496 Genai Jobs - Page 17

GenAI, NLP, or LLM based systems , strong Python development skills and working LangChain, LlamaIndex, Hugging Face Transformers, or similar GenAI libraries Deep understanding of vector databases and embedding techniques

Qualifications: A Bachelor's degree in a relevant field such as Computer Science, Software Engineering, or Data Science is preferred. A Masters degree in Artificial Intelligence is a plus. 3-8 years of experience working with Python and a high level of proficiency in the language. Outstanding analytical and problem-solving abilities. Extensive experience with Generative AI, with a solid understanding of end-to-end pipelines involving Large Language Models (LLMs) such as OpenAI, Llama, Claude, etc. Proven expertise in Prompt Engineering. Strong knowledge of NLP techniques, including text summarization, question answering, and more. Proficient in software design patterns, with experience in writing modular, reusable, and maintainable code. Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure). Relevant experience with Docker and Kubernetes is highly desirable. Strong ability to rapidly prototype ideas and tackle complex problems with innovative solutions. Experience working within an Agile development environment. Excellent communication and presentation skills.

Introduction A Data and AI Technology Sales Engineer role (what we internally call a, Brand Technical Specialist) within IBMs zStack brand means accelerating enterprises success by improving their ability to understand their data. It means providing solutions that enable people across organizations, in multiple roles, the ability to turn data into actionable insights without having to wait for IT. And it means solutioning and selling multi-award winning software deployed on IBM z/LinuxONE platform, and world-class design practices that enables business analysts to ask new questions. The answers to which are literally shaping the future and changing the world. Excellent onboarding and an industry leading learning culture will set you up for positive impact and success, whilst ongoing development will advance your career through an upward trajectory. Our sales environment is collaborative and experiential. Part of a team, youll be surrounded by bright minds and keen co-creators - always willing to help and be helped - as you apply passion to work that will compel our clients to invest in IBMs products and services. Your role and responsibilities Applying excellent communication and empathy, youll act as a trusted strategic advisor to some of the worlds most transformational enterprises and culturally influential brands, as they rely on your expertise and our technology to solve some of their hardest problems. With your focus on the front-end of the solution lifecycle, youll be a master at listening to stakeholders, grasping their business challenges and requirements, and forming more detailed definitions of new architectural structures that will make up their best-fit, value adding solutions. Were committed to success. In this role, your achievements will drive your career, team, and clients to thrive. A typical day may involve: Understanding client needs and aligning them with IBM Z solutions. Creating effective end-to-end architecture using IBM Z. Ensuring architectural viability and conducting assessments. Identifying and resolving project risks and conflicts. Your primary responsibilities will include: - Client Strategy Design: Creating client strategies for Data & AI infrastructure around the IBM z and LinuxONE platform - Solution Definition: Defining IBM Data & AI solutions that constitute functionalities such as Data Integration (ETL), Data Store (DB2, Oracle, MySql) and Data Science (Watson studio, Watson ML) leveraging the strengths of the IBM z and LinuxONE platform - Providing proof of concepts and simplifying complex topics for meeting clients business requirements in the area of data platform modernization and analytics. - Credibility Building: Establishing credibility and trust to facilitate architecture and solution benefits to drive revenue and technical business objectives. Required education Bachelors Degree Required technical and professional expertise Required Professional and Technical Expertise : - Minimum 8-14 years of experience in Data and AI technologies which should include infrastructure for Analytics & Advance Analytics solutions like Datalake, Data Warehouse, Business Analytics, AI, GenAI & Datafabric - Experiential selling including co-creation and hands-on technical sales methods such as: demos, custom demos, Proofs of concept, Minimum Viable Products (MVPs) or other technical proofs Build deep brand (Data & AI) expertise to assist partners to deliver PoX (Custom Demo, PoC, MVP, etc.) to progress opportunities. Identifying partners with skills, expertise, and experience Exceptional interpersonal and communication skills, and an ability to collaborate effectively with Ecosystem Partners, clients and sales professionals. Understanding of areas of Governance Risk and Controls is a bonus. Experience in AI Landscape and technologies at work across Banking/Finance Know how and technical capabilities and working experience on similar Data AI Products like Cloudera, Teradata, Oracle, Informatica, SAS, etc Preferred technical and professional experience - Knowledge of IBM Z and how it fits in the Digital Transformation (training in IBMs Z product will be provided)

About the Role We are looking for a Senior Data Scientist to come and work on our growing AI stack. You will be working with a team of highly skilled and motivated data scientists and machine learning engineers. If you are excited about natural language understanding and machine translation, AppZen is the right place for you to apply and grow your skills. Key Responsibilities: Solid understanding of machine learning fundamentals, and familiar with standard algorithms and techniques Solid understanding of Python programming, including core data structures (lists, dicts, sets, tuples), object-oriented design, and writing clean, modular, and maintainable code. Experience with code optimization techniques, including efficient memory and runtime usage, vectorization (NumPy/Pandas), and debugging performance bottlenecks. Hands-on experience with LLMs such as GPT, LLaMA, or Claude, including evaluation and integration into production pipelines. Proficiency in using GenAI frameworks and tools (e.g., Hugging Face Transformers, LangChain, OpenAI APIs, vLLM, or AutoGen) to build, customize, and deploy language-based solutions. Ability to analyze, evaluate, and optimize LLM outputs for accuracy, safety, relevance, and bias mitigation in enterprise use cases. Work with internal and external stakeholders on program management Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be useful Excellent written and verbal technical communication skills; communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions M.Tech/B.Tech. or equivalent experience in Computer Science, Engineering, Statistics, or other relevant technical field Must have 6+ years of industry experience You are a team player Nice-to-Have: Track record of having developed novel algorithms, e.g. publications in one or more of the following: KDD, WWW, NIPS, ISWC, NAACL, ACL, SIGIR, EMNLP, ICML etc Good Understanding of MLOps tools/processes like ElasticSearch, Jenkins, Docker is plus. Expertise in building and fine-tuning LLM models using Transformers and RAG systems.

In this role, you will: Participate in low to moderately complex initiatives and projects associated with the technology domain, including installation, upgrades, and deployment efforts Identify opportunities for service quality and availability improvements within the technology domain environment Design, code, test, debug, and document for low to moderately complex projects and programs associated with technology domain, including upgrades and deployments Review and analyze technical assignments or challenges that are related to low to medium risk deliverables and that require research, evaluation, and selection of alternative technology domains Present recommendations for resolving issues or may escalate issues as needed to meet established service level agreements Exercise some independent judgment while also developing understanding of given technology domain in reference to security and compliance requirements Provide information to technology colleagues, internal partners, and stakeholders Required Qualifications: 2+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing . --- What the Candidate Will Do ---- Build GenAI powered customer support assistants through prompt engineering 3P LLMs or fine-tuning custom LLMs. Work with stakeholders across engineering, product and data science to understand product requirements, prototype, iterate and launch GenAI assistants in production. Explore novel ideas and innovative solutions that can lead to a step change in our products. ---- Basic Qualifications ---- Master's degree in Computer Science or closely related field. Knowledge of latest ML algorithms such as GenAI, NLP, CV, recommendation systems. Coding chops, clean, elegant, bug-free code in languages like Java, GO Strong desire to learn and grow, while building the best-in-class systems ---- Preferred Qualifications ---- Deep knowledge of NLP theory and an understanding of the latest innovations in Generative AI Contributed to the broader technical community through tech talks, publications, open source projects, or other ways. Have a proven track record working across an organization not just across teams. We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. .Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .

Bengaluru [Hybrid 2 days/week] Skill & Experience Mandatory Skills: GenAI Exposure, Data Modelling, Database Development, Data Warehouse Management, Data Strategy Development, End to end Data Architecture, Virtualization and Consumption layer expertise Developing and maintaining data pipelines for efficient data extraction, transformation, and loading (ETL) processes. Designing and optimizing data storage solutions, including data warehouses and data lakes. Ensuring data quality and integrity through data validation, cleansing, and error handling. Collaborating with data analysts, data architects, and software engineers to understand data requirements and deliver relevant data sets (e.g., for business intelligence). Implementing data security measures and access controls to protect sensitive information. Automating and improving data processes and workflows for scalability and efficiency. Monitoring data infrastructure for performance and reliability to address issues promptly. Keeping abreast of industry trends and emerging technologies in data engineering. Documenting data pipelines, processes, and best practices for knowledge sharing. Participating in data governance and compliance efforts to meet regulatory requirements. Providing technical support and mentoring to junior data engineers, if applicable. Continuously optimizing data architecture to support the company's evolving data needs. Collaborating with cross-functional teams to drive data-driven decision-making within the organization.

[Hybrid 2 days/week] Skill & Experience Mandatory Skills: GenAI Exposure, Data Modelling, Database Development, Data Warehouse Management, Data Strategy Development, End to end Data Architecture, Virtualization and Consumption layer expertise Developing and maintaining data pipelines for efficient data extraction, transformation, and loading (ETL) processes. Designing and optimizing data storage solutions, including data warehouses and data lakes. Ensuring data quality and integrity through data validation, cleansing, and error handling. Collaborating with data analysts, data architects, and software engineers to understand data requirements and deliver relevant data sets (e.g., for business intelligence). Implementing data security measures and access controls to protect sensitive information. Automating and improving data processes and workflows for scalability and efficiency. Monitoring data infrastructure for performance and reliability to address issues promptly. Keeping abreast of industry trends and emerging technologies in data engineering. Documenting data pipelines, processes, and best practices for knowledge sharing. Participating in data governance and compliance efforts to meet regulatory requirements. Providing technical support and mentoring to junior data engineers, if applicable. Continuously optimizing data architecture to support the company's evolving data needs. Collaborating with cross-functional teams to drive data-driven decision-making within the organization.

Machine Learnig ,Deep Learning,Python,GenAI

Role & responsibilities A skilled SDET with expertise in Python and a basic understanding of Generative AI (GenAI) to join our quality engineering team. The ideal candidate will be responsible for designing automated test frameworks, implementing test strategies, and leveraging AI-driven automation techniques to enhance testing efficiency. Key Responsibilities: Develop, maintain, and optimize automated test frameworks and scripts using Python . Design and execute API, UI, and performance testing using tools like Pytest, Selenium. Integrate GenAI-based automation techniques to improve test generation, defect prediction, and self-healing scripts. Collaborate with developers to implement CI/CD pipelines and ensure robust test automation in DevOps environments. Conduct root cause analysis for defects and implement intelligent test strategies for faster issue resolution. Work with large datasets and create synthetic test data using AI-based models. Leverage AI-powered tools to optimize test coverage and reduce redundant test cases. Maintain and enhance monitoring and logging frameworks for better observability in test environments. Preferred candidate profile Strong proficiency in Python for test automation and scripting. Experience with test automation tools (Pytest, Selenium, Robot Framework, Playwright). Hands-on experience in API testing (Postman, RestAssured, FastAPI, Flask). Familiarity with GenAI concepts and AI-driven testing approaches. Exposure to AI/ML libraries like TensorFlow, OpenAI API, or Hugging Face is a plus. Experience with Docker, Kubernetes, Jenkins, and Git for automation in DevOps pipelines. Working knowledge of cloud platforms ( AWS, Azure, GCP ) and infrastructure testing. Strong analytical skills with a problem-solving mindset. Good to Have: Experience with AI-powered test automation tools (Testim, Mabl, Applitools). Familiarity with LLMs (Large Language Models) and AI-assisted testing frameworks. Understanding of data science workflows for test data generation. Previous experience working in Agile/Scrum teams.

Role & responsibilities Management Level - VP/Senior Manager Work Model - Hybrid (twice a week - Should be based out of the base location) Team Size - IC Regions - All Global regions Target Orgs - Genpact, TCS, similar organizations, Big 4s Skill requirements Strong experience in core F&A solutioning (all 3 towers (R2R/O2C/P2P exp. is required)) Proficient in handling presales activities, including RFPs and RFIs, solution designing etc. Look at specialists who can re-imagine the Future of Finance using AI/GenAI and Agentic Architecture Consulting mindset: Out of the box thinking, Zero Based Solutioning approach Ability to tell a coherent story to the client on solution and value differentiation Target Operating Model and business case / Return on Investment sense are default Traditional Pre-Sales, RFP, RFI candidates will not fit our SA of the Future.

Main Skills : AI Archt (Solutions/Technical) - LLM/Gen AI + Any Cloud + Python Project Role : AI / ML Engineer Project Role Description: Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Natural Language Processing (NLP) Roles & Responsibilities: Expected to perform independently and become an SME. Required active participation/contribution in team discussions. Contribute in providing solutions to work related problems. Develop applications and systems utilizing AI tools and Cloud AI services. Apply GenAI models as part of the solution. Implement deep learning and neural networks. Create chatbots and work on image processing. Collaborate with team members to provide innovative solutions. Professional & Technical Skills: Must To Have Skills: Proficiency in Natural Language Processing (NLP). Strong understanding of statistical analysis and machine learning algorithms. Experience with data visualization tools such as Tableau or Power BI. Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: The candidate should have a minimum of 2 years of experience in Natural Language Processing (NLP).

Main Skills : AI Archt (Solutions/Technical) - LLM/Gen AI + Any Cloud + Python Project Role : AI / ML Engineer Project Role Description: Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Natural Language Processing (NLP) Roles & Responsibilities: Expected to perform independently and become an SME. Required active participation/contribution in team discussions. Contribute in providing solutions to work related problems. Develop applications and systems utilizing AI tools and Cloud AI services. Apply GenAI models as part of the solution. Implement deep learning and neural networks. Create chatbots and work on image processing. Collaborate with team members to provide innovative solutions. Professional & Technical Skills: Must To Have Skills: Proficiency in Natural Language Processing (NLP). Strong understanding of statistical analysis and machine learning algorithms. Experience with data visualization tools such as Tableau or Power BI. Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: The candidate should have a minimum of 2 years of experience in Natural Language Processing (NLP).

Main Skills : AI Archt (Solutions/Technical) - LLM/Gen AI + Any Cloud + Python Project Role : AI / ML Engineer Project Role Description: Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Natural Language Processing (NLP) Roles & Responsibilities: Expected to perform independently and become an SME. Required active participation/contribution in team discussions. Contribute in providing solutions to work related problems. Develop applications and systems utilizing AI tools and Cloud AI services. Apply GenAI models as part of the solution. Implement deep learning and neural networks. Create chatbots and work on image processing. Collaborate with team members to provide innovative solutions. Professional & Technical Skills: Must To Have Skills: Proficiency in Natural Language Processing (NLP). Strong understanding of statistical analysis and machine learning algorithms. Experience with data visualization tools such as Tableau or Power BI. Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: The candidate should have a minimum of 2 years of experience in Natural Language Processing (NLP).

Hands-on experience in IOT product and tools, Gen AI, SQL and basics of PLC programming with troubleshooting. Strong analytical and problem solving skills. Exposure in MySQL, Python and PLC logic understanding. Previous experience in debugging and understanding of PLC systems, and industrial protocols such as (OPC,MQTT,TCP) Integrating and utilizing existing GenAI models and services Understanding and Evaluating GenAI Models and APIs Integrating GenAI Services (e.g., GPT-3, Claude, Anthropic, Google AI, etc.) Prompt Engineering for GenAI Models Software Development Life Cycle (SDLC) methodologies (Agile, Scrum)

Must to Have OR Primary skillsets 1. Proficiency in Solution Architecture, Costing and Pricing, Staffing sizing estimations, Infrastructure Managed Services (IMS) solutioning, Cloud Solutioning, Good grip on Excels 2. Solution Manager, Solution Architect, PreSales Architect, Presales Solution, Sales Solution Architect, Solution Manager Also have experience in 1. Pre-solutioning is Sales stages, Presales area, Drafting Solution Plan, Proposal Response, Deal stakeholder mgmt., Reviews and approvals from Deal Team Good to have Cloud, Paas, Data AI, GenAI, Automation

Management Level - VP/Senior Manager Work Model - Hybrid (twice a week - Should be based out of the base location) Team Size - IC Regions - All Global regions Target Orgs - Genpact, TCS, similar organizations, Big 4s Skill requirements Strong experience in core F&A solutioning (all 3 towers (R2R/O2C/P2P) exp. is required) Proficient in handling presales activities, including RFPs and RFIs, solution designing etc. Look at specialists who can re-imagine the Future of Finance using AI/GenAI and Agentic Architecture Consulting mindset: Out of the box thinking, Zero Based Solutioning approach Ability to Tell a coherent story to the client on solution and value differentiation Target Op Model and business case / Return on Investment sense are default. Traditional Pre-Sales, RFP, RFI candidates will not fit our SA of the Future.

Management Level - VP/Senior Manager Work Model - Hybrid (twice a week - Should be based out of the base location) Team Size - IC Regions - All Global regions Target Orgs - Genpact, TCS, similar organizations, Big 4s Skill requirements Strong experience in core F&A solutioning (all 3 towers (R2R/O2C/P2P) exp. is required) Proficient in handling presales activities, including RFPs and RFIs, solution designing etc. Look at specialists who can re-imagine the Future of Finance using AI/GenAI and Agentic Architecture Consulting mindset: Out of the box thinking, Zero Based Solutioning approach Ability to Tell a coherent story to the client on solution and value differentiation Target Op Model and business case / Return on Investment sense are default. Traditional Pre-Sales, RFP, RFI candidates will not fit our SA of the Future.

Hi, We are hiring for the Leading ITES Company for Transformation Lead - FAO Profile. Job Description : Experienced F&A Transformation Lead ( O2C , R2R & P2P all 3 Towers) to drive the strategic evolution and continuous improvement of our F&A processes. Roles & Responsibilities: Develop and execute a comprehensive F&A transformation (O2C, R2R & P2P all 3 Towers) strategy aligned with organizational goals and industry trends. Lead and manage a team , including product business owners and solution architects. Foster a collaborative and high-performance culture within the team, providing guidance and support to ensure successful outcomes. Identify and implement innovative technologies, methodologies, tools, and products to streamline F&A processes. Analyze existing F&A processes to identify areas for improvement, driving initiatives to enhance efficiency, reduce costs, and mitigate risks. Set annual targets on key KPIs/metrics for delivery teams across F&A, working in collaboration with delivery, other teams, using best practices, benchmarking, and ongoing initiatives. Design and oversee the implementation of end-to-end F&A processes to ensure seamless operations. Define guidelines, process enhancements, and targets for continuous improvement. Lead governance efforts related to changes in tools and solutions, collaborating with Vendors, CIO, Finance, and Functional Delivery Teams. Establish and monitor key performance indicators (KPIs) to track the effectiveness of F&A transformation initiatives and drive continuous improvement. Qualifications, Work Experience & Skills Minimum 10+ years of experience of which 5+ years in F&A Operations and 3 years of relevant experience ( in Transformation) Proven experience in F&A process management and transformation, with a focus on leading multiple products. Deep understanding of F&A (All 3 Towers) processes. Expertise in leveraging innovative technologies like RPA, Gen AI, Automation tools, and products for process optimization. Key Skills : a) Minimum 10+ years of experience in F&A Operations b) Minimum 3 years of relevant experience in Transformation c) Expertise in leveraging innovative technologies like RPA, Gen AI,Automation tools. d) Any Graduate To Apply, WhatsApp 'Hi' @ 9151555419 Follow the Steps Below: >Click on Start option to Apply and fill the details >Select the location as Other ( to get multiple location option ) a) To Apply for above Job Role ( Noida )Type : Job Code # 550 b) To Apply for above Job Role ( Nagpur )Type : Job Code # 551

Job Description Management Level: Ind & Func AI Decision Science Analyst/Consultant Location: Bengaluru (Bangalore), Gurugram (Gurgaon), Hyderabad, Chennai. Must-have skills: Programming languages -Python/R, Generative AI, Large Language Models (LLMs), ML libraries such as Scikit-learn, TensorFlow, Torch, Lang Chain, or OpenAI API, RAG Applications. Good to have skills : Big data technologies such as Spark or Hadoop,AI model explainability(XAI),bias detection and AI ethics. Familiarity with Edge AI and deploying models on embedded devices for industrial automation. Experience with Reinforcement Learning (RL) and AI-driven optimization techniques. Job Summary We are looking for a Data Scientist / AI Specialist with 2-9years of experience to join our team and work on client projects in the Automotive & Industrial sectors. This role will involve leveraging traditional Machine Learning (ML), Generative AI (GenAI), Agentic AI, and Autonomous AI Systems to drive innovation, optimize processes, and enhance decision-making in complex industrial environments. Prior experience in the Auto/Industrial industry is a plus, but we welcome candidates from any domain with a strong analytical mindset and a passion for applying AI to real-world business challenges. Roles & Responsibilities: Develop, deploy and monitor AI/ML models in production environments & enterprise systems, including predictive analytics, anomaly detection, and process optimization for clients. Work with Generative AI models (e.g., GPT, Stable Diffusion, DALLE) for applications such as content generation, automated documentation, code synthesis, and intelligent assistants. Implement Agentic AI systems, including AI-powered automation, self-learning agents, and decision-support systems for industrial applications. Design and build Autonomous AI solutions for tasks like predictive maintenance, supply chain optimization, and robotic process automation (RPA). Work with structured and unstructured data from various sources, including IoT sensors, manufacturing logs, and customer interactions. Optimize and fine-tune LLMs (Large Language Models) for specific business applications, ensuring ethical and explainable AI use. Utilize MOps and AI orchestration tools to streamline model deployment, monitoring, and retraining cycles. Collaborate with cross-functional teams, including engineers, business analysts, and domain experts, to align AI solutions with business objectives. Stay updated with cutting-edge AI research in Generative AI, Autonomous AI, and Multi-Agent Systems. Professional & Technical Skills: 3-5 years of experience in Data Science, Machine Learning, or AI-related roles. Proficiency in Python (preferred) or R, and experience with ML libraries such as Scikit-learn, TensorFlow, Torch, Lang Chain, or OpenAI API. Strong understanding of Generative AI, Large Language Models (LLMs), and their practical applications. Hands-on experience in fine-tuning and deploying foundation models (e.g., OpenAI, Llama, Claude, Gemini, etc.). Experience with Vector Databases (e.g., FAISS, Chroma, Weaviate, Pinecone) for retrieval-augmented generation (RAG) applications. Knowledge of Autonomous AI Agents (e.g., AutoGPT, BabyAGI) and multi-agent orchestration frameworks. Experience working with SQL and NoSQL databases. Familiarity with cloud platforms (AWS, Azure, or GCP) for AI/ML model deployment. Strong problem-solving and analytical thinking abilities. Ability to communicate complex AI concepts to technical and non-technical stakeholders. Bonus: Experience in Automotive, Industrial, or Manufacturing AI applications (e.g., predictive maintenance, quality inspection, digital twins). Additional Information: Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record /MBA from top-tier universities. Excellent Communication and Interpersonal Skills. About Our Company | Accenture Job Qualifications Job Qualifications Experience: Minimum 2-9 years of relevant Data Science, Machine Learning or AI-related roles., Exposure to Industrial & Automotive Firms or Professional Services. Educational Qualification: Bachelor/Master’s degree in Statistics/Economics/ Mathematics/ Computer Science or related disciplines with an excellent academic record or MBA from top-tier universities.

Roles and Responsibilities Design and develop AI-powered solutions using various tools such as Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, etc. Collaborate with cross-functional teams to identify business problems and design data science projects that solve real-world issues. Develop predictive models and algorithms to analyze large datasets and provide insights for informed decision-making. Conduct exploratory data analysis (EDA) to identify trends, patterns, and correlations in complex datasets. Communicate technical findings effectively through reports, presentations, and visualizations.

Senior Tech Lead AWS AI (Anthropic) Experience: - Minimum 12-15 years of total IT experience, with at least 57 years in AI/ML engineering and solution implementation. Strong hands-on expertise in building and deploying GenAI solutions on AWS using services like Amazon Bedrock, SageMaker, and integration with Anthropic Claude models. Location: Bangalore / Pune (hybrid/flexible on a case-by-case basis) Role Overview: - The Senior Tech Lead AWS AI (Anthropic) will be responsible for driving the development and deployment of AI/ML solutions using AWS-native services, particularly leveraging Amazon Bedrock and Claude by Anthropic. The role demands a hands-on technical leader who can guide engineering teams, collaborate with architects, and translate solution blueprints into high-quality implementations. The ideal candidate is expected to bring strong experience in delivering GenAI solutions, coding expertise in Python, and a deep understanding of AWS AI/ML services. Key Responsibilities:- Lead technical implementation of AI solutions using AWS Bedrock (Claude, Titan), Amazon SageMaker, Lambda, and other AWS-native services. Translate high-level solution designs into detailed technical tasks and oversee delivery across engineering teams. Develop and optimize prompts, fine-tune models, implement RAG patterns, and integrate vector search solutions (e.g., OpenSearch, Pinecone). Build scalable and secure APIs to expose GenAI capabilities to enterprise applications. Design and implement end-to-end ML pipelines using SageMaker, Step Functions, and MLOps best practices. Ensure compliance with AWS security best practices including IAM roles, data encryption, and responsible AI principles. Collaborate closely with solution architects, product owners, and DevOps teams for successful deployment and monitoring. Support PoCs and pilots, ensuring timely delivery, performance benchmarks, and smooth handover to production. Mentor junior engineers, promote clean coding practices, and contribute to reusable code assets and internal GenAI accelerators. Required Skills and Competencies: - Strong hands-on experience with Amazon Bedrock and Claude models (prompt tuning, RAG, embeddings). Proficiency in Python and cloud-native development using RESTful APIs, AWS SDKs, and event-driven patterns. Deep knowledge of Amazon SageMaker (model training, deployment, tuning, pipelines). Experience implementing vector search, embedding pipelines, and prompt engineering strategies. Familiarity with LangChain, Haystack, or equivalent GenAI orchestration frameworks. Knowledge of AWS services including Lambda, API Gateway, Step Functions, DynamoDB, and IAM. Exposure to model evaluation, cost-performance optimization, and real-time inference patterns. Desirable Qualifications: - AWS Certified Machine Learning Specialty or AWS Certified Solutions Architect Associate/Professional. Experience with CI/CD pipelines, model versioning, and infrastructure-as-code using CDK or Terraform. Knowledge of GenAI applications such as chatbots, summarization tools, code assistants, and content generation. Exposure to third-party models (e.g., Cohere, Stability AI) integrated via AWS Marketplace. Soft Skills: - Strong problem-solving and debugging skills with a bias for action. Excellent verbal and written communication; able to explain complex technical concepts clearly. Leadership mindset with the ability to coordinate across distributed teams. Adaptability and enthusiasm for learning new GenAI tools and technologies in a fast-paced environment.

Role: Gen AI Engineer Exp: 5 to 8 yrs. Loc: Bangalore, Pune, Hyderabad NP: Immediate joiners, who can join in 30 days. Required Skills: Python, Large Language Models (LLM), Machine Learning (ML), Generative AI

About The Role Were building an agentic AI platform that turns one line of text and a video feed into end-to-end, real-time computer-vision solutionsthink semantic video search, object / action recognition, and task-oriented visual agents deployable with a single click As a Gen AI ML Engineer, youll architect the core vision & multimodal-reasoning stack and pave the road from prototype to production. Roles And Responsibilities Semantic video search Ship a pipeline that allows users to type show every forklift near aisle 5 in the last 30 minutes and get keyed-off clips in Wire embeddings to a hybrid FAISS/HNSW index; surface results through a simple REST & React playground. Create agentic pipelines Chain vision language models and zero/few-shot vision models with LLM planners (Gemini, GPT-4o, AutoGen, etc.) so a single prompt becomes a multi-step perception workflow. Profile and accelerate inference (TensorRT, ONNX, quantization, batching) to meet latency / throughput targets on GPU and CPU fleets. Rapid prototyping loops Run weekly paper-to-prototype spikes: reproduce a fresh arXiv idea, benchmark, and decide go/no-go in Hand successful python scripts & checkpoints to MLOps for productionizationno plumbing marathons. Data & Evaluation Spin up scalable pipelines for video ingestion, labeling (active learning, weak supervision), experiment tracking, and continuous evaluation. Collaborate & Lead Partner with product and ML Ops engineers; set research direction, mentor future hires, and establish best practices. Must-have Skill Set 13 years deep-learning research experience (internships & grad work count). Fluency in Python + PyTorch; comfortable hacking large vision/LLM repos. Proof you ship ideasfirst-author paper, OSS repo, Kaggle medal, or faithful reproduction of a cutting-edge model. Hands-on with LLM prompting/fine-tuning and at least one agent framework. Able to turn fuzzy product asks into measurable experiments and explain results clearly. Bonus Cred Large-scale video retrieval or temporal grounding experience. Prior work building agentic-AI pipelines that combine perception models with LLM reasoning. Open-source contributions to GenAI/vision libs (OpenCLIP, Vid2Seq, ViperGPT, etc.). What can you expect? Ability to shape the future of manufacturing by leveraging best-in-class AI and software; we are a unique organization with niche skill set that you would also develop while working with us World class work culture, coaching and development Mentoring from highly experienced leadership from world class companies (refer to Ripik.AI website for details) International exposure Work Location NOIDA (Work from Office)

What you will be doing As the AID Engr III Spec - Data Science - AI Product Manager for Business Enablement Organization, you will be responsible for Business engagement, architecting and building innovative solutions by applying cutting edge data science techniques. Engaging closely with the business stakeholders, understand problem statements and incubate ideas and models. Discovering insights using data modeling and analysis techniques that will guide strategic decisions and uncover optimization opportunities. Creating data science driven solutions that drive product effectiveness, personalization, better customer experience and operational efficiencies. Working closely with the stakeholder to prioritize the use cases and build the roadmap. Working with a talented team of data analysts, software developers and data science professionals who will play a key role in developing and delivering the next generation AI/ML solutions to the business. Having a passion to understand domains, systems and be able to associate business opportunities to this understanding and create analytical solutions Strategies and opportunities where data science and AI can be leveraged. Cross-team collaboration Working closely with other AI D pillars like AI Center, Data engineering and ML engineering and other groups Performing thorough data analysis, uncover opportunities and address business problems. Assertive and objective decision-making skills with the drive to deliver and arrive at solutions. Diagnosing business bottlenecks and provide prescriptive recommendations for stakeholders. What we are looking for You have excellent analytical skills, and are eager to work in a collaborative environment with global teams to drive data science applications for business problems, develop end-to-end analytical solutions and communicate insights and findings to leadership. You have strong expertise in VCG digital sales, Retail and in driving use cases that drive personalization. You are always willing to learn new technologies. You thrive in a dynamic environment and are able to interact with various stakeholders and cross functional teams to implement data science driven business solutions. You will need to have: Bachelors degree or Four or more years of work experience. Three or more years of experience practicing data science in business. Prior experience working in a Product team and having a product mindset. Extensive experience with AI solutioning in the Networks related areas like workforce optimization, reliability, Energy optimization etc. Strong communication, presentation and collaboration skills. Good Consumer knowledge and experience. Excellent analytical skills and use case prioritizations to build the roadmap at the product level in alignment with the business and stakeholders. Excellent knowledge on machine learning and predictive modeling. Experience in identifying business opportunities and build impactful data science driven use cases. Excellent problem solving and critical thinking capabilities. Experience using different statistical/modeling techniques. Excellent working knowledge of SQL for data analysis and EDA using Python. Ability to create compelling narratives and articulate insights through strong storytelling skills. Experience working in analytics projects. Even better if you have one or more of the following: Experience interacting and collaborating deeply with other lines of business the ability to work across cross cultural teams. Experienced with A/B and Multivariate testing, and should be able to provide recommendations accordingly. Expertise in performing thorough data analysis using database queries, spreadsheets, statistical packages tools, and communicate results effectively. Experience with dev-ops and agile models, as well as more traditional functional operating models. Ability to interact and provide executive level communications to senior management. Exposure to GenAI and Prompt engineering. Experience managing time-bound project deliverables for multiple stakeholders.