103 Rag Pipelines Jobs

Role Overview: You will be the Tech Lead responsible for overseeing the architecture and technical solutioning for GenAI-powered use cases in the insurance industry. Your role will involve collaborating with business teams, designing end-to-end systems, ensuring technical delivery, and serving as the technical face to the client. Key Responsibilities: - Lead the architecture and technical solutioning for GenAI-powered use cases in the insurance industry. - Collaborate with business teams to ideate, assess, and create use cases demonstrating tangible value. - Design end-to-end systems integrating GenAI components, APIs, and cloud infrastructure. - Drive technical delivery to ensure scalability, performance, and alignment with client goals. - Work with engineers, product managers, and QA to deliver production-grade solutions. - Act as the technical point of contact for clients, supporting solution discussions and managing stakeholder expectations. - Evaluate and select appropriate GenAI tools and platforms such as OpenAI, LangChain, and RAG pipelines. - Uphold data privacy, compliance, and security standards in all solutions. Qualifications: - Minimum 10 years of experience in software development/architecture with a strong background in system design and enterprise delivery. - Proven track record in designing AI/ML or GenAI solutions, preferably using tools like OpenAI, Azure OpenAI, LangChain, etc. - Sound knowledge of cloud infrastructure (AWS/Azure/GCP) and integration best practices. - Experience in insurance workflows like underwriting, claims, policy administration, or financial operations. - Ability to create clear technical documentation, architecture diagrams, and engineering playbooks. - Hands-on development experience in Python, Node.js, or similar languages is a plus. - Strong stakeholder management and communication skills. Additional Company Details: The company is a global consulting, technology, and managed services firm supporting insurance organizations worldwide. Specializing in underwriting, claims, policy services, data, and digital transformation, they help insurers improve efficiency and drive growth through tailored solutions leveraging innovation and advanced technologies. Their client-centric approach ensures measurable business outcomes and long-term value creation.,

Role & responsibilities Role Overview: InnovaPoint is seeking a dynamic Senior AI Engineer to lead the development and deployment of cutting-edge AI solutions. This role is ideal for a self-driven technologist with deep expertise in AI/ML and a passion for building intelligent systems such as AI chatbots, agents, automation tools, and recommendation engines. You will be responsible for transforming business challenges into scalable AI solutions while also supporting strategic conversations about how AI can reshape services and operations. Responsibilities: Design, build, and deploy AI/ML models, AI chatbots, and custom AI agents Work with LLMs (OpenAI, Anthropic, Mistral) and frameworks like LangChain or LlamaIndex Develop prompt engineering and RAG-based solutions using vector databases Integrate AI capabilities into web applications, internal tools, and client platforms Optimize and monitor model performance in production environments Collaborate with frontend/backend developers and DevOps for AI solution delivery Research and experiment with the latest in GenAI, NLP, and multimodal AI systems Maintain AI best practices, documentation, and model version control Required Skills: Strong programming skills in Python and experience with AI/ML libraries (Transformers, PyTorch, TensorFlow) Hands-on experience with GenAI APIs (OpenAI, Claude, etc.) Solid grasp of LLMs, chatbot architectures, RAG pipelines, and embedding models Experience deploying models in cloud environments (AWS/GCP/Azure) Knowledge of vector stores, memory modules, and LLM app frameworks Bonus: familiarity with Streamlit, Gradio, or other rapid AI prototyping tools Qualifications: B.Tech/M.Tech/MCA in Computer Science, AI, Data Science, or related field 4+ years of software development experience, focused on AI/ML/GenAI For more information, please visit our website and social media pages. Website www.innovapoint.com Insta - InnovaPoint (@innovapoint) • Instagram LinkedIn - InnovaPoint Infotech Private Limited | LinkedIn

Primary Title: Senior LLM Engineer (4+ years) Hybrid, India About The Opportunity A technology consulting firm operating at the intersection of Enterprise AI, Generative AI and Cloud Engineering seeks an experienced LLM-focused engineer. You will build and productionize LLM-powered products and integrations for enterprise customers across knowledge management, search, automation, and conversational AI use-cases. This is a hybrid role based in India for candidates with strong hands-on LLM engineering experience. Role & Responsibilities Own design and implementation of end-to-end LLM solutions: data ingestion ? retrieval (RAG) ? fine-tuning ? inference and monitoring for production workloads. Develop robust Python microservices to serve LLM inference, retrieval, and agentic workflows using LangChain/LangGraph or equivalent toolkits. Implement and optimise vector search pipelines (FAISS/Pinecone/Milvus), embedding generation, chunking strategies, and relevance tuning for sub-second retrieval. Perform parameter-efficient fine-tuning (LoRA/adapters) and evaluation workflows; manage model versioning and automated validation for quality and safety. Containerise and deploy models and services with Docker and Kubernetes; integrate with cloud infra (AWS/Azure/GCP) and CI/CD for repeatable delivery. Establish observability, alerting, and performance SLAs for LLM services; collaborate with cross-functional teams to define success metrics and iterate rapidly. Skills & Qualifications Must-Have 4+ years engineering experience with 2+ years working directly on LLM/Generative AI projects. Strong Python skills and hands-on experience with PyTorch and HuggingFace/transformers libraries. Practical experience building RAG pipelines, vector search (FAISS/Pinecone/Milvus), and embedding workflows. Experience with fine-tuning strategies (LoRA/adapters) and evaluation frameworks for model quality and safety. Familiarity with Docker, Kubernetes, cloud deployment (AWS/Azure/GCP), and Git-based CI/CD workflows. Solid understanding of prompt engineering, retrieval strategies, and production monitoring of ML services. Preferred Experience with LangChain/LangGraph, agent frameworks, or building tool-calling pipelines. Exposure to MLOps platforms, model registry, autoscaling low-latency inference, and cost-optimisation techniques. Background in productionising LLMs for enterprise use-cases (knowledge bases, search, virtual assistants). Benefits & Culture Highlights Hybrid work model with flexible in-office collaboration and remote days; competitive market compensation. Opportunity to work on high-impact enterprise AI initiatives and shape production-grade GenAI patterns across customers. Learning-first culture: access to technical mentorship, experimentation environments, and conferences/learning stipend. To apply: include a brief portfolio of LLM projects, links to relevant repositories or demos, and a summary of production responsibilities. This role is ideal for engineers passionate about turning cutting-edge LLM research into reliable, scalable enterprise solutions. Skills: llm,open ai,gemini Show more Show less

Primary Title: Senior LLM Engineer (4+ years) Hybrid, India About The Opportunity A technology consulting firm operating at the intersection of Enterprise AI, Generative AI and Cloud Engineering seeks an experienced LLM-focused engineer. You will build and productionize LLM-powered products and integrations for enterprise customers across knowledge management, search, automation, and conversational AI use-cases. This is a hybrid role based in India for candidates with strong hands-on LLM engineering experience. Role & Responsibilities Own design and implementation of end-to-end LLM solutions: data ingestion ? retrieval (RAG) ? fine-tuning ? inference and monitoring for production workloads. Develop robust Python microservices to serve LLM inference, retrieval, and agentic workflows using LangChain/LangGraph or equivalent toolkits. Implement and optimise vector search pipelines (FAISS/Pinecone/Milvus), embedding generation, chunking strategies, and relevance tuning for sub-second retrieval. Perform parameter-efficient fine-tuning (LoRA/adapters) and evaluation workflows; manage model versioning and automated validation for quality and safety. Containerise and deploy models and services with Docker and Kubernetes; integrate with cloud infra (AWS/Azure/GCP) and CI/CD for repeatable delivery. Establish observability, alerting, and performance SLAs for LLM services; collaborate with cross-functional teams to define success metrics and iterate rapidly. Skills & Qualifications Must-Have 4+ years engineering experience with 2+ years working directly on LLM/Generative AI projects. Strong Python skills and hands-on experience with PyTorch and HuggingFace/transformers libraries. Practical experience building RAG pipelines, vector search (FAISS/Pinecone/Milvus), and embedding workflows. Experience with fine-tuning strategies (LoRA/adapters) and evaluation frameworks for model quality and safety. Familiarity with Docker, Kubernetes, cloud deployment (AWS/Azure/GCP), and Git-based CI/CD workflows. Solid understanding of prompt engineering, retrieval strategies, and production monitoring of ML services. Preferred Experience with LangChain/LangGraph, agent frameworks, or building tool-calling pipelines. Exposure to MLOps platforms, model registry, autoscaling low-latency inference, and cost-optimisation techniques. Background in productionising LLMs for enterprise use-cases (knowledge bases, search, virtual assistants). Benefits & Culture Highlights Hybrid work model with flexible in-office collaboration and remote days; competitive market compensation. Opportunity to work on high-impact enterprise AI initiatives and shape production-grade GenAI patterns across customers. Learning-first culture: access to technical mentorship, experimentation environments, and conferences/learning stipend. To apply: include a brief portfolio of LLM projects, links to relevant repositories or demos, and a summary of production responsibilities. This role is ideal for engineers passionate about turning cutting-edge LLM research into reliable, scalable enterprise solutions. Skills: llm,open ai,gemini Show more Show less

As a Generative AI Developer, your role will involve designing, building, and deploying solutions powered by Large Language Models (LLMs), multimodal AI, and prompt engineering. You will collaborate closely with product and engineering teams to integrate GenAI capabilities into real-world applications such as chatbots, copilots, content generation, and intelligent automation. Key Responsibilities: - AI/ML Development: - Fine-tune and optimize LLMs (GPT, LLaMA, Claude, etc.) for specific business use cases. - Build and deploy GenAI-powered applications like chatbots, copilots, summarization, Q&A systems, and generative content. - Experiment with multimodal AI involving text, image, audio, and video. - Prompt Engineering & Orchestration: - Design effective prompts and workflows to maximize model performance. - Work with frameworks like LangChain, LlamaIndex, and Haystack for retrieval-augmented generation (RAG). - Backend & Integration: - Develop APIs and services to integrate GenAI models into existing platforms. - Connect AI with structured and unstructured data sources. - Cloud & Deployment: - Deploy models on AWS, Azure, or GCP (SageMaker, Vertex AI, Azure OpenAI). - Implement scalable and cost-efficient inference pipelines. - MLOps & Performance: - Monitor AI models in production including latency, accuracy, and hallucination rates. - Implement continuous training, evaluation, and improvement workflows. Required Skills & Qualifications: - Strong programming skills in Python (Node.js/Java is a plus). - Hands-on experience with GenAI/LLMs (OpenAI, Anthropic, Hugging Face, Cohere, Stability AI). - Familiarity with LangChain, LlamaIndex, and RAG pipelines. - Knowledge of NLP, embeddings, vector databases (Pinecone, Weaviate, Milvus, FAISS). - Experience with cloud platforms (AWS, Azure, GCP) and deployment of ML models. - Understanding of prompt design, fine-tuning, and model evaluation. - Solid grasp of APIs, microservices, and REST/GraphQL integrations. Preferred: - Experience with multimodal models (text-to-image, speech-to-text, etc.). - Exposure to containerization and orchestration (Docker, Kubernetes). - Knowledge of data privacy, security, and compliance in AI systems. - Prior work in AI-driven SaaS products. In this role, you will have the opportunity to contribute to cutting-edge projects in the field of Generative AI. If you have experience deploying applications or AI models on cloud platforms, familiarity with AI/ML frameworks, and working with CDN platforms for scaling applications, we encourage you to apply for this full-time position.,

As part of the R&D Disruptive product team at Contentstack, you will play a crucial role in ideating and developing the MVP product, as well as creating new products. Your responsibilities will include: - Working with emerging technologies and experimenting with new ones to develop prototypes. - Collaborating with various product and engineering teams to integrate emerging tech into existing products. - Engaging in full-stack development, from code commits to production, to ensure the best user experience. - Designing, developing, and testing features throughout the development lifecycle. - Writing high-quality, scalable, testable, and reliable code. - Collaborating with cross-functional teams to understand the domain and deliver appropriate solutions. - Maintaining an open mindset for learning and adapting to new roles. - Continuous improvement through active learning and feedback mechanisms. Qualifications required for this role include: - Prior experience in Generative AI (LLM) and integrating with LLM APIs. - Proficiency in working with LLM Agents and creating Agentic AI solutions. - Experience in developing RAG pipelines and Prompt Engineering. - Ability to quickly learn new skills and apply them to solve complex problems. - Strong object-oriented design and development skills. - Knowledge of Software Development Life Cycle and proficiency in HTML, CSS, JavaScript, Node.js. - Excellent communication skills. - Exposure to databases such as MongoDB, Redis, and/or relational databases is preferred. - Familiarity with the tech stack including GenAI, Machine Learning, LLM, RAG, and NLP. - Experience level required is 2 to 6 years. About Contentstack: (Contentstack is a company focused on providing innovative solutions in the content management space. For any additional details about the company, please refer to their official website.),

As a Lead AI Developer at Aumento Technologies & Consulting Services Pvt Ltd, you will play a crucial role in bridging business requirements with cutting-edge AI solutions. You will independently design, develop, and deploy enterprise-grade AI systems, including RAG (Retrieval-Augmented Generation) based applications. **Key Responsibilities:** - Collaborate with business stakeholders to identify and scope AI/ML/GenAI opportunities - Lead development of RAG-based AI solutions, integrating LLMs with enterprise data sources - Design and implement data pipelines, embeddings, and vector databases for retrieval-based systems - Build and optimize machine learning, deep learning, NLP, and generative AI models - Deploy AI solutions into production on cloud platforms (SAP BTP AI Core, Azure ML, AWS Sagemaker, GCP Vertex AI) - Establish best practices in MLOps (CI/CD, monitoring, model retraining, governance) - Mentor junior AI developers and contribute to reusable AI accelerators **Required Skills & Experience:** - Bachelors/Masters degree in Computer Science, Data Science, AI/ML, or related field - 6+ years of experience in AI/ML development, with 2+ years in a lead/architect role - Strong programming in Python and experience with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) - Hands-on expertise in Generative AI, RAG pipelines, vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) - Experience with LLM integration (OpenAI, Anthropic, Hugging Face, LangChain, LlamaIndex, etc.) - Strong knowledge of NLP techniques: embeddings, transformers, summarization, question answering - Experience with cloud-based AI development (SAP BTP AI Core preferred, Azure, AWS, GCP) - Understanding of MLOps & model lifecycle management - Ability to articulate business requirements and convert them into scalable AI solutions **Good to Have:** - Experience integrating AI with SAP ecosystem (SAC, BTP, DataSphere, Integration Suite) - Domain exposure in Manufacturing, CPG industries, Pharma, Automotive - Knowledge of prompt engineering and fine-tuning LLMs - Experience in data security, governance, and responsible AI If you are passionate about building AI solutions that blend machine learning, generative AI, and RAG for real-world impact, do not hesitate to apply. Join us to lead cutting-edge AI & GenAI initiatives across industries and be part of an entrepreneurial, collaborative work environment with competitive compensation and fast-track growth opportunities.,

As an experienced consulting professional in the field of Data Science or AI/ML Engineering, you will be responsible for understanding solutions, industry best practices, and implementing Oracle products and technology to meet customer needs. You will operate independently to deliver high-quality work products to engagements, applying Oracle methodology, company procedures, and leading practices. **Key Responsibilities:** - Lead end-to-end AI/ML solution design and production deployment - Specialize in Generative AI, LLMs, NLP, and AI agent development - Expertise in Python and modern ML/NLP frameworks such as HuggingFace, LangChain, PyTorch, TensorFlow - Fine-tune LLMs for domain-specific applications like Q&A systems, auto-documentation, and predictive insights - Build, scale, and optimize AI systems on OCI with knowledge of hybrid/multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, vector databases, and RAG pipelines - Familiarity with MLOps, model governance, and CI/CD for ML workflows - Excellent communication and stakeholder management skills to bridge the gap between technical and executive teams **Qualifications & Experience:** - 12-15 years of total experience, with a minimum of 5 years in Data Science or AI/ML Engineering roles - Proven track record in AI/ML solution design and deployment - Expertise in Python and modern ML/NLP frameworks - Hands-on experience with AI systems on OCI and knowledge of multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, and model governance - Experience in stakeholder engagement, program oversight, and solution design **Additional Details:** The company is committed to an inclusive culture that celebrates diverse insights and perspectives, fostering an environment that inspires thought leadership and innovation. Oracle offers a competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability, including Medical, Life Insurance, Retirement Planning, and more. The company encourages employees to engage in giving back to communities and values diversity and inclusion in the workforce. If you are looking for a challenging role where you can leverage your expertise in AI/ML engineering to drive innovative solutions and work in a diverse and inclusive environment, this position at Oracle might be the perfect fit for you.,

As a Senior Data Scientist at AuxoAI, you will have the opportunity to lead the design, deployment, and scaling of production-grade ML systems, focusing on AI, machine learning engineering (MLE), and generative AI. Your role will involve a combination of cutting-edge research and production rigor, where you will be responsible for mentoring while building impactful AI applications. Key Responsibilities: - Own the full ML lifecycle, including model design, training, evaluation, and deployment - Design production-ready ML pipelines integrating CI/CD, testing, monitoring, and drift detection - Fine-tune Large Language Models (LLMs) and implement retrieval-augmented generation (RAG) pipelines - Build agentic workflows for reasoning, planning, and decision-making - Develop real-time and batch inference systems using Docker, Kubernetes, and Spark - Utilize state-of-the-art architectures such as transformers, diffusion models, RLHF, and multimodal pipelines - Collaborate with product and engineering teams to integrate AI models into business applications - Mentor junior team members and advocate for MLOps, scalable architecture, and responsible AI best workflows Qualifications Required: - 5+ years of experience in designing, deploying, and scaling ML/DL systems in production - Proficiency in Python and deep learning frameworks like PyTorch, TensorFlow, or JAX - Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines - Familiarity with agent-based development, including ReAct agents, function-calling, and orchestration - Strong understanding of MLOps tools such as Docker, Kubernetes, Spark, model registries, and deployment workflows - Solid software engineering background with expertise in testing, version control, and APIs - Demonstrated ability to balance innovation with scalable deployment - B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field Join AuxoAI and be part of a team that values innovation, scalability, and responsible AI practices to make a significant impact in the field of AI and machine learning.,

As a Senior AI Engineer at Uplevyl, you will play a crucial role in leading the design and deployment of AI-powered, agentic workflows that drive the future of personalized insights. Your main focus will be on vector search, retrieval-augmented generation (RAG), and intelligent automation, collaborating closely with full-stack engineers and product teams to bring scalable GenAI features into production. Key Responsibilities: - Design and implement RAG pipelines for semantic search, personalization, and contextual enrichment. - Build agentic AI workflows using Pinecone, LangChain/LangGraph, and custom orchestration. - Integrate LLM-driven features into production systems, balancing innovation with scalability. - Architect and optimize vector databases (Pinecone, FAISS, Milvus) for low-latency retrieval. - Work with structured/unstructured datasets for embedding, indexing, and enrichment. - Collaborate with data engineers on ETL/ELT pipelines to prepare data for AI applications. - Partner with backend and frontend engineers to integrate AI features into user-facing products. - Participate in Agile ceremonies (sprint planning, reviews, standups). - Maintain clear documentation and support knowledge sharing across the AI team. Required Qualifications: - 5+ years in AI/ML engineering or software engineering with applied AI focus. - Hands-on experience with RAG pipelines, vector databases (Pinecone, FAISS, Milvus), and LLM integration. - Strong background in Python for AI workflows (embeddings, orchestration, optimization). - Familiarity with agentic architectures (LangChain, LangGraph, or similar). - Experience deploying and scaling AI features on AWS cloud environments. - Strong collaboration and communication skills for cross-functional teamwork. Tech Stack: - AI Tools: Pinecone, LangChain, LangGraph, OpenAI APIs (ChatGPT, GPT-4/5), HuggingFace models - Languages: Python (primary for AI workflows), basic Node.js knowledge for integration - Cloud & DevOps: AWS (Lambda, S3, RDS, DynamoDB, IAM), Docker, CI/CD pipelines - Data Engineering: SQL, Python (Pandas, NumPy), ETL/ELT workflows, Databases (Postgres, DynamoDB, Redis) - Bonus Exposure: React, Next.js Preferred Skills: - Experience with embedding models, HuggingFace Transformers, or fine-tuning LLMs. - Knowledge of compliance frameworks (GDPR, HIPAA, SOC 2). - Exposure to personalization engines, recommender systems, or conversational AI.,

As a Data Scientist specializing in Generative AI, you will be responsible for the following: - Utilizing your 3+ years of experience in Data Science to work on generative AI, agentic AI, LLMs, and NLP. - Demonstrating hands-on expertise with RAG pipelines, knowledge graphs, and prompt engineering. - Applying your skills in Azure AI tools such as Azure OpenAI, Cognitive Services, and Azure ML. - Leveraging your experience with LangChain, Agentic AI frameworks, and orchestration tools. - Proficiency in utilizing Hugging Face for model building and fine-tuning. - Demonstrating strong Python development skills specifically tailored for AI applications. - Working with vector databases, embeddings, and semantic search implementations. - Applying your solid MLOps background including CI/CD pipelines, DevOps integration, and AI deployment optimization. - Familiarity with FastAPI, Databricks, AWS, MLflow, Faiss, Redis, and OpenAI APIs. - Being a great problem-solver who enjoys debugging and improving AI systems. Qualifications required for this role include: - Bachelor's or Master's degree in Computer Science, Data Science, or a related field. - 4 to 5 years of relevant experience in Data Science with a focus on generative AI and NLP. - Proven track record of working with AI tools and frameworks mentioned in the job description. If you are passionate about Data Science and Generative AI, and enjoy working on cutting-edge technologies, this role is perfect for you. Apply now by sending your resume to deepak.visko@gmail.com or call 9238142824. Please note that this is a full-time, permanent position with benefits including cell phone reimbursement, health insurance, paid sick time, paid time off, and Provident Fund. The work location is in person at Noida.,

Line of Service Advisory Industry/Sector Not Applicable Specialism Operations Management Level Director Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in intelligent automation at PwC will focus on conducting process mining, designing next generation small- and large-scale automation solutions, and implementing intelligent process automation, robotic process automation and digital workflow solutions to help clients achieve operational efficiencies and reduce costs. *Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences foreach other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firms growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Job Description & Summary: We are seeking an experienced Technical Director specializing in autonomous agents and Large Language Models (LLMs) to join our team. The ideal candidate will help design, develop, and optimize agents that can perform complex tasks autonomously while maintaining reliability and safety. Responsibilities: Design and implement autonomous agents using LangChain / Crew.ai / SK / Autogen and other relevant frameworks - Develop and optimize RAG systems for improved information retrieval and response generation - Create robust evaluation frameworks for testing agent performance and safety - Implement monitoring and logging systems for agent behavior - Develop documentation and best practices for agent development - Contribute to the improvement of agent architecture and capabilities Hands-on experience with: - Building and deploying autonomous agents - LangChain framework for developing applications - Retrieval Augmented Generation (RAG) systems - Large Language Models (LLMs) and their APIs - Solid understanding of safety principles and best practices - Resolving Hallucinations in the outcomes Mandatory skill sets: -Advanced Python programming with expertise in async programming and API development - Experience with vector databases and embedding models - Proficiency in implementing RAG pipelines and knowledge retrieval systems - Familiarity with prompt engineering and LLM optimization techniques - Experience with development frameworks and tools - Knowledge of modern software development practices (Git, CI/CD, testing) Preferred skill sets: Multiple LLM providers (OpenAI, Anthropic, etc.) - Tools for agent orchestration and workflow management - Natural Language Processing (NLP) techniques - Container technologies (Docker, Kubernetes) - Understanding of semantic search and information retrieval concepts - Knowledge of agent alignment and safety considerations Years of experience required: 15-20 years Education qualification: Graduate Engineer or Management Graduate Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master Degree, Bachelor Degree Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Automation Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, Analytical Thinking, Automation Algorithms, Automation Engineering, Automation Framework Design and Development, Automation Programming, Automation Solutions, Automation Studio, Automation System Efficiency, Blue Prism, Business Analysis, Business Performance Management, Business Process Analysis, Business Process Automation (BPA), Business Transformation, Business Value Optimization, C++ Programming Language, Coaching and Feedback, Cognitive Automation, Communication, Conducting Discovery, Configuration Management (CM) + 48 more Desired Languages (If blank, desired languages not specified) Travel Requirements Available for Work Visa Sponsorship Government Clearance Required Job Posting End Date Show more Show less

About Us At InzpireU, we are on a mission to amplify human potential through AI-powered mentorship, learning, and accountability. We believe AI should serve as an enabler of growthnot a replacement for people. As an AI Intern, you will be part of a passionate team building next-gen solutions that combine AI, data, and human guidance to transform how individuals and organizations learn, grow, and succeed. Role Overview We are seeking a motivated AI Intern who is eager to gain hands-on experience in applied AI, product development, and data-driven solutions. You will support the design, development, and testing of AI features across mentorship, learning personalization, and outcome tracking. This is an excellent opportunity to learn, experiment, and build real-world AI applications in a fast-paced startup environment. Key Responsibilities Assist in building and fine-tuning AI/ML models (LLMs, recommendation engines, NLP, etc.). Support integration of AI features into our platform (e.g., Co-Guru, APEX assessments, document writers). Research emerging AI tools and frameworks (e.g., LangChain, OpenAI, Gemini, vector databases) and provide insights for adoption. Help design conversational AI prompts, workflows, and evaluation strategies. Work with the engineering team to clean, label, and prepare datasets. Document experiments, findings, and best practices to build internal AI knowledge. Collaborate with product managers and mentors to align AI solutions with user needs. Requirements Currently pursuing a degree in Computer Science, AI/ML, Data Science, or related field . Basic understanding of Python , ML libraries (TensorFlow, PyTorch, scikit-learn), or LLM frameworks. Familiarity with APIs, databases, and cloud services (AWS/GCP/Azure is a plus). Strong interest in Generative AI, NLP, and applied machine learning . Analytical mindset with eagerness to learn and experiment. Good communication skills and ability to work in a collaborative, remote-first team. Preferred (Nice to Have) Hands-on experience with LangChain, RAG pipelines, vector databases (Pinecone, Weaviate, FAISS) . Exposure to AI ethics, bias mitigation, and responsible AI frameworks . Prior projects (academic or personal) in chatbots, recommendation systems, or predictive analytics . What Youll Gain Real-world exposure to AI product development in a startup environment . Mentorship from experienced engineers and AI innovators. Opportunity to contribute to features that directly impact users. Potential pathway to a full-time AI Engineer role upon successful completion. Show more Show less

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra India). The ideal candidate should have 1215+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. Top 3 Daily Tasks: ? Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. ? Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. ? Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed invisible intelligence within secure wearable systems. Must have 1215+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Must have: -Programming languages: Python, C/C++, Java (Android), Kotlin, JavaScript/Node.js, Swift, Objective-C, CUDA, Shell scripting -Expert in TensorFlow, PyTorch, ONNX, HuggingFace; model optimization with TensorRT, TFLite -Deep experience with LLMs, RAG pipelines, vector DBs (FAISS, Milvus) -Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops -Strong in privacy-preserving AI (federated learning, differential privacy) -Secure real-time comms (WebRTC, SIP, RTP) Nice to have: -Experience with MCP or similar protocol frameworks -Background in wearables/XR or smart glass AI platforms -Expertise in platform security architectures (sandboxing, auditability) Show more Show less

You are an experienced Senior Consultant with a strong background in Java development and practical exposure to Generative AI (GenAI) technologies. Your main responsibilities will include designing and delivering scalable solutions, integrating AI-driven capabilities into enterprise applications, and providing technical leadership to development teams. Your key responsibilities will involve designing, developing, and maintaining scalable applications using Java, Spring Boot, and Microservices. You will also be responsible for architecting and integrating Generative AI solutions such as LLMs, embeddings, and RAG pipelines into business applications. Collaborating with data scientists and AI engineers to operationalize models, developing and optimizing APIs for AI/ML services, and ensuring secure and efficient integration will be crucial aspects of your role. Additionally, implementing cloud-native solutions on platforms like AWS, Azure, or GCP will be part of your responsibilities. You will play a significant role in guiding and mentoring junior engineers, conducting code reviews, and knowledge-sharing sessions. Collaborating with business stakeholders to translate requirements into technical architecture and solutions will be essential. Ensuring that delivery aligns with best practices in software engineering, CI/CD, testing, and TDD/BDD will also be a key part of your responsibilities. To excel in this role, you must have at least 9 years of strong development experience in Java, Spring Boot, and Microservices. Hands-on experience with Generative AI/LLMs, a strong understanding of RESTful APIs, GraphQL, and event-driven architectures, as well as experience with cloud services like AWS Lambda, S3, DynamoDB, GCP Vertex AI, or Azure Cognitive Services are required. Exposure to vector databases, familiarity with prompt engineering and AI model fine-tuning, and a solid understanding of data pipelines and integrating AI services into enterprise workflows are also essential. You should have a strong grasp of software engineering best practices such as TDD, CI/CD, and Agile methodologies. It would be beneficial if you have experience in Python for AI/ML integrations, familiarity with Kubernetes, Docker, Terraform for deployment, knowledge of MLOps practices, and prior consulting experience in digital transformation or AI-led initiatives.,

Job Summary: We are seeking an innovative and highly skilled Data Scientist (LLM & Generative AI) with 5+ years of experience in machine learning, natural language processing, and applied AI. The ideal candidate will have deep expertise in large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and agentic AI approaches. This role involves developing intelligent, autonomous, and scalable AI solutions that leverage cutting-edge research in generative AI, transformers, and multi-agent systems. In addition, the candidate will be expected to collaborate closely with engineering teams to bring research into production. Key Responsibilities: Research, design, and implement advanced LLM-based solutions for NLP, knowledge retrieval, and reasoning tasks. Develop and fine-tune LLMs (e.g., GPT, LLaMA, Falcon, Claude) for domain-specific use cases. Apply agentic AI approaches (multi-agent systems, autonomous agents, decision-making pipelines) to real-world business challenges. Design and implement retrieval-augmented generation (RAG) pipelines to combine structured/unstructured data with LLM capabilities. Build and optimize prompt engineering frameworks, evaluation metrics, and automated testing for generative AI outputs. Collaborate with ML engineers to deploy models into scalable cloud environments (AWS/GCP/Azure). Work with cross-functional teams to integrate LLM-powered agents into applications, workflows, and customer-facing products. Stay up-to-date with the latest research in LLMs, generative AI, reinforcement learning, and agentic architectures. Mentor junior team members and contribute to building an internal knowledge base on applied AI best practices. Requirements: Must-Have Skills: 5+ years of experience in data science, ML, or AI research with a focus on NLP and deep learning. Strong experience working with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on expertise in fine-tuning and deploying LLMs using frameworks like Hugging Face Transformers, LangChain, or Haystack. Deep understanding of agentic AI approaches, including orchestration, multi-agent workflows, and autonomous reasoning systems. Proficiency in Python and ML libraries (PyTorch, TensorFlow, Hugging Face, LangChain, Ray). Strong background in applied NLP techniques such as text classification, summarization, embeddings, semantic search, and dialogue systems. Experience building RAG pipelines with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus). Familiarity with MLOps and cloud deployment (AWS Sagemaker, GCP Vertex AI, Azure ML). Nice-to-Have Skills: Knowledge of reinforcement learning (RLHF, RLAIF) for LLM optimization. Experience with multi-modal models (text, image, speech). Familiarity with graph databases and knowledge graphs for reasoning tasks. Contributions to open-source projects in NLP/LLM space. Understanding of privacy, security, and ethical considerations in generative AI. Location- remote Salary -25lpa Experience -5+years 6 months contract (extendable) Show more Show less

Ready to build the future with AI? At Genpact, we dont just keep up with technologywe set the pace. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory, our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment. Genpact (NYSE: G) is anadvanced technology services and solutions company that deliverslastingvalue for leading enterprisesglobally.Through ourdeep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead.Powered by curiosity, courage, and innovation,our teamsimplementdata, technology, and AItocreate tomorrow, today.Get to know us atgenpact.comand onLinkedIn,X,YouTube, andFacebook. Inviting applications for the role of Consultant – Generative AI Engineer In this role, you will be responsible for creating cutting-edge artificial intelligence solutions that possess a broad understanding of diverse tasks and domains. You will contribute to the development of intelligent systems capable of adapting and learning across a wide range of applications. Responsibilities Strong understanding of generative AI models and algorithms, with specific experience in Vector Search Utility and RAG techniques. Proficient in either of the Generative AI Model (OpenAI ChatGPT, llama, Claude 2, others), Machine Learning, Python, Flask/Django, microservices, Cloud (Azure, AWS, GCP - one of the cloud Azure / AWS is mandatory) Should have work experience working with Vector Search Utility, Retrieval-Augmented Generation (RAG), Knowledge mining from Multiple sources. Preferred if candidate has experience using data from Salesforce, ServiceNow, Confluence system for Knowledge mining. Candidate should be well verse with Prompt Engineering techniques. Proficiency in programming languages such as Python and frameworks like TensorFlow, PyTorch, or Keras. Experience with Databricks AI Platform or similar platforms. Knowledge of deep learning architectures, neural networks, and machine learning techniques. Experience with data preprocessing and data cleaning techniques. Strong analytical and problem-solving skills. Good communication and collaboration skills. Ability to work in a fast-paced and dynamic environment. Qualifications we seek in you! Minimum Qualifications / Skills BE/B.TECH Preferred Qualifications/ Skills Create comprehensive documentation of algorithms, models, and methodologies, and actively contribute to knowledge transfer within the team to foster a collaborative and learning-oriented environment. Demonstrated expertise in artificial intelligence, machine learning, and deep learning. Strong programming skills, preferably in Python, and experience with popular AI frameworks (e.g., TensorFlow, PyTorch). Experience with reinforcement learning and transfer learning in the context of General AI. Knowledge of cognitive science principles and their application to AI development. Why join Genpact? • Lead AI-first transformation – Build and scale AI solutions that redefine industries • Make an impact – Drive change for global enterprises and solve business challenges that matter • Accelerate your career—Gain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills • Grow with the best – Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace • Committed to ethical AI – Work in an environment where governance, transparency, and security are at the core of everything we build • Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

As a Generative AI Architect with 5 to 10+ years of experience, you will be responsible for designing, developing, and deploying enterprise-grade GenAI solutions. Your role will require in-depth expertise in LLMs, RAG, MLOps, cloud platforms, and scalable AI architecture. You will architect and implement secure, scalable GenAI solutions using LLMs such as GPT, Claude, LLaMA, and Mistral. Additionally, you will build RAG pipelines with LangChain, LlamaIndex, FAISS, Weaviate, and ElasticSearch. Your responsibilities will also include leading prompt engineering, setting up evaluation frameworks for accuracy and safety, and developing reusable GenAI modules for function calling, summarization, document chat, and Q&A. Furthermore, you will deploy workloads on AWS Bedrock, Azure OpenAI, and GCP Vertex AI, ensuring monitoring and observability with Grafana, Prometheus, and OpenTelemetry. You will apply MLOps best practices such as CI/CD, model versioning, and rollback. Researching emerging trends like multi-agent systems, autonomous agents, and fine-tuning will also be part of your role, along with implementing data governance and compliance measures like PII masking, audit logs, and encryption. To be successful in this role, you should have 8+ years of experience in AI/ML, including 2-3 years specifically in LLMs/GenAI. Strong coding skills in Python with Hugging Face Transformers, LangChain, and OpenAI SDKs are essential. Expertise in Vector Databases like Pinecone, FAISS, Qdrant, and Weaviate is required, along with hands-on experience with cloud AI platforms such as AWS SageMaker/Bedrock, Azure OpenAI, and GCP Vertex AI. Experience in building RAG pipelines and chat-based applications, familiarity with agents and orchestration frameworks like LangGraph, AutoGen, and CrewAI, knowledge of MLOps stack including MLflow, Airflow, Docker, Kubernetes, and FastAPI, as well as understanding of prompt security and GenAI evaluation metrics like BERTScore, BLEU, and GPTScore are also important. Excellent communication and leadership skills for architecture discussions and mentoring are expected in this role.,

You are a Machine Learning & Generative AI Engineer responsible for designing, building, and deploying advanced ML and GenAI solutions. This role presents an exciting opportunity to work on cutting-edge AI systems, such as LLM fine-tuning, Transformer architectures, and RAG pipelines, while also contributing to traditional ML model development for decision-making and automation. With a minimum of 3 years of experience in Machine Learning, Deep Learning, and AI model development, you are expected to demonstrate a strong proficiency in Python, PyTorch, TensorFlow, Scikit-Learn, and MLflow. Your expertise should encompass Transformer architectures (such as BERT, GPT, T5, LLaMA, Falcon) and attention mechanisms. Additionally, experience with Generative AI, including LLM fine-tuning, instruction tuning, and prompt optimization is crucial. You should be familiar with RAG (Retrieval-Augmented Generation) embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows. A solid foundation in statistics, probability, and optimization techniques is essential for this role. You should have experience working with cloud ML platforms like Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, or GCP Vertex AI. Familiarity with Big Data & Data Engineering tools like Spark, Hadoop, Databricks, and SQL/NoSQL databases is required. Proficiency in CI/CD, MLOps, and automation pipelines (such as Airflow, Kubeflow, MLflow) is expected, along with hands-on experience with Docker and Kubernetes for scalable ML/LLM deployment. It would be advantageous if you have experience in NLP & Computer Vision areas, including Transformers, BERT/GPT models, YOLO, and OpenCV. Exposure to vector search & embeddings for enterprise-scale GenAI solutions, multimodal AI, Edge AI / federated learning, RLHF (Reinforcement Learning with Human Feedback) for LLMs, real-time ML applications, and low-latency model serving is considered a plus. Your responsibilities will include designing, building, and deploying end-to-end ML pipelines covering data preprocessing, feature engineering, model training, and deployment. You will develop and optimize LLM-based solutions for enterprise use cases, leveraging Transformer architectures. Implementing RAG pipelines using embeddings and vector databases to integrate domain-specific knowledge into LLMs will also be part of your role. Fine-tuning LLMs on custom datasets for domain-specific tasks and ensuring scalable deployment of ML & LLM models on cloud environments are critical responsibilities. Collaborating with cross-functional teams comprising data scientists, domain experts, and software engineers to deliver AI-driven business impact is expected from you.,

* Develop AI solutions using Python, ML frameworks, OpenAI APIs. * Implement NLP techniques, LLM model dvlpmnt. * Collaborate on RAG pipelines, embeddings, AI-driven workflows. ability to build/deploy RAG pipelines, embeddings, AI-driven workflows .

Overview: We are seeking candidates who are willing to begin their employment at the iProgrammer office for the first three months. After this period, the role will transition to Saudi Arabia, where you will continue your work. The organization will provide full support for relocation, including visa processing, accommodation, and transportation. We are hiring Senior AI Python Developers to design and deploy scalable AI/ML solutions. Candidates should have strong Python expertise, experience with ML frameworks, and the ability to mentor juniors while driving innovation. Key Responsibilities Lead the design, development, and deployment of AI/ML models and pipelines. Build scalable Python applications and APIs to integrate AI into production systems. Architect and implement LLM-based solutions (GPT, Llama, Falcon) and RAG pipelines for enterprise use cases. Apply Agentic AI concepts to build autonomous and multi-agent systems. Perform AI fine-tuning for domain-specific and production-ready models. Implement and optimize OCR solutions for unstructured data. Leverage LangChain to develop advanced LLM-powered applications. Collaborate with product managers, data engineers, and DevOps teams to deliver robust solutions. Monitor and optimize model performance continuously. Write clean, efficient, and maintainable code following best practices. Guide, mentor, and review junior developers work. Stay updated with emerging AI/ML technologies and recommend adoption. Contribute to MLOps practices (CI/CD for ML, model versioning, Docker/Kubernetes deployment). Ensure compliance with data security, governance, and ethical AI standards. Qualifications & Skills Bachelors or Masters in Computer Science, Software Engineering, AI, or related fields. 5+ years of professional Python development experience. Proven expertise with ML frameworks: TensorFlow, PyTorch, Hugging Face, Scikit-learn. Hands-on experience with Agentic AI, AI Fine-Tuning, OCR, and LangChain. Strong grasp of ML algorithms, feature engineering, and data preprocessing. Knowledge of SQL/NoSQL databases. Experience with cloud platforms (AWS, GCP, Azure). Proficiency in Docker/Kubernetes. Strong analytical, problem-solving, and communication skills. Demonstrated leadership and mentoring abilities. Preferred (Nice to Have) Experience building SaaS AI products or enterprise AI solutions. Familiarity with data security standards (ISO 27001, GDPR, NCA). Research background in deep learning, NLP, or generative AI. Contributions to open-source AI/ML projects.

As an Associate Architect Machine Learning (ML) with 4-7 years of experience, you will play a crucial role in integrating generative AI (Gen AI) capabilities into various Software Development Lifecycle (SDLC) phases to enhance efficiency and innovation. Your primary focus will be on identifying high-impact business opportunities where Gen AI adoption can accelerate project delivery and improve solutioning across multiple domains. This position requires a blend of technical expertise, strategic thinking, and client engagement skills to successfully drive Gen AI implementation. Your responsibilities will include collaborating across multiple projects to identify Gen AI and ML strategies, leading discussions with clients to understand their pain points and recommend AI-driven solutions, actively contributing to strategy and operational meetings, and working closely with project engineering and product teams to implement Gen AI capabilities into production-ready solutions. You will also be involved in conducting proof-of-concepts (POCs) and feasibility studies, assisting teams with ML model selection, training, and deployment, and mentoring junior engineers and data scientists in best practices for ML and Gen AI development. To excel in this role, you must possess strong technical expertise in traditional ML techniques (supervised/unsupervised learning, time series forecasting, NLP) and Gen AI models (LLMs, diffusion models, transformers). Proficiency in Python, TensorFlow, PyTorch, and experience with cloud-based ML services (AWS, GCP, Azure) is essential. You should also be adept at architecting and optimizing scalable AI systems using microservices, containerization, and distributed computing for high availability and cost efficiency. Additionally, you must demonstrate strategic thinking skills by identifying and assessing new Gen AI opportunities in business processes, along with strong client handling and communication abilities to lead client discussions, presentations, and workshops effectively. Preferred qualifications for this role include prior experience in Gen AI solutioning for enterprise use cases, familiarity with LLM fine-tuning, prompt engineering, and knowledge retrieval techniques, as well as experience in deploying ML solutions in production environments at scale. Joining our team will provide you with the opportunity to be at the forefront of AI-driven innovation, collaborate with top AI/ML experts, and work on challenging projects that leverage cutting-edge AI technologies. If you are passionate about ML, Gen AI, and driving innovation, we invite you to apply and be a part of shaping the future of AI-driven solutions. Apply now to embark on this exciting journey with us.,

- GenAI-powered applications - Retrieval-Augmented Generation (RAG) pipelines - Prompt engineering and fine-tuning - Cloud platforms - Reusable components and APIs - MLOps practices - Integrate GenAI into business workflows - Hallucination mitigation Required Candidate profile - 5+ years of experience in AI/ML, with 2+ years in LLMs /GenAI - vector databases - Proficiency in Python - RAG pipelines, embeddings, and chat-based solutions - Cloud AI services - Prompt safety

Job Title: AI Engineer Generative AI & Multi-Agent Systems Location : Pan India Mode : Hybrid (2 days/week WFO) Role Overview We are looking for a highly skilled Python Developer with hands-on experience in LLM-based systems and multi-agent orchestration using frameworks like AutoGen and LangChain . The ideal candidate will be responsible for designing, building, and fine-tuning intelligent agent workflows that interact via APIs and LLMs to solve complex enterprise problems. Key Responsibilities Architect and implement multi-agent systems using AutoGen, LangChain, or similar frameworks Design and develop scalable backend services using Python (FastAPI, Flask, Django) Integrate and fine-tune LLMs (OpenAI, Azure OpenAI) for enterprise use cases Build Retrieval-Augmented Generation (RAG) pipelines and prompt engineering strategies Collaborate with cross-functional teams to deploy GenAI solutions in production Ensure robust API integrations and agent communication protocols Mandatory Skills Advanced Python programming Experience with AutoGen or other multi-agent orchestration frameworks Hands-on with OpenAI API , Azure OpenAI , and LLM integration Strong understanding of prompt engineering , embeddings, and RAG Familiarity with cloud platforms (Azure preferred) Good to Have Experience with LangGraph, Hugging Face Transformers Knowledge of vector databases (FAISS, ChromaDB) Exposure to CI/CD pipelines and containerization (Docker, Jenkins)

Do you have a passion for pushing the boundaries of innovation and excited about the potential of AI to enhance the human experience Come join Cerence AI, the global leader in AI for transportation, specializing in developing AI and voice-powered companions for various vehicles. With over 500 million cars equipped with Cerence technology, we collaborate with prominent automakers like Volkswagen, Mercedes, Audi, Toyota, and more to create intuitive, integrated experiences for safer, connected, and enjoyable journeys. Our team at Cerence AI is dedicated to advancing AI innovation globally, with headquarters in Burlington, Massachusetts, USA, and 16 other offices across Europe, Asia, and North America. We bring together diverse backgrounds and skills to elevate transportation user experiences. Our culture is customer-centric, collaborative, fast-paced, and fun, providing continuous opportunities for learning and career growth. We are looking for a talented and innovative AI Specialist to join our team, focusing on developing advanced speech recognition technologies for our automotive voice assistant model. The ideal candidate will have a strong background in AI/ML technologies, including experience in Speech & GenAI solutions development, research on emerging technologies, and collaboration with cross-functional teams to enhance product offerings. Your role will involve staying updated on the latest AI and NLP trends, designing software components to integrate LLM capabilities, analyzing data insights, testing and validating models for deployment, collaborating with stakeholders, and sharing knowledge through training sessions to foster innovation. Requirements for this role include a Bachelor's degree in computer science, Data Science, Artificial Intelligence, or related fields, proficiency in programming languages like React and Python, experience with dev-Ops, cloud platforms, release pipelines, and BI solutions. Strong analytical, problem-solving, and communication skills are essential for this position. Join Cerence Inc., the global industry leader in creating unique automotive experiences, and be part of a dynamic team driving innovation in voice and AI technology for cars. This exciting opportunity offers meaningful contributions to a rapidly growing industry, with a focus on equal opportunity and a secure workplace environment. Prospective and current employees are encouraged to follow security protocols, report suspicious activities, respect corporate security procedures, adhere to compliance regulations, maintain a zero-tolerance policy for workplace violence, and demonstrate knowledge of information security and data privacy requirements through internal training programs.,