities:- Develop, maintain, and scale full-stack applications using React.js, Next.js, Node.js, TypeScript, and Python Integrate AI APIs (OpenAI, Claude) and build custom chat interfaces and intelligent workflows Apply prompt engineering techniques to enhance AI accuracy and UX Work with LangChain, AutoGen, Manus for building advanced AI-driven applications Leverage AI-native coding tools like GitHub Copilot, Cursor, Tabnine, Replit for efficient development Collaborate closely with UI/UX designers, backend teams, and AI researchers Optimize applications for performance, scalability, and cross-platform compatibility Deploy applications using tools like Vercel, Supabase, Railway, and orchestrate flows using n8n Actively participate in Agile/Scrum ceremonies and sprint plannin g Required Skills:- 45 years of hands-on experience in full-stack development Strong proficiency in JavaScript , React , Next.js , Node.js , TypeScript, Python Experience with AI APIs such as OpenAI and Claude Practical knowledge of prompt engineering and vector search concepts Familiarity with modern IDEs and AI coding assistants ( GitHub Copilot, Amazon Q , Tabnine , etc.) Experience working with PostgreSQL and deployment tools like Vercel and Railway Excellent problem-solving and communication skills Leadership qualities and the ability to mentor junior developers Tech Stack You’ll Use: Frontend: React, Next.js Backend: Node.js, Express, Python Database: PostgreSQL (hosted or via Supabase) AI Tools: OpenAI, Claude, LangChain, AutoGen, Manus Dev Tools: GitHub, Cursor, Replit, GitHub Copilot, Tabnine Automation & DevOps: n8n, Railway, Vercel Why Join Us? Be at the forefront of real-world AI innovation Work on cutting-edge AI + web technology Join a talented, collaborative, and forward-thinking team Gain growth opportunities in a fast-evolving tech space Contribute to exciting projects that make an impact

As a Senior AI Engineer specialized in Voice AI and Autonomous Agents at Spyne, you will be responsible for owning and building Spynes in-house voice bot stack. This pivotal role involves leveraging your expertise in LLMs, ASR/TTS, and voice UX to develop immersive, human-like conversations between auto dealerships and their customers. Located in Gurugram, you will work from the office five days a week to drive the development of cutting-edge AI solutions in the automotive retail sector. Your primary responsibilities will include: - Voice AI Stack Ownership: Developing and managing the complete voice bot pipeline encompassing ASR, NLU, dialog state management, tool calling, and TTS to deliver a seamless conversation experience. - LLM Orchestration & Tooling: Designing systems utilizing MCP to facilitate structured context exchange between real-time ASR, memory, APIs, and the LLM. - RAG Integration: Implementing retrieval-augmented generation to support responses based on dealership knowledge bases, inventory data, recall lookups, and FAQs. - Vector Store & Memory: Creating scalable vector-based search functionalities for dynamic FAQ handling, call recall, and user-specific memory embedding. - Latency Optimization: Engineering low-latency, streaming ASR + TTS pipelines and optimizing turn-taking models for natural conversations. - Model Tuning & Hallucination Control: Customizing tone, reducing hallucinations, and aligning responses with business objectives via fine-tuning, LoRA, or instruction tuning. - Instrumentation & QA Looping: Establishing robust observability, conducting real-time call QA processes, and analyzing interruptions, hallucinations, and fallbacks. - Cross-functional Collaboration: Collaborating closely with product, infra, and leadership teams to scale the voice bot solution to numerous US dealerships effectively. To excel in this role, you should possess: - Architectural Thinking: Ability to comprehend the integration of ASR, LLMs, memory, and tools and design modular, observable, and resilient systems. - LLM Tooling Mastery: Proficiency in implementing tool calling, retrieval pipelines, function calls, or prompt chaining across various workflows. - Fluency in Vector Search & RAG: Expertise in chunking, embedding, indexing, and retrieval processes while avoiding prompt bloat and token overflow. - Latency-First Mindset: Capability to identify and rectify token delays, optimize API round-trip time, and ensure human-like call interactions. - Grounding > Hallucination: Skill in tracing hallucinations to weak prompts, lack of guardrails, or tool access deficiencies and addressing them effectively. - Prototyping Skills: Comfort with building from scratch and rapid iteration using open-source or hosted tools as required. Requirements for this role include: - 5+ years of experience in AI/ML or voice/NLP systems with real-time exposure. - Profound knowledge of LLM orchestration, RAG, vector search, and prompt engineering. - Experience with MCP-style architectures and structured context pipelines between LLMs and APIs/tools. - Familiarity with integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models. - Strong understanding of latency optimization, streaming inference, and real-time audio pipelines. - Proficiency in Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infrastructures (AWS/GCP). - Solid debugging, logging, and QA capabilities for hallucination, grounding, and UX analysis. Join Spyne for a real-world AI impact, a superior team balancing speed with technical depth, high autonomy, and visibility from day one, accelerated career growth, MacBook along with essential tools, and a flat structure focused on meaningful work without unnecessary bureaucracy.,

As a Senior AI Engineer - Voice AI / Autonomous Agents at Spyne, you will have the opportunity to own and build Spynes in-house voice bot stack. In this high-impact individual contributor role, you will be at the intersection of LLMs, ASR/TTS, and voice UX, focusing on creating deeply human, latency-optimized conversations between auto dealerships and their customers. Your main responsibilities will include: Voice AI Stack Ownership: Building and owning the end-to-end voice bot pipeline, including ASR, NLU, dialog state management, tool calling, and TTS to deliver a natural, human-like conversation experience. LLM Orchestration & Tooling: Architecting systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM. RAG Integration: Implementing retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs. Vector Store & Memory: Designing scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding. Latency Optimization: Engineering low-latency, streaming ASR + TTS pipelines and fine-tuning turn-taking models for natural conversation. Model Tuning & Hallucination Control: Using fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals. Instrumentation & QA Looping: Building robust observability, running real-time call QA pipelines, and analyzing interruptions, hallucinations, and fallbacks. Cross-functional Collaboration: Working closely with product, infra, and leadership to scale this bot to thousands of US dealerships. To be successful in this role, you should possess: Architect-level thinking: Understanding how ASR, LLMs, memory, and tools fit together and having the ability to design modular, observable, and resilient systems. LLM Tooling Mastery: Implementing tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows. Fluency in Vector Search & RAG: Knowing how to chunk, embed, index, and retrieve, while avoiding prompt bloat and token overflow. Latency-First Mindset: Debugging token delays, understanding the cost of each API hop, and optimizing round-trip time to maintain human-like interactions. Grounding > Hallucination: Tracing hallucinations back to weak prompts, missing guardrails, or lack of tool access and effectively addressing them. Prototyper at heart: Being unafraid of building from scratch and iterating quickly, utilizing open-source or hosted tools as necessary. The ideal candidate will have: 5+ years of experience in AI/ML or voice/NLP systems with real-time experience. Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering. Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools. Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models. Solid understanding of latency optimization, streaming inference, and real-time audio pipelines. Hands-on experience with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP). Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior. Working at Spyne offers real-world AI impact at scale, a high-performing team that balances speed with technical depth, high autonomy and visibility from day one, rapid career acceleration, access to MacBook and all necessary tools and compute, a flat structure with real work focus, and no BS. Join us in redefining how cars are marketed and sold with cutting-edge Generative AI.,

As a Data Scientist specializing in Generative AI & ML Engineering, your primary responsibility will be to research and develop AI algorithms and models. You will be tasked with analyzing data, constructing predictive models, and employing machine learning techniques to address intricate problems. Your proficiency should encompass a range of skills including proficiency in languages/frameworks such as Fast API and Azure UI Search API (React), as well as expertise in databases and ETL tools like Cosmos DB and Data Factory Data Bricks. In addition, you should have a strong command of Python and R, familiarity with Azure Cloud Basics and Gitlab Pipeline, and experience in deploying AI solutions end-to-end. In addition to your proficient skills, you are expected to possess expert-level knowledge in areas such as Azure Open AI, Open AI GPT Family of models, and Azure Storage Account. Your expertise should extend to machine learning algorithms, deep learning frameworks like TensorFlow and PyTorch, and a solid foundation in mathematics including linear algebra, calculus, probability, and statistics. Furthermore, your role will require proficiency in data analysis tools such as Pandas, NumPy, and SQL, as well as strong statistical and probabilistic modeling skills. Experience with data visualization tools like Matplotlib, Seaborn, and Tableau, along with knowledge of big data technologies like Spark and Hive, will be essential for success in this position. Overall, your experience in AI-driven analytics and decision-making systems, coupled with your ability to develop and deploy AI frameworks and models, will be critical in delivering effective solutions to complex challenges.,

The position of AI & Data Intern at Novasensa in Delhi NCR is a valuable opportunity to contribute to the development of a custom AI Assistant aimed at automating experiments, analyzing lab data, and supporting decision-making in sustainability challenges. As an intern, you will work with the R&D team to shape this tool and apply your programming skills to real-world scenarios. This internship offers a chance to use Python and data skills on an AI system, learn about AI's role in clean-tech innovation, and gain mentorship from a startup team working at the intersection of sustainability, engineering, and software. Your responsibilities as an AI & Data Intern will include supporting the development and testing of internal AI tools, such as programming and automation tasks. You will write Python scripts for data processing, automate R&D tasks, and assist in building backend tools for experiment tracking and analysis. Additionally, you will be involved in data analysis and visualization, where you will analyze lab results, generate visual summaries, and track patterns and insights from recycling experiments. Furthermore, you will contribute to AI Assistant Development by helping with document parsing, semantic search, and improving the performance of the AI assistant using real lab data. The ideal candidate for this internship is a curious and motivated learner with basic to intermediate Python programming skills, an understanding of data structures and functions, familiarity with data visualization tools, and an interest in AI and sustainability. Exposure to AI tools and experience with data cleaning and automation are considered advantageous. Candidates pursuing or holding degrees in Computer Science, Data Science, AI, ML, Statistics, Mathematics, or related fields are encouraged to apply. Past interns have highlighted Novasensa as a unique opportunity to work on deep-tech projects with a real impact on sustainability. If you are passionate about using your coding skills to contribute to a cleaner planet, this internship at Novasensa is the perfect opportunity for you. To apply, send your resume along with a short note explaining why you want to intern at Novasensa and what you hope to learn and contribute to hr@novasensa.com. Early applications are preferred as they are reviewed on a rolling basis. Join Novasensa to learn, build, and make an impact with your code for a greener future.,

Job Responsibilities We are seeking a highly strategic and execution-driven person to join the CEO's office as a (Program and Strategy Manager) and drive the adoption of Agentic AI (autonomous, goal-driven AI systems) across all functionsProduct, Tech, Marketing, Data, Sales, Customer Success, Delivery, Onboarding, HR, Finance, PR, Branding and more. You will act as a bridge across cross-functional teams to ensure alignment and drive the strategic direction of our AI-powered product portfolio. What will you do Cross-Functional Agentic AI Transformation Define and execute the company-wide high-impact agentic AI automation across functions.(e.g., AI-driven sales bots, automated customer onboarding, HR talent matching, finance forecasting). Develop metrics and KPIs to track AI-driven efficiency gains. Lead no-code AI tooling initiatives (e.g., GPT-based automation, AI agents, RPA, AutoML) to empower non-technical teams. Partner with Engineering & Data teams to integrate AI into existing workflows. Program Management and Strategy Develop, implement, and monitor key strategic initiatives that align with the company's overall business objectives. Define, track, and own key business KPIs, ensuring execution of high-impact priorities. Design and lead cross-functional projects to drive business outcomes, such as revenue growth, customer acquisition, and operational efficiency Prepare executive reports, investor decks, and MBR presentations. Provide strategic assistance and support to the senior leadership team Team & Stakeholder Management Act as the bridge between the CEO's Office and department heads to drive AI adoption. Conduct workshops to upskill teams on AI tools and best practices. Manage vendor partnerships (OpenAI, Microsoft, Google AI, etc.) for AI tooling. What you must have 3+ years of experience, preferably in Product, Program Management, or Strategy roles. Expertise in analytics, excel, SQL, and BI tools (Tableau, Looker, Power BI, etc.) Basic familiarity with LLM APIs (e.g., OpenAI, Anthropic, Hugging Face) Technical background with ability to collaborate effectively with ML/AI engineering teams. Exceptional communication skills to explain technical AI concepts to non-technical stakeholders. Excellence in strategic thinking, problem-solving, and decision-making. Analytical mindset with the ability to define and measure success metrics. Ability to thrive in a fast-paced, ambiguous environment.

Build and own the full voice bot pipeline including ASR, NLU, dialog management, tool calling, and TTS. Architect systems using MCP to connect ASR, memory, APIs, and LLMs in real-time. Implement RAG to ground responses using data from knowledge bases, inventory, and FAQs. Design scalable vector search systems for memory embedding and FAQ handling. Engineer low-latency ASR and TTS pipelines, optimizing for natural turn-taking. Apply fine-tuning, LoRA, and instruction tuning to reduce hallucinations and align model tone. Build observability systems and QA pipelines to monitor calls and analyze model behavior. Collaborate with cross-functional teams to scale the voice bot to thousands of users. Design modular, observable, and resilient AI systems. Implement retrieval pipelines, function calls, and prompt chaining across workflows. Expertly chunk, embed, and retrieve documents in RAG systems. Debug latency issues and optimize for low round-trip time. Trace hallucinations to root causes and fix via guardrails or tool access. Build prototypes using open-source or hosted tools with speed and flexibility. 5+ years in AI/ML or voice/NLP with real-time experience. Deep knowledge of LLM orchestration, vector search, and prompt engineering. Experience with ASR (Whisper, Deepgram), TTS (ElevenLabs, Coqui), and OpenAI models. Skilled in latency optimization and real-time audio pipelines. Hands-on with Python, FastAPI, vector DBs, and cloud platforms.

Job Title: AI Engineer Job Type: Contract Location: Offshore (Remote) Start Date: July 28th, 2025 Experience: 5+ Years Shift Time: Till 1 pm EST Duration: 18 weeks Job Responsibilities: Design and implement scalable Gen AI solutions on Azure to meet enterprise needs. Build and optimize AI-based search systems for content discovery and business use cases. Develop agentic AI frameworks capable of autonomous decision-making and task execution. Work on data and content refinement pipelines to improve model performance and output relevance. Collaborate with cross-functional teams including architects, data scientists, and DevOps engineers. Ensure best practices in AI governance, model monitoring, and security are followed. Qualifications Gen AI on Azure (Azure OpenAI, Azure ML, Cognitive Services) Generative AI-based search (e.g., vector search, RAG models, embeddings) Strong foundation in AI/ML principles Experience with data/content pipelines and processing Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow) Preferred Experience: Proven track record in building agentic AI solutions Ability to work independently in a remote setting Experience in delivering short-term, high-impact AI projects

: Generative AI Engineer : 3 to 5 years : We are looking for a Generative AI Engineer with 3 to 5 years of hands-on experience in Retrieval-Augmented Generation (RAG), Agentic AI, and Data Pipelines. The ideal candidate will have real-time experience in developing and deploying AI-powered solutions, working with advanced language models, and optimizing AI workflows for production environments. : Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Build and manage data pipelines for processing, transforming, and feeding structured/unstructured data into AI models. Ensure scalability, performance, and security of AI-driven solutions in production environments. Collaborate with cross-functional teams, including data engineers, software developers, and product managers. Conduct experiments and evaluations to improve AI system accuracy and efficiency. Stay updated with the latest advancements in AI/ML research, open-source models, and industry best practices. & : Hands-on experience with RAG architectures, including vector databases (e.g., Pinecone, ChromaDB, Weaviate, OpenSearch, FAISS). Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes). Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications. Strong understanding of vector search, embedding models, and hybrid retrieval techniques. Experience with optimizing inference and serving AI models in real-time production systems. -- : Experience with multi-modal AI (text, image, audio) and LLM fine tuning. Familiarity with privacy-preserving AI techniques and responsible AI frameworks. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation. ____________________________________________________________________________ "Python/Gen AI Developer" Experience: 5 to 8 Location: Coimbatore/Remote Notice Period: Immediate Joiners are Preferred : Design, develop, and fine-tune Large Language Models (LLMs) for various in-house applications. Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Build and manage data pipelines for processing, transforming, and feeding structured/unstructured data into AI models. Ensure scalability, performance, and security of AI-driven solutions in production environments. Collaborate with cross-functional teams, including data engineers, software developers, and product managers. Conduct experiments and evaluations to improve AI system accuracy and efficiency. Stay updated with the latest advancements in AI/ML research, open-source models, and industry best practices. & : Strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases (e.g., Pinecone, ChromaDB, Weaviate, OpenSearch, FAISS). Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Experience in Python web frameworks such as FastAPI, Django, or Flask. 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). Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications. Strong understanding of vector search, embedding models, and hybrid retrieval techniques. Experience with optimizing inference and serving AI models in real-time production systems. -- : Experience with multi-modal AI (text, image, audio). Familiarity with privacy-preserving AI techniques and responsible AI frameworks. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation. Role & responsibilities Preferred candidate profile

Were seeking a seasoned AI/ML Developer to join our tech team and help build next-generation GenAI products and scalable AI-powered APIs. You’ll architect and deploy intelligent workflows on Google Cloud Platform, integrate cutting-edge LLMs, and design real-time intent-detection systems across multiple user journeys. Key Responsibilities Model Development & Deployment: Build, train and deploy AI/ML models using GCP’s ADK and Vertex AI. Implement prompt-engineering strategies for large language models (e.g., Gemini). Vector Search & Retrieval: Design and maintain vector search pipelines on GCP. Integrate with LangChain and other tools for context-aware retrieval. API & Backend Engineering: Develop secure, scalable RESTful APIs using FastAPI and Python. Automate deployments via GitHub CI/CD workflows. Intent-Detection Systems: Architect multi-flow intent-detection pipelines with high accuracy. Continuously monitor and optimize model performance. Cloud Infrastructure & Security: Enforce best practices for secure, scalable GCP services. Collaborate with DevOps to ensure reliable, automated infrastructure. Collaboration & Documentation: Work closely with cross-functional teams (DevOps, Product, QA). Maintain clear technical documentation and share knowledge. Required Skills & Qualifications: AI/ML Expertise: 4+ years hands-on with AI/ML solutions in production. Proficiency with GCP services: Vertex AI, ADK, Firestore. Vector Search & LLM Integration: Experience building vector search pipelines on GCP. Strong familiarity with Gemini, LangChain, or similar LLM frameworks. Backend Development: Advanced Python skills; production experience with FastAPI. Solid understanding of REST principles, authentication, and security. DevOps & Automation: GitHub Actions (or equivalent) for CI/CD. Infrastructure as Code (Terraform, Deployment Manager, etc.). Intent Detection & NLP: Track record of building intent-classification or NLU systems. Familiarity with metrics and A/B testing for conversational AI. Soft Skills: Excellent problem-solving and analytical abilities. Strong communication skills and a collaborative mindset.

Job Title: Backend Developer (FARM Stack Python, FastAPI/Django, MongoDB) Location: South Bengaluru, Karnataka, India Employment Type: Full-Time Experience Required: 4 to 9 years Work Mode: Work from Office only (No Work from Home or Hybrid option) We are seeking a skilled and experienced Backend Developer to join a fast-paced, mission-driven technology team that is transforming how Indians discover and own properties. You will be part of a platform built using the FARM stack (FastAPI/Django, React, MongoDB), contributing to the design and development of scalable backend architectures, cloud-native systems, and microservices. You will work on high-impact solutions using AWS services, Redis for performance optimization, and OpenSearch for advanced data search. This role is ideal for developers passionate about backend engineering, clean architecture, and meaningful technology innovation. Responsibilities: Build and maintain backend services using Python, FastAPI or Django Architect and implement scalable systems using microservices Design and optimize MongoDB schemas and queries Work with AWS (Lambda, API Gateway, DynamoDB, S3, SQS, SNS) Integrate Redis for caching and session management Implement OpenSearch and vector search for advanced search use cases Write and maintain unit tests following TDD principles using tools like pytest Create and maintain Swagger documentation for APIs Use Git for version control and follow best practices for branching and collaboration Contribute to Agile ceremonies including sprint planning and retrospectives Required Skills: 4 to 9 years of backend development experience in Python Strong experience with FastAPI or Django frameworks Deep understanding of MongoDB and NoSQL schema design Experience building microservices and distributed systems Hands-on experience with AWS cloud and serverless architecture Familiarity with Redis, OpenSearch, and vector-based search Proficiency in unit testing, Git workflows, Swagger, and CI/CD pipelines Experience working in Agile teams Preferred Skills: Docker and Kubernetes CI/CD tools like Jenkins, GitLab CI, or CircleCI Knowledge of API security best practices Experience working with large datasets and high availability systems Please Note: While initial HR and technical rounds will be conducted online, attending a final offline (in-person) interview in Bengaluru is mandatory for shortlisted candidates. The client will not confirm selection or issue an offer letter without this in-person interaction. If you are certain you cannot travel to Bengaluru for the offline interview, we kindly request you not to proceed with the online rounds, as the selection process cannot be completed without a face-to-face meeting.

Job Description: We are looking for a skilled Data / Analytics Engineer with hands-on experience in vector databases and search optimization techniques . You will help build scalable, high-performance infrastructure to support AI-powered applications like semantic search , recommendation systems , and RAG pipelines . Key Responsibilities: Optimize vector search algorithms for performance and scalability. Build pipelines to process high-dimensional embeddings (e.g., BERT , CLIP , OpenAI ). Implement ANN indexing techniques like HNSW , IVF , PQ . Integrate vector search with data platforms and APIs . Collaborate with cross-functional teams (data scientists, engineers, product). Monitor and resolve latency , throughput , and scaling issues. Must-Have Skills: Python AWS Vector Databases (e.g., Elasticsearch , FAISS , Pinecone ) Vector Search / Similarity Search ANN Search Algorithms HNSW , IVF , PQ Snowflake / Databricks Embedding Models – BERT , CLIP , OpenAI Kafka / Flink for real-time data pipelines REST APIs , GraphQL , or gRPC for integration Good to Have: Knowledge of semantic caching and hybrid retrieval Experience with distributed systems and high-performance computing Familiarity with RAG (Retrieval-Augmented Generation) workflows Apply Now if You: Enjoy solving performance bottlenecks in AI infrastructure Love working with cutting-edge ML models and search technologies Thrive in collaborative , fast-paced environments

Hiring AI & Data Retrieval Engineer with expertise in NLQ, Text-to-SQL, LLMs, LangChain, pgVector, PostgreSQL, vector search, Python, AI libraries, Agentic AI & API integration. Exp with NLP, RAG, BI tools, live projects & LLM fine-tuning preferred.

We are seeking a highly skilled and innovative AI/ML Engineer with hands-on experience in developing and deploying intelligent chatbot systems. The ideal candidate will have a strong background in machine learning, natural language processing (NLP), and software engineering, with proven experience building conversational AI systems that deliver real value to users. Below is JD- Design, develop, and deploy AI-driven search solutions for eCommerce platforms to enhance product discovery and relevance. Build and optimize agentic AI chatbots that guide users through personalized shopping experiences, customer service, and post-purchase workflows. Work closely with product managers, UX designers, and developers to translate business requirements into intelligent solutions. Integrate third-party or custom AI/ML services with eCommerce platforms like Shopify, Magento, Adobe Commerce, Salesforce Commerce Cloud , etc. Apply natural language understanding (NLU) and context management for advanced chatbot functionality. Analyze search and conversation data to continuously improve relevance, ranking, and chatbot accuracy. Experiment with generative AI (e.g., OpenAI, Anthropic) for advanced conversational capabilities. Collaborate in an agile environment, participate in code reviews, and contribute to architecture discussions. Fine-tune language models and recommendation engines to personalize user interactions based on behavior, preferences, and purchase history. Monitor performance of chatbot systems and iterate using A/B testing, user feedback, and analytics tools. Ensure chatbot systems comply with privacy, security, and data governance standards relevant to eCommerce and consumer data. Preferred: Experience working with Google Vertex search/ Vector search / Elastic search / Milvus, etc Ecommerce AI search experience. Experience in building and deploying AI/ML solutions, with at least 2 years focused on chatbot development. Proficiency in NLP tools and frameworks (e.g., spaCy, NLTK, Hugging Face, Rasa, Dialogflow, Botpress). Experience working with LLMs and APIs from providers like OpenAI, Anthropic, or Cohere. Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).