9 Vector Stores Jobs

Siemens EDA is a global technology leader in Electronic Design Automation software. Our software tools enable companies around the world to develop highly innovative electronic products faster and more cost-effectively. Our customers use our tools to push the boundaries of technology and physics to deliver better products in the increasingly complex world of chip, board, and system design. Join a dynamic and fast-evolving team that is building next-generation AI-based tools and agent systems for QuestaSim, flagship simulation software at Siemens EDA. We're focused on designing intelligent AI agents, optimizers, and copilots using modern AI/ML techniques. This is an R&D-heavy role with real-world applications, significant autonomy, and room to innovate. This role is based in Noida. But you'll also get to visit other locations in India and globe, so you'll need to go where this job takes you. In return, you'll get the chance to work with teams impacting entire cities, countries, and the shape of things to come. We make real what matters! We are seeking a highly motivated and experienced software engineer with a strong background in AI/ML to join the QuestaSim (Simulation) R&D team at Siemens EDA. In this role, you will design and develop AI-powered agents using LLMs, LangChain, vector databases, and retrieval-augmented generation (RAG). You will build intelligent systems that understand natural language queries and automate complex workflows. Additionally, you will integrate and experiment with ML pipelines, data-driven decision-making, and reinforcement learning for adaptive systems. You will also prototype and productize tools that leverage code understanding, profiling, and data analysis. Collaboration with AI researchers, UX designers, and backend teams to translate ideas into working products and robust features is a key aspect of this role. Furthermore, you will work on prompt engineering, few-shot learning, and tool use orchestration. Key Responsibilities: - Design and develop AI-powered agents using LLMs, LangChain, vector databases, and retrieval-augmented generation (RAG). - Build intelligent systems that understand natural language queries and automate complex workflows. - Integrate and experiment with ML pipelines, data-driven decision-making, and reinforcement learning for adaptive systems. - Prototype and productize tools that leverage code understanding, profiling, and data analysis. - Collaborate closely with AI researchers, UX designers, and backend teams to translate ideas into working products and robust features. - Work on prompt engineering, few-shot learning, and tool use orchestration. Must-Have: - Hands-on experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). - 4-8 years of proven experience. - Strong working knowledge of LangChain, RAG pipelines, and vector stores. - Strong understanding and experience in application of Deep Learning models like ANNs and transformers. - Experience in developing AI agents or copilots that interface with tools or external APIs. - Proficiency in Python; familiarity with software design patterns and clean code. - Practical experience in data preprocessing, feature engineering, and model evaluation. - Familiarity with LLMs (OpenAI, LLaMA, Claude, etc.) and prompt engineering best practices. - Ability to identify AI use-cases, conceptualize solutions, and drive from prototype to production. - Strong proficiency in programming languages like C/C++ and Python, along with strong foundations in algorithms and data structures. Good to Have: - Background or interest in Digital Design, SystemVerilog, or EDA tools (can be learned on the job). - Basic knowledge of compilers, parallelism, or profiling tools is a bonus. Why Join Us - Work on cutting-edge AI R&D projects with real product impact! - Be part of a startup-like team within a global tech company. - Opportunity to lead innovation, publish internally, and drive industry-first solutions. - Competitive compensation, flexibility, and a collaborative culture. We are Siemens - A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we encourage applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow! Transform the everyday,

At PwC, the focus in data and analytics is on leveraging data to drive insights and make informed business decisions. Advanced analytics techniques are utilized to help clients optimize operations and achieve strategic goals. As a Data Analyst at PwC, the emphasis is on utilizing advanced analytical techniques to extract insights from large datasets and facilitate data-driven decision-making. Skills in data manipulation, visualization, and statistical modeling are leveraged to assist clients in solving complex business problems. Candidates with 4+ years of hands-on experience are preferred for the role of GenAI Data Scientist at PwC US - Acceleration Center. The Senior Associate level position requires a highly skilled individual with a strong background in data science, particularly focusing on GenAI technologies. The ideal candidate should possess a solid understanding of statistical analysis, machine learning, data visualization, and application programming. Responsibilities include collaborating with product, engineering, and domain experts to identify high-impact GenAI opportunities, designing and building GenAI and Agentic AI solutions end-to-end, processing structured and unstructured data for LLM workflows, validating and evaluating models, containerizing and deploying production workloads, communicating findings and insights, and staying current with GenAI advancements. Requirements for this position include a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field, 1-2 years of hands-on experience delivering GenAI solutions, proficiency in Python with additional experience in R or Scala, experience with vector stores and search technologies, expertise in data preprocessing, feature engineering, and statistical experimentation, competence with cloud services across Azure, AWS, or Google Cloud, proficiency in data visualization, and strong problem-solving skills. Nice to have skills include relevant certifications in GenAI tools and technologies, hands-on experience with leading agent orchestration platforms, proven experience in chatbot design and development, practical knowledge of ML/DL frameworks, and proficiency in object-oriented programming with languages such as Java, C++, or C#. Candidates with a background in BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA or any related degree are encouraged to apply for this challenging role at PwC US - Acceleration Center.,

DecisionX is pioneering a new category with the world's first Decision AI, an AI Super-Agent that assists high-growth teams in making smarter, faster decisions by transforming fragmented data into clear next steps. Whether it involves strategic decisions in the boardroom or operational decisions across various departments like Sales, Marketing, Product, and Engineering, down to the minutiae that drives daily operations, Decision AI serves as your invisible co-pilot, thinking alongside you, acting ahead of you, and evolving beyond you. We are seeking a dedicated and hands-on AI Engineer to join our Founding team. In this role, you will collaborate closely with leading AI experts to develop the intelligence layer of our exclusive "Agentic Number System." Key Responsibilities - Building, fine-tuning, and deploying AI/ML models for tasks such as segmentation, scoring, recommendation, and orchestration. - Developing and optimizing agent workflows using LLMs (OpenAI, Claude, Mistral, etc.) for contextual reasoning and task execution. - Creating vector-based memory systems utilizing tools like FAISS, Chroma, or Weaviate. - Working with APIs and connectors to incorporate third-party data sources (e.g., Salesforce, HubSpot, GSuite, Snowflake). - Designing pipelines that transform structured and unstructured signals into actionable insights. - Collaborating with GTM and product teams to define practical AI agent use cases. - Staying informed about the latest developments in LLMs, retrieval-augmented generation (RAG), and agent orchestration frameworks (e.g., CrewAI, AutoGen, LangGraph). Must Have Skills - 5-8 years of experience in AI/ML engineering or applied data science. - Proficient programming skills in Python, with expertise in LangChain, Pandas, NumPy, and Scikit-learn. - Experience with LLMs (OpenAI, Anthropic, etc.), prompt engineering, and RAG pipelines. - Familiarity with vector stores, embeddings, and semantic search. - Expertise in data wrangling, feature engineering, and model deployment. - Knowledge of MLOps tools such as MLflow, Weights & Biases, or equivalent. What you will get - Opportunity to shape the AI architecture of a high-ambition startup. - Close collaboration with a visionary founder and experienced product team. - Ownership, autonomy, and the thrill of building something from 0 to 1. - Early team equity and a fast growth trajectory.,

As a GenAI Data Scientist at PwC US - Acceleration Center, you will be responsible for developing and implementing machine learning models and algorithms for GenAI projects. Your role will involve collaborating with product, engineering, and domain experts to identify high-impact opportunities, designing and building GenAI and Agentic AI solutions, processing structured and unstructured data for LLM workflows, validating and evaluating models, containerizing and deploying production workloads, communicating findings via various mediums, and staying updated with GenAI advancements. You should possess a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field, along with 1-2 years of hands-on experience delivering GenAI solutions and 3-5 years of deploying machine learning solutions in production environments. Proficiency in Python, experience with vector stores and search technologies, familiarity with LLM-backed agent frameworks, expertise in data preprocessing and feature engineering, competence with cloud services, solid grasp of Git workflows and CI/CD pipelines, and proficiency in data visualization are essential requirements. Additionally, having relevant certifications in GenAI tools, hands-on experience with leading agent orchestration platforms, expertise in chatbot design, practical knowledge of ML/DL frameworks, and proficiency in object-oriented programming with languages like Java, C++, or C# are considered as nice-to-have skills. The ideal candidate should possess strong problem-solving skills, a collaborative mindset, and the ability to thrive in a fast-paced environment. If you are passionate about leveraging data to drive insights and make informed business decisions, this role offers an exciting opportunity to contribute to cutting-edge GenAI projects and drive innovation in the field of data science.,

Role & responsibilities Experimenting with new Generative AI models Developing proof of concepts and pilots for various Generative AI and Agentic AI use cases Collaborating with Solution Architects and Enterprise Architects Evangelizing Generative AI and AI adoption within the bank Creating and presenting demos to promote reference architectures Experience: 5+ years of relevant experience Skills: 1. Programming Languages: a. Python 2. Machine Learning Frameworks: a. PyTorch b. TensorFlow 3. Experience with Generative AI Models: a. GANs (Generative Adversarial Networks) b. VAEs (Variational Autoencoders) c. Transformers 4. Cloud Platforms: a. AWS (Amazon Web Services) b. GCP (Google Cloud Platform) c. Azure 5. Data Handling: a. Feature stores b. Vector stores c. Retrieval-Augmented Generation (RAG) d. Data visualization 6. Big Data Technologies: a. Spark 7. Workflow Orchestration: a. Airflow

Atologist Infotech is seeking an experienced and forward-thinking AI Engineer to contribute to the shaping and scaling of the AI Agent Framework. In this hands-on engineering position, your primary focus will be on the development of intelligent and modular agent systems capable of reasoning, planning, and autonomously interacting in real-world scenarios. Working closely with a collaborative team, you will be responsible for designing and implementing agent-oriented systems that facilitate task decomposition, memory management, and contextual planning. Additionally, you will play a key role in extending the in-house AI Agent Framework by incorporating reusable components such as tools, memory modules, and orchestration logic. Your duties will also involve building and integrating vector search, semantic retrieval, and memory systems to empower long-term, goal-oriented behavior in agents. You will be tasked with connecting LLMs (e.g., OpenAI, Anthropic) and NLU/NLP layers to enable natural task inputs and autonomous reasoning capabilities. Furthermore, you will develop RESTful APIs using FastAPI, Flask, or Django to expose agent functionalities and facilitate integration with other products. As an AI Engineer at Atologist Infotech, you will be expected to design scalable, event-driven microservice architectures customized for AI-native workloads and agent frameworks. Emphasizing responsible AI design, you will prioritize user safety, transparency, and privacy throughout the development process. **Key Responsibilities:** - AI Agent System Development: Design and implement agent-oriented systems supporting task decomposition, memory handling, and contextual planning. - Framework Engineering: Extend the in-house AI Agent Framework with reusable components like tools, memory modules, and orchestration logic. - Contextual Intelligence: Build and integrate vector search, semantic retrieval, and memory systems to enable long-term, goal-driven agent behavior. - Natural Language Interfaces: Connect LLMs and NLU/NLP layers for natural task inputs and autonomous reasoning capabilities. - API Engineering: Develop RESTful APIs using FastAPI, Flask, or Django to expose agent capabilities and integrate with other products. - System Architecture: Design scalable, event-driven microservice architectures tailored for AI-native workloads and agent frameworks. - Ethical AI: Prioritize responsible AI design with user safety, transparency, and privacy at the core. **Required Skills & Qualifications:** - Education: Bachelors or Masters degree in Computer Science, Artificial Intelligence, or a related field. - Python Proficiency: Strong software engineering skills in Python (3.x) with expertise in async programming, architecture design, and typing. - AI/LLM Experience: Practical experience using LLMs for reasoning, prompt engineering, chaining, or building agent-like applications. - Frameworks & Tools: FastAPI, Flask, or Django; LangChain, LlamaIndex, or other agent frameworks; Vector stores (FAISS, Weaviate, Pinecone); PostgreSQL, Redis, and event queues (Celery, RabbitMQ). - Version Control & Testing: Proficient with Git workflows and writing tests using Pytest or similar. **Bonus Skills (Nice-to-Have):** - Experience with autonomous agents, tool-calling, or memory-driven task systems. - Familiarity with cognitive architectures or symbolic reasoning. - Contributions to open-source AI frameworks or tooling. This is a full-time, permanent position offering benefits such as leave encashment, paid sick time, paid time off, and Provident Fund. The work schedule is fixed from Monday to Friday. Experience: AI - 3 years (Preferred) Work Location: In person,

As a part of our team at Raven, a YC-backed startup specializing in building AI assistants for manufacturing plants, you will play a crucial role in leveraging decades of manufacturing expertise to tackle real operational challenges through AI solutions. Based in Bangalore, our small yet dedicated team is committed to enhancing industrial operations to be safer, smarter, and more efficient. In this core technical position, your primary focus will be on developing AI-native applications and agents tailored for manufacturing workflows. Specifically, you will be responsible for: - Building Python/Go backend services that seamlessly integrate with AI systems. - Enhancing multi-modal pipeline infrastructure to manage P&IDs, SOPs, sensor data, and technical documents effectively. - Constructing agent memory systems utilizing knowledge graphs and event timelines. - Designing AI orchestration layers to facilitate decision-making workflows based on structured/unstructured plant data. - Conducting rapid prototyping of new AI workflows and deploying them in real-world plant settings. We are seeking individuals with at least 2-4 years of experience in building production systems, possessing strong Python/Go skills, familiarity with LLMs, embeddings, and vector stores. The ideal candidate should have a proactive approach to problem-solving, a keen interest in taking ownership of end-to-end solutions, and the ability to thrive in dynamic environments by iterating quickly and delivering tangible value. Moreover, a background in working at startups and the ability to adapt to various roles will be considered a bonus. By joining our team, you will have the opportunity to contribute to the development of core systems that empower plant teams to make informed decisions swiftly and safely. We offer a chance to shape the product, culture, and direction of the company as one of the initial hires, with a stake in the company through equity. You will be part of a collaborative environment that encourages fast iteration and in-person collaboration, focusing on addressing meaningful problems that have a direct impact on safety and efficiency in real-world scenarios.,

The company Raven, a YC-backed startup (S22), is dedicated to developing AI assistants for manufacturing plants by leveraging decades of manufacturing expertise combined with AI technology to address operational challenges. With strong support from top VCs, the team in Bangalore focuses on enhancing industrial operations to promote safety, intelligence, and efficiency within challenging work environments. As a part of the team, your key responsibilities will revolve around the core technical aspect of constructing AI-native applications and agents tailored for manufacturing workflows. Your tasks will include: - Building Python/Go backend services that seamlessly integrate with AI systems. - Enhancing multi-modal pipeline infrastructure to manage P&IDs, SOPs, sensor data, and technical documents effectively. - Developing agent memory systems utilizing knowledge graphs and event timelines. - Designing AI orchestration layers to facilitate decision-making workflows based on structured/unstructured plant data. - Rapid prototyping of new AI workflows and deploying them in real-world plant settings. The ideal candidate for this role should possess: - 2+ years of experience in constructing production systems. - Proficiency in Python/Go programming, with familiarity in LLMs, embeddings, and vector storage. - A keen interest in problem-solving and a proactive approach towards finding solutions. - A deep commitment to problem ownership throughout the entire process, from exploring potential solutions to implementing functional systems in production. - Comfort in handling ambiguity, adapting quickly, and delivering tangible value. A bonus would be past experience working in a startup environment and a willingness to take on various responsibilities. Joining Raven means being part of a team dedicated to developing fundamental systems that empower plant teams to make quicker and safer decisions. The role offers: - Impact: As one of the initial hires, you will play a pivotal role in shaping the product, culture, and trajectory of the company. - Ownership: You will be granted 0.1-1% equity, emphasizing the importance of feeling a sense of ownership in the company. - Focus: An opportunity to tackle significant, complex problems that directly influence real-world outcomes related to safety and efficiency. The company values the collaboration and fast iteration that come with working together in person, particularly at this stage of growth. The emphasis on teamwork and proximity aims to enhance collaboration and accelerate progress towards shared goals.,

Key Responsibilities: Work with stakeholders to understand requirements and deliver AI solutions across several domains in Wealth Management. Stay updated with the latest advancements in AI and machine learning technologies. Conduct research and experiments to improve AI capabilities within the division. Required Competencies: Retrieval-Augmented Generation (RAG): Experience in developing and implementing RAG models to enhance information retrieval and generation tasks. Vector Stores: Knowledge of Vector Stores for efficient data storage and retrieval. Prompt Engineering: Skills in designing and optimizing prompts for AI models to improve accuracy and relevance. Large Language Model APIs (LLM APIs): Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Claude). Programming Languages: Proficiency in Python, Java, or other relevant programming languages. Data Analysis: Strong analytical skills and experience with data analysis tools. Problem-Solving: Excellent problem-solving abilities and attention to detail. Communication: Strong verbal and written communication skills. Preferred Competencies: Graph RAG: Proficiency in using Graph RAG for complex data relationships and insights. Knowledge Graphs: Expertise in building and managing Knowledge Graphs to represent and query complex data structures. Machine Learning Frameworks: Experience with TensorFlow, PyTorch, or similar frameworks. Experience with cloud platforms such as AWS, Google Cloud, or Azure. Familiarity with natural language processing (NLP) and computer vision technologies. Previous experience in a similar role or industry. Master s or Ph.D. in Computer Science, Data Science, or a related field. Years of experience: 3-5