16 Embedding Models Jobs

The AI Engineer is an ML engineer who is responsible for building and optimizing machine learning models, retrieval-augmented generation (RAG) systems, and verifiable ML systems that transform how we search and analyze complex medical and insurance data. This role requires a deep understanding of machine learning, LLM technologies, data science, and software engineering. This is an ML-engineering role and not a data science role , which means you should be comfortable building production-ready systems. This is not a research role. This is a Hybrid role in the HYD office, 3 days a week. Job Responsibilities: Data engineering: Design and optimize systems capable of processing large volumes of data in both batch and real-time. Design, implement, and optimize retrieval-augmented generation (RAG) systems that leverage the latest LLM technologies to deliver highly relevant search results at scale. Develop and refine embedding models, vector databases, and retrieval mechanisms that maximize search relevance while minimizing latency and operational costs. Create robust evaluation frameworks to measure quality, continuously improve our LLM-based solution based on user feedback and performance metrics. Build and optimize machine learning models and verifiable ML systems that transform how we search and analyze complex medical and insurance data. Build and optimize production-ready systems that are scalable and can handle large amounts of data. Build and optimize agentic systems that can reason and make decisions. Develop machine learning models in healthcare and insurance settings with the highest standards for safety and quality. Stay on top of AI and ML security and governance requirements. Basic Requirements: BS in Computer Science (concentration on machine learning/AI), Engineering, Statistics, or a related field At least three (3) years of industry experience and specifically with some of the recent Gen AI technologies. Experience with containerization, Kubernetes, and cloud-native ML technologies such as Kubeflow. Experience with CI/CD pipelines and automated testing. High level of proficiency with Python and several ML frameworks. Preferred Requirements: Experience with medical coding and clinical policy analysis. Exposure to USA healthcare insurance will be an advantage. Strong understanding of clinical coding standards (e.g., ICD-10, CPT, HCPCS) is an advantage. Show more Show less

Job Requisition ID # 25WD90121 Position Overview Are you a problem solver who thrives on building real-world AI applications Do you geek out over LLMs, RAG, MCP and agentic architectures Want to help shape a brand-new team and build cool stuff that actually ships If so, read on. Were building a new Applied AI team within Autodesks Data and Process Management (DPM) group. As a Founding Principal Engineer, youll be at the heart of this initiative working in a highly dynamic environment, designing, building, and scaling AI-powered experiences across our diverse portfolio providing critical Product Lifecycle Management (PLM) and Product Data Management (PDM) capabilities to our customers. Youll work on real production systems, solve hard problems, and help define the future of AI at Autodesk. Responsibilities Build AI-powered Experiences: Architect and develop production-grade AI applications that are scalable, resilient & secure Shape AI Strategy: Help define the AI roadmap for DPM by identifying opportunities, evaluating emerging technologies, and guiding long-term direction Operationalize LLMs: Fine-tune, evaluate, and deploy large language models in production environments. Balance performance, cost, and user experience while working with real-world data and constraints Build for Builders: Design frameworks and tools that make it easier for other teams to develop AI-powered experiences Guide Engineering Practices: Collaborate with other engineering teams to define and evolve best practices for AI experimentation, evaluation, and optimization. Provide technical guidance and influence decisions across teams Drive Innovation: Stay on top of the latest in AI technologies (e.g. LLMs, VLMs, Foundation Models), Architecture Patterns such as fine-tuning, RAG, function calling, MCP and moreand bring these innovations to production effectively Optimize for Scale: Ensure AI applications are resilient, performant, and can scale well in production Collaborate Across Functions: Partner with product managers, architects, engineers, and data scientists to bring AI features to life in Autodesk products Minimum Qualifications Masters in computer science, AI, Machine Learning, Data Science, or a related field 10+ years building scalable cloud-native applications, with 3+ years focused on production AI/ML systems Deep understanding of LLMs, VLMs, and foundation models, including their architecture, limitations, and practical applications Experience fine-tuning LLMs using real-world datasets and integrating them into production systems Experience with LLM related technologies including frameworks, embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems, MCP, in production settings Deep understanding of data modeling, system architectures, and processing techniques Experience with AWS cloud services and SageMaker Studio (or similar) for scalable data processing and model development Proven track record of building and deploying scalable cloud-native AI applications using platforms like AWS, Azure, or Google Cloud. Proficiency in Python or TypeScript You love tackling complex challenges and delivering elegant, scalable solutions You can explain technical concepts clearly to both technical and non- technical audiences Preferred Qualifications Experience building AI applications in the CAD or manufacturing domain. Experience designing evaluation pipelines for LLM-based systems (e.g., prompt testing, hallucination detection, safety filters) Familiarity with tools and frameworks for LLM fine-tuning and orchestration (e.g., LoRA, QLoRA, AoT P-Tuning etc.) A passion for mentoring and growing engineering talent Experience with emerging Agentic AI solutions such as LangGraph, CrewAI, A2A, Opik Comet, or equivalents Contributions to open-source AI projects or publications in the field Bonus points if youve ever explained RAG to a non-technical friendand they got it Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk its at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world. When youre an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future Join us! Salary transparency Salary is one part of Autodesks competitive compensation package. Offers are based on the candidates experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package. Diversity & Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging Are you an existing contractor or consultant with Autodesk Please search for open jobs and apply internally (not on this external site). Show more Show less

Details: Job Description Stefanini Group is a multinational company with a global presence in 41 countries and 44 languages, specializing in technological solutions. We believe in digital innovation and agility to transform businesses for a better future. Our diverse portfolio includes consulting, marketing, mobility, AI services, service desk, field service, and outsourcing solutions. Experience in Deep learning engineering (mostly on MLOps) Strong NLP/LLM experience and processing text using LLM Proficient in Pyspark/Databricks & Python programming. Building backend applications (data processing etc) using Python and Deep learning frame works. Deploying models and building APIS (FAST API, FLASK API) Need to have experience working with GPU&aposS. Working knowledge of Vector databases like 1) Milvus 2) azure cognitive search 3) quadrant etc Experience in transformers and working with hugging face models like llama, Mixtral AI and embedding models etc. Job Requirements Details: Good to have: Knowledge and experience in Kubernetes, docker etc. Cloud Experience working with VM&aposS and azure storage. Sound data engineering experience. Show more Show less

Yahoo Finance is the world's leading finance destination, providing investors with news, information, and tools to make confident financial decisions. Trusted by over 150 million visitors globally each month, representing over $20 trillion dollars in investable assets, Yahoo Finance delivers high-quality real-time market data across desktop, mobile, and streaming platforms. With breaking news from thousands of sources, original editorial perspectives, objective analyst ratings and research, analytical charts and technical tools, personalized mobile alerts, and more, Yahoo Finance equips investors with knowledge and insights to achieve financial freedom and greater prosperity. Yahoo is a top provider of media and technology brands, reaching over a billion people worldwide. Yahoos Media Engineering organization utilizes the latest technologies to build brands that members love, including Yahoo, AOL, Engadget, TechCrunch, Autoblog, In The Know, and more. With a focus on building at a massive scale to reach hundreds of millions of users, our teams strive to create world-class user experiences, delivering trusted content and data across all brands. We are committed to building and revitalizing this essential, trusted resource for investors and savers under a new leadership team. As an experienced engineer, you will collaborate closely with Engineering, Product, and Design teams to enhance our product offerings. You will develop applications and tools essential for supporting our business operations and ensuring the quality of our data and services. This role involves architecting, designing, scoping, building, maintaining, and iterating on systems needed to deliver world-class finance products and features. Responsibilities: - Be part of an agile scrum team, demonstrating progress through proof of concept, sandboxing, and prototyping - Architect and design scalable, maintainable, secure, and reusable strategic solutions - Deploy, monitor, and manage ML models in production environments using MLOps best practices - Work closely with data scientists to transition models from development to production efficiently - Optimize ML models and infrastructure for efficiency, scalability, and cost-effectiveness - Design and implement frameworks and tools to empower developers and non-technical colleagues - Lead key team initiatives by managing and improving the software development life cycle - Seek opportunities to improve quality and efficiency in day-to-day workflow processes - Present and communicate progress across multiple groups, sharing knowledge and best practices - Perform code reviews for peers and recommend approaches to solving complex problems - Own, deploy, monitor, and operate large-scale production systems - Lead and mentor junior engineers in building production-grade systems and applications - Act as a technical liaison to translate business needs into technical solutions Requirements (must have): - MS or PhD in Computer Science or related major - 5 to 10 years industry experience as a Back End Engineer, ML Engineer, or Research Engineer - Deep functional knowledge and hands-on experience with AWS or GCP cloud services, RESTful Web Services, Containerization (Docker, ECS, Kubernetes), and modern AI tools - Experience with AI/ML Ops tools and platforms, basic Data Science concepts, and version control tools - Capable of implementing resilient web architecture and building web products end to end - Familiarity with financial datasets and experience with time series analysis - Ability to work in a hybrid model, commuting 3 days a week to an office in Bangalore Important notes: - All applicants must apply for Yahoo openings directly with Yahoo - Offer letters and documents will be issued through the system for e-signatures - Yahoo offers flexibility around employee location and hybrid working For further inquiries about the role, please discuss with the recruiter.,

As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. This role will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions. Your responsibilities will include establishing and promoting a library of common ML assets, including reusable ML models, features stores, data pipelines, and standardized templates. You will lead efforts to create shared tools and platforms that streamline the end-to-end ML lifecycle across the organization. Additionally, you will create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques, and gain experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines. You will advise on the strategy and development of multiple products, applications, and technologies, serving as a lead advisor on the technical feasibility and business need for AIML use cases. Furthermore, you will liaise with firm-wide AI ML stakeholders, translating highly complex technical issues, trends, and approaches to leadership to drive the firm's innovation and enable leaders to make strategic, well-informed decisions about technology advancements. You will also influence across business, product, and technology teams and successfully manage senior stakeholder relationships, championing the firm's culture of diversity, opportunity, inclusion, and respect. To be successful in this role, you must have formal training or certification on Machine Learning concepts and at least 10 years of applied experience, along with 5+ years of experience leading technologists to manage, anticipate, and solve complex technical items within your domain of expertise. An MS and/or PhD in Computer Science, Machine Learning, or a related field is required, as well as at least 10 years of experience in one of the programming languages like Python, Java, C/C++, etc., with intermediate Python skills being a must. You should have a solid understanding of using ML techniques, especially in Natural Language Processing (NLP) and Large Language Models (LLMs), hands-on experience with machine learning and deep learning methods, and the ability to work on system design from ideation through completion with limited supervision. Practical cloud-native experience such as AWS is necessary, along with good communication skills, a passion for detail and follow-through, and the ability to work effectively with engineers, product managers, and other ML practitioners. Preferred qualifications for this role include experience with Ray, MLFlow, and/or other distributed training frameworks, in-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies, advanced knowledge in Reinforcement Learning or Meta Learning, and a deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc., is also desirable.,

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.,

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

As a Software Engineer at Infoware, you will be responsible for developing and fine-tuning a Retrieval-Augmented Generation (RAG) pipeline to personalize responses based on a user's history, preferences, and interactions. Your role will involve designing a scalable system for capturing, storing, indexing, and retrieving user-specific knowledge. You will integrate AI-based systems by combining algorithms and automation, engineer prompts, and optimize context windows for better LLM retrieval. Additionally, you will apply vector databases and embedding models to user-specific data and create adaptive systems that learn and evolve over time. In this role, you will be expected to work independently, propose solutions, and iterate quickly. The ability to learn and adapt to various enterprise systems is crucial for success in this position. The probation period for this role is 3 months, and the salary during this period will be decided with the candidate. Infoware is a process-driven software solutions provider that specializes in bespoke software solutions. We collaborate with enterprises and startups, offering them end-to-end solutions. To learn more about our company, please visit our website at https://www.infowareindia.com/,

As a visionary technical co-founder, you will combine engineering excellence with philosophical depth to embark on the journey of building something rare, intelligent, and deeply rooted. You will be driven by first-principle problem solving and AI that reasons instead of merely responding. Your role will involve leading the technical architecture of a foundational AI product while embodying the qualities of humility to listen and the conviction to build. Your core responsibilities will revolve around spearheading the design, development, and iteration of VIKAS AI's reasoning engine. This will include building and fine-tuning LLMs, integrating RAG pipelines, and designing multi-agent systems. You will architect systems that strike a balance between cultural depth, emotional nuance, and technical performance. Collaborating closely with the team, you will shape core product features such as culturally intelligent LLMs, an aesthetically curated image engine, and a short-form AI news video layer. Additionally, you will co-create the technical roadmap, hire the early team, and oversee the infrastructure. To excel in this role, strong experience in machine learning, NLP, and LLMs is essential. You should be proficient with Transformers, LangChain, HuggingFace, or similar frameworks and possess solid knowledge of Python, vector databases, and inference infrastructure. Experience with RAG (Retrieval-Augmented Generation) and agent-based architectures, as well as familiarity with embedding models, fine-tuning, and prompt engineering, will set you up for success. An added advantage would be an interest in Indic language modeling or symbolic reasoning, experience in building low-latency, high-context systems, and an eye for clean code, ethics, and culture. Beyond your technical skills, your philosophical outlook and values will play a crucial role in defining who you are as a builder-philosopher. Your commitment to cultural intelligence, ethical AI, and context-aware systems will be evident as you strive to bridge the gap in current AI capabilities. You will prioritize truth over hype, depth over speed, and alignment over noise, reflecting a holistic approach to your work. In return for your contributions, you will receive co-founder status with meaningful equity, the opportunity to be at the forefront of building a product with global potential and local essence, complete creative and architectural freedom to innovate from the ground up, and the guidance of a visionary founder who is relentless, clear, and deeply committed. This role offers you the chance to not just follow existing trends but to redefine the narrative by putting India on the map through innovative thinking and impactful solutions. If you are intrigued by this opportunity and resonate with the vision outlined, feel free to reach out by DM or email at vikasai150807@gmail.com. Let's engage in conversations that transcend mere features and delve into shaping promising futures.,

We are looking for a highly motivated Mid-Level AI Engineer to join our growing AI team. Your main responsibility will be to develop intelligent applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. Working closely with data scientists, backend engineers, and product teams, you will build and deploy AI-powered solutions that provide real-world value. Your key responsibilities will include designing, developing, and optimizing applications utilizing LLMs such as GPT, LLaMA, and Claude. You will also be tasked with implementing RAG pipelines to improve LLM performance using domain-specific knowledge bases and search tools. Developing and maintaining robust Python codebases for AI-driven solutions will be a crucial part of your role. Additionally, integrating vector databases like Pinecone, Weaviate, and FAISS, as well as embedding models for information retrieval, will be part of your daily tasks. You will work with APIs, frameworks like LangChain and Haystack, and various tools to create scalable AI workflows. Collaboration with product and design teams to define AI use cases and deliver impactful features will also be a significant aspect of your job. Conducting experiments to assess model performance, retrieval relevance, and system latency will be essential for continuous improvement. Staying up-to-date with the latest research and advancements in LLMs, RAG, and AI infrastructure is crucial for this role. To be successful in this position, you should have at least 3-5 years of experience in software engineering or AI/ML engineering, with a strong proficiency in Python. Experience working with LLMs such as OpenAI and Hugging Face Transformers is required, along with hands-on experience in RAG architecture and vector-based retrieval techniques. Familiarity with embedding models like SentenceTransformers and OpenAI embeddings is also necessary. Knowledge of API design, deployment, performance optimization, version control (e.g., Git), containerization (e.g., Docker), and cloud platforms (e.g., AWS, GCP, Azure) is expected. Preferred qualifications include experience with LangChain, Haystack, or similar LLM orchestration frameworks. Understanding NLP evaluation metrics, prompt engineering best practices, knowledge graphs, semantic search, and document parsing pipelines will be beneficial. Experience deploying models in production, monitoring system performance, and contributing to open-source AI/ML projects are considered advantageous for this role.,

As a Mid-Level AI Engineer at our company, you will be an integral part of our AI team, focusing on the development of intelligent applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. Your collaboration with data scientists, backend engineers, and product teams will be pivotal in building and deploying AI-powered solutions that bring real-world value. Your responsibilities will include designing, developing, and optimizing applications by leveraging LLMs such as GPT, LLaMA, and Claude. You will also be responsible for implementing RAG pipelines to enhance LLM performance through domain-specific knowledge bases and search tools. Developing and maintaining robust Python codebases for AI-driven solutions, integrating vector databases like Pinecone, Weaviate, FAISS, and embedding models for information retrieval will be a key part of your role. Additionally, you will work with APIs, frameworks like LangChain, Haystack, and tools to build scalable AI workflows. Collaborating with product and design teams to define AI use cases and deliver impactful features, conducting experiments to evaluate model performance, retrieval relevance, and system latency, as well as staying updated on research and advancements in LLMs, RAG, and AI infrastructure are also important aspects of your responsibilities. To be successful in this role, you should have at least 3-5 years of experience in software engineering or AI/ML engineering, with a strong proficiency in Python. Experience working with LLMs from OpenAI, Hugging Face Transformers, etc., hands-on experience with RAG architecture, vector-based retrieval techniques, embedding models like SentenceTransformers, OpenAI embeddings, and vector databases such as Pinecone, FAISS is required. Knowledge of API design, deployment, performance optimization, version control using Git, containerization with Docker, and cloud platforms like AWS, GCP, Azure is essential. Preferred qualifications include experience with LangChain, Haystack, or similar LLM orchestration frameworks, understanding of NLP evaluation metrics, prompt engineering best practices, exposure to knowledge graphs, semantic search, document parsing pipelines, experience in deploying models in production, monitoring system performance, and contributions to open-source AI/ML projects are a plus.,

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

Job Title: GenAI Developer Location: Noida Experience: 5-7 years (minimum 2 years in Generative AI/LLM-based projects) Job Summary: We are looking for a hands-on and seasoned Generative AI Developer with proven expertise in building and deploying applications powered by Large Language Models (LLMs), especially open-source models, and handling unstructured data. This role combines strong technical acumen with leadership capabilities to drive end-to-end GenAI initiatives from prototype to production. Key Responsibilities : Lead design, development, and deployment of GenAI applications utilizing opensource LLMs (e.g., LLaMA, Mistral, Falcon, etc.). Build robust pipelines to extract, clean, and preprocess unstructured data (text, PDFs, images, etc.) for training and inference. Integrate LLMs with business workflows via APIs, vector databases (e.g., FAISS, Milvus, Pinecone), and prompt engineering. Fine-tune and optimize open-source LLMs for specific use-cases, including domain adaptation. • Mentor junior developers and guide project execution with Agile methodology. Evaluate and implement open-source tools, libraries, and frameworks to support scalable and cost-efficient GenAI solutions. Collaborate with cross-functional teams. Ensure security, compliance, and responsible AI practices during development and deployment. Required Skills & Qualifications : Bachelors or Masters degree in Computer Science, AI/ML, or related field. Strong hands-on experience with open-source LLMs (e.g., HuggingFace Transformers, LangChain, Llama.cpp). Proven experience in prompt engineering, RAG (Retrieval-Augmented Generation), and model fine-tuning. Proficient in handling unstructured data using tools like SpaCy, NLTK, OCR (Tesseract), or NLP libraries. Deep knowledge of Python and frameworks like PyTorch or TensorFlow. Experience with vector databases, embedding models, and knowledge graphs. Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes). Excellent problem-solving skills. Good To Have : • Exposure to multimodal GenAI (text + image). Knowledge of data governance and AI ethics. Contributions to open-source GenAI projects or publications. Interested Candidates who have matching skill set and experience, can directly drop their resumes on 'Sonakshi.gupta@aptaracorp.com' .

About this role: Lead Software Engineer (AI) position having experience in classic and generative AI techniques, and responsible for design, implementation, and support of Python based applications to help fulfill our Research & Consulting Delivery strategy. What youll do: Deliver client engagements that use AI rapidly, on the order of a few weeks Stay on top of current tools, techniques, and frameworks to be able to use and advise clients on them Build proofs of concept rapidly, to learn and adapt to changing market needs Support building internal applications for use by associates to improve productivity What you’ll need: 6-8 years of experience in classic AI techniques and at least 1.5 years in generative AI techniques. Demonstrated ability to run short development cycles and solid grasp of building software in a collaborative team setting. Must have: Experience building applications for knowledge search and summarization, frameworks to evaluate and compare performance of different GenAI techniques, measuring and improving accuracy and helpfulness of generative responses, implementing observability. Experience with agentic AI frameworks, RAG, embedding models, vector DBs Experience working with Python libraries like Pandas, Scikit-Learn, Numpy, and Scipy is required. Experience deploying applications to cloud platforms such as Azure and AWS. Solid grasp of building software in a collaborative team setting - use of agile scrum and tools like Jira / GitHub. Nice to have: Experience in finetuning Language models. Familiarity with AWS Bedrock / Azure AI / Databricks Services. Experience in Machine learning models and techniques like NLP, BERT, Transformers, Deep learning. Experience in MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., Experience building scalable data models and performing complex relational databases queries using SQL (Oracle, MySQL, PostgreSQL). Who you are: Excellent written, verbal, and interpersonal communication skills with the ability to present technical information in a clear and concise manner to IT Leaders and business stakeholders. Effective time management skills and ability to meet deadlines. Excellent communications skills interacting with technical and business audiences. Excellent organization, multitasking, and prioritization skills. Must possess a willingness and aptitude to embrace new technologies/ideas and master concepts rapidly. Intellectual curiosity, passion for technology and keeping up with new trends. Delivering project work on-time within budget with high quality. Demonstrated ability to run short development cycle.

About the Team and Our Scope We are a forward-thinking tech organization within Swiss Re, delivering transformative AI/ML solutions that redefine how businesses operate. Our mission is to build intelligent, secure, and scalable systems that deliver real-time insights, automation, and high-impact user experiences to clients globally. You'll join a high-velocity AI/ML team working closely with product managers, architects, and engineers to create next-gen enterprise-grade solutions. Our team is built on a startup mindset - bias to action, fast iterations, and ruthless focus on value delivery. We're not only shaping the future of AI in business - we're shaping the future of talent. This role is ideal for someone passionate about advanced AI engineering today and curious about evolving into a product leadership role tomorrow. You'll get exposure to customer discovery, roadmap planning, and strategic decision-making alongside your technical contributions. Role Overview As an AI/ML Engineer, you will play a pivotal role in the research, development, and deployment of next-generation GenAI and machine learning solutions . Your scope will go beyond retrieval-augmented generation (RAG) to include areas such as prompt engineering, long-context LLM orchestration, multi-modal model integration (voice, text, image, PDF), and agent-based workflows. You will help assess trade-offs between RAG and context-native strategies, explore hybrid techniques, and build intelligent pipelines that blend structured and unstructured data. You'll work with technologies such as LLMs, vector databases, orchestration frameworks, prompt chaining libraries, and embedding models, embedding intelligence into complex, business-critical systems. This role sits at the intersection of rapid GenAI prototyping and rigorous enterprise deployment, giving you hands-on influence over both the technical stack and the emerging product direction. Key Responsibilities Build Next-Gen GenAI Pipelines : Design, implement, and optimize pipelines across RAG, prompt engineering, long-context input handling, and multi-modal processing. Prototype, Validate, Deploy : Rapidly test ideas through PoCs, validate performance against real-world business use cases, and industrialize successful patterns. Ingest, Enrich, Embed: Construct ingestion workflows including OCR, chunking, embeddings, and indexing into vector databases to unlock unstructured data. Integrate Seamlessly: Embed GenAI services into critical business workflows, balancing scalability, compliance, latency, and observability. Explore Hybrid Strategies: Combine RAG with context-native models, retrieval mechanisms, and agentic reasoning to build robust hybrid architectures. Drive Impact with Product Thinking : Collaborate with product managers and UX designers to shape user-centric solutions and understand business context. Ensure Enterprise-Grade Quality: Deliver solutions that are secure, compliant (e.g., GDPR), explainable, and resilient - especially in regulated environments. What Makes You a Fit Must-Have Technical Expertise Proven experience with GenAI techniques and LLMs , including RAG, long-context inference, prompt tuning, and multi-modal integration. Strong hands-on skills with Python , embedding models, and orchestration libraries (e.g., LangChain, Semantic Kernel, or equivalents). Comfort with MLOps practices , including version control, CI/CD pipelines, model monitoring, and reproducibility. Ability to operate independently, deliver iteratively, and challenge assumptions with data-driven insight. Understanding of vector search optimization and retrieval tuning. Exposure to multi-modal models Nice-To-Have Qualifications Experience building and operating AI systems in regulated industries (e.g., insurance, finance, healthcare). Familiarity with Azure AI ecosystem (e.g., Azure OpenAI, Azure AI Document Intelligence, Azure Cognitive Search) and deployment practices in cloud-native environments. Experience with agentic AI architectures , tools like AutoGen, or prompt chaining frameworks. Familiarity with data privacy and auditability principles in enterprise AI. Bonus: You Think Like a Product Manager While this role is technical at its core, we highly value candidates who are curious about how AI features become products . If you're excited by the idea of influencing roadmaps, shaping requirements, or owning end-to-end value delivery - we'll give you space to grow into it. This is a role where engineering and product are not silos . If you're keen to move in that direction, we'll mentor and support your evolution. Why Join Us You'll be part of a team that's pushing AI/ML into uncharted, high-value territory. We operate with urgency, autonomy, and deep collaboration. You'll prototype fast, deliver often, and see your work shape real-world outcomes - whether in underwriting, claims, or data orchestration. And if you're looking to transition from deep tech to product leadership , this role is a launchpad. Swiss Re is an equal opportunity employer . We celebrate diversity and are committed to creating an inclusive environment for all employees. Keywords: Reference Code: 134317

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.