SUMMARY Job Opening: Gen AI Professional Location: Pan India Experience: 9-12 years Notice Period: Immediate to 90 days Job Description We are seeking a Gen AI Professional with 9 12 years of overall experience and a minimum of 5+ years of relevant experience in Gen AI. The ideal candidate should have a strong foundation in machine learning, deep learning, and computer science, along with expertise in generative AI models and techniques such as GANs, VAEs, and Transformers. Experience with natural language processing (NLP) and computer vision is a plus. The candidate should be able to work independently and as part of a team, with knowledge of advanced programming languages like Python and AI-centric libraries like TensorFlow, PyTorch, and Keras. Additionally, experience in data management, including data pre-processing, augmentation, and generation of synthetic data, as well as developing and deploying AI models in production environments, is required. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying, managing, and scaling AI solutions is also essential. The candidate should be able to bring new ideas and innovative solutions to our clients. Requirements Requirements: Bachelor's degree in Computer Science, Engineering, or related field. Proven experience in Gen AI, LSTM, BERT, GPT, Machine Learning, and Deep Learning. Strong proficiency in Python and AI-centric libraries like TensorFlow, PyTorch, and Keras. Familiarity with cloud services (AWS, Azure, GCP) and containerization technologies like Docker and Kubernetes. Excellent problem-solving and analytical skills. Strong communication and teamwork abilities.

About The Role : Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options c. Integrate model performance management tools into the current business infrastructure 3. Team Management a. Resourcing i. Support recruitment process to on-board right resources for the team b. Talent Management i. Support on boarding and training for the team members to enhance capability & effectiveness ii. Manage team attrition c. Performance Management i. Conduct timely performance reviews and provide constructive feedback to own direct reports ii. Be a role model to team for five habits iii. Ensure that the Performance Nxt is followed for the entire team d. Employee Satisfaction and Engagement i. Lead and drive engagement initiatives for the team Deliver No. Performance Parameter Measure 1. Demand generation Order booking 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management % trained on new skills, Team attrition %

Introduction We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA- as the world around us changes, so do we. Wipro empowers companies to transform their business and deliver superior experiences for their customers, partners and employees. With an entrepreneurial mindset and a sense of fun, we thoughtfully evaluate clients problems; craft innovative solutions that leverage cutting-edge technologies; and work side-by-side with clients to drive business outcomes. Enterprise Futuring is the largest global business line across Wipro, they offer our clients forward-looking solutions for large-scale enterprise transformation. They offer intelligent insights, enterprise data, application platforms, digital operations, and cybersecurity risk services. At Enterprise Futuring, the AI practice has deep industry knowledge, incredible passion, and strong customer relationships. Wipro stands firm as a leading partner in AI service innovation, creating impactful realizations of business potential. Through the development of robust, personalized solutions enhanced by the innovative power of AI technology, Wipro is committed to building transformative journeys for clients. Roles & Responsibilities Day-to-day technical responsibilities Design solutions and implement generative AI models and algorithms, utilizing state-of-the-art algorithms such as GPT, VAE, and GANs. Work on integrating cloud with GenAI algorithms like ChatGPT, Bedrock, Bard, PaLM etc. Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals. Research the latest advancements in generative AI, machine learning, and deep learning techniques, and identify opportunities to integrate them into our products and services. Optimize existing generative AI models for improved performance, scalability, and efficiency. Develop and maintain AI pipelines, including data pre-processing, feature extraction, model training, and evaluation. Drive the team to build GenAI products and solutions, working in an agile methodology Stakeholder Interaction & Management Work with internal teams and get relevant data/inputs for preparing documents such as RFP responses, capability demonstrations, client presentations and collaterals, participating in the customer calls to sell solutions etc. Collaborate with relevant stakeholders/teams to get feedback and make revisions to ensure that the proposal stays relevant to the needs throughout various proposal stages. Ensures communication among all parties throughout the proposal process Identifies bottlenecks in the process escalating accordingly to higher level, as necessary, to ensure timetable and deliverables remain on track Reach out to the below mentioned internal teams during proposal creation. Effective Project Management Effectively and efficiently plan, organize, lead and control the delivery of the final solution/proposal/document Prepare a work plan that lists the tasks required to create the proposal, such as design, writing, editing, review and production Uses strong interpersonal, organizational, and time management skills to juggle multiple tasks with differing deadlines to consistently produce the document Collaborate and influence internal key stakeholders to get relevant data within the specified timeline to ensure relevant data in plugged into the solution Ensure promptness and compliance of proposals by creating and managing proposal calendars, compliance checklists, compliance matrices, trackers, etc. Oversees collection and completion of all proposal components (technical, cost, management, annexes) working in collaboration with internal teams, as well as partners. Follow up with relevant stakeholders/teams to get feedback and revisions and ensure that the proposal development stays on schedule. Update the sales team and other stakeholders on a regular basis on the progress of the proposal Tech skills you will have You have solid experience over the last few years developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. You are proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras. Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure. Prompt engineering for GenAI algorithms Experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. Deployment of GenAI models Scrum/ Agile Why work at Wipro We pride ourselves on creating an inclusive workplace that provides equal opportunities to all persons regardless of their age, cultural background, sexual orientation, gender identity and expression, disability, veteran status, or anything else. If you only meet some of the requirements for this role, that's okay! We value a diverse range of backgrounds & ideas and believe this is fundamental for our future success. So, if you have the curiosity to learn and the willingness to teach what you know, we'd love to hear from you. Wipro has been globally recognized by several organizations for our commitment to sustainability, inclusion, and diversity. Social good is in our DNA, we believe in sustainability for the health of our planet, its inhabitants, and our business. For over 75 years we have operated as a purpose-driven company with an unwavering commitment to our customers and our communities. Energized by what we call the Spirit of Wipro, we commit ourselves to being a catalyst for change- working to build a more just, equitable and sustainable society. Around 66% of Wipros economic ownership is pledged towards philanthropic purposes. All of our employees are expected to embody Wipros 5-Habits for Success which are:Being Respectful, Being Responsive, Always Communicating, Demonstrate Stewardship, Building Trust.

9+ years experience in designing, developing and deploying production-grade machine learning solutions (supervised, unsupervised, reinforcement learning), deep learning framework (e.g. TensorFlow, PyTorch, Keras, etc) and NLP (NLTK, Spark NLP, spaCy, HuggingFace, Flair, NLTK, etc) for real-world business problems Experience with Open Source LLM and Langchain Framework Expertise in Python and SQL, with working experience in Apache Spark, Hadoop, Databricks, Snowflake, or other big data systems Development and ML experience in cloud platforms such as Microsoft Azure Combination of deep technical skills and business sense, to interface with all levels and disciplines within an organization. Excellent written and verbal communication skills to explain complex research to both technical and non-technical audiences Self-motivated individual that thrives in a dynamic environment

Skill :Python, Flask, ML/DL modeling, Agile Scrum, Project management Exp :5.5 to 9 Years. Location :chennai/ hyderabad/ bangalore/ coimbatore/ Pune NP :0 to 90 days.

Your future role Take on a new challenge and apply your refined expertise in a new cutting-edge field. You'll work alongside innovative, solution-oriented, and collaborative teammates. You'll design and implement complex generative AI solutions, contributing to the advancement of our AI/ML/DL/NLP platforms. Day-to-day, you'll work closely with teams across the business (data scientists, software engineers, project managers), managing a team of AI-ML engineers, and much more. You'll specifically take care of deploying generative AI models into scalable services, but also conduct cutting-edge research to keep our solutions at the forefront of the industry. We'll look to you for: Developing end-to-end architecture for scalable machine learning solutions Researching and developing advanced generative AI models Deploying AI models into REST API services Staying up-to-date with industry advancements Optimizing AI models for efficiency and scalability Collaborating on dataset curation for AI applications Improving AI model performance through experimentation All about you We value passion and attitude over experience. That's why we don't expect you to have every single skill. Instead, we've listed some that we think will help you succeed and grow in this role: Degree in Computer Science, Information Technology, EE, EEE, or related fields Experience or understanding of machine learning, recommendation systems, pattern recognition, NLP, data mining, or AI Knowledge of deep learning techniques and frameworks (TensorFlow, PyTorch) Familiarity with cloud platforms like Microsoft Azure A certification in a relevant field is a plus Strong programming skills, especially in Python Experience with CI/CD, Docker, and Kubernetes Things you'll enjoy Join us on a life-long transformative journey the rail industry is here to stay, so you can grow and develop new skills and experiences throughout your career. You'll also: Enjoy stability, challenges and a long-term career free from boring daily routines Work with cutting-edge security standards for rail signalling Collaborate with transverse teams and helpful colleagues Contribute to innovative projects that shape the future of mobility Utilise our dynamic and flexible working environment Steer your career in whatever direction you choose across functions and countries Benefit from our investment in your development, through award-winning learning opportunities Progress towards leadership and advanced technical roles Benefit from a fair and dynamic reward package that recognises your performance and potential, plus comprehensive and competitive social coverage (life, medical, pension) You don't need to be a train enthusiast to thrive with us. We guarantee that when you step onto one of our trains with your friends or family, you'll be proud. If you're up for the challenge, we'd love to hear from you!

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build whats next for their businesses. Your role Work with senior engineers and architects to implement end-to-end MLOps lifecycle projects. Contribute to building and testing ML pipelines, including data ingestion, model training, and deployment phases. Support the deployment, scaling, and monitoring of ML models in production environments. Collaborate with data scientists, data engineers, and other team members to ensure the successful implementation of MLOps processes. Engage in code reviews, testing, and quality assurance to ensure reliable model performance. Gain hands-on experience with Infrastructure-as-Code (IaC) and configuration management. Manage cloud resources (Azure, AWS, or GCP) and assist with cost-optimization strategies. Ensure compliance with best practices in DevOps/MLOps, including security and governance considerations. Assist with the implementation and support of LLM (Large Language Model) pipelines, including model fine-tuning, evaluation, and deployment in cloud and on-premises environments. Your Profile Basic understanding of data structures, data modeling, and software architecture. Experience with at least one ML framework (e.g., TensorFlow, Keras, or scikit-learn) and associated libraries (NumPy, Pandas, etc.). Familiarity with programming languages like Python and SQL, with exposure to version control (e.g., Git). Hands-on experience with cloud platforms (AWS, GCP, or Azure). Knowledge of CI/CD principles and DevOps practices for ML. Exposure to containerization tools such as Docker and orchestration tools like Kubernetes. Basic understanding of LLM concepts and NLP techniques. Familiarity with LLM frameworks such as Hugging Face Transformers or OpenAI API. What you will love about working here We recognize the significance of flexible work arrangements to provide support . Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build whats next for their businesses. Your Role Collaborate with MLOps Architect to implement the MLOps lifecycle project Understand key objectives and requirements of the MLOPs project and prioritizing to meet deliverable work Identify and evaluate the best tools and assemble the team of engineers and developers to work on it Apply problem solving approach to prototype and/or plan scaling in production Engage with Data scientist, Data engineers and others to set up end to end ML pipelines Build, Test, Deploy & Monitor ML pipelines Implement MLOps risk mitigation strategies and test validation MLOps patterns Apply responsible AI/ML Modeling approach to build AI solutions Your Profile MLOps Engineers/Architects who can design ML system, create data pipeline, build and deploy ML models on cloud as well as on-promises environment. Hands-on experience with ML frameworks, libraries, agile environments, and deploying machine learning solutions using DevOps principles Strong programming and coding languages such as Python, SQL, Java, C++, R, JavaScript , etc. Experience with machine learning frameworks, libraries and packages like Tensorflow, Keras, PyTorch, scikit-learn, NumPy, Pandas, etc. Good understand on the tools serving different purposes in the MLOps pipelines, including Continuous Integration servers, Configuration management, Deployment automation, Containers, Infrastructure Orchestration, Monitoring and analytics, Testing and Cloud Quality tools, as well as network protocols Strong experience with LLM frameworks and libraries, such as Hugging Face Transformers, LangChain, or OpenAI API. What you will love about working here We recognize the significance of flexible work arrangements to provide support . Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.

Responsibilities Develop modular, reusable components for internal AI projects , ensuring scalability and long-term usability. Collaborate with the team to manage tasks within a structured Agile framework , while ensuring priority tasks are addressed efficiently during each sprint. Balance a workload that includes both development and cross-team communication to ensure the progress of high-priority tasks. Ensure clear and effective communication with team members, particularly within project standups and ongoing task tracking. Take ownership of tasks while working within an established structure and manage changing priorities when necessary. Demonstrate a proactive approach in solving problems and propose innovative solutions to improve existing AI frameworks. Required education Bachelor's Degree Required technical and professional expertise 2+ years of relevant industry experience Proficiency in Python and experience in developing projects (either through college work, internships, or personal projects). Demonstrated innovation and creativity in AI-related projects or any technical domain. Foundational knowledge and interest in artificial intelligence and modern AI technologies (such as machine learning, deep learning, NLP, etc.). Ability to work in a collaborative, structured Agile environment and manage tasks within a sprint while maintaining flexibility for high-priority changes. Strong communication skills and an ability to work well with different teams to ensure project success and progress. Preferred technical and professional experience Familiarity with AI frameworks and libraries (such as TensorFlow , PyTorch , scikit-learn , etc.). Experience with version control systems like Git . Experience in Agile development processes, task management, and team communication.

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Communications & Media - AI & Data Architectures Title :- Ind & Func AI Value Strategy Sr Manager Job location :- Bangalore About S&C - Global Network:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU? Accenture has committed to invest USD 3Billion into GenAI in next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role AI Architecture strategy and Assessment: Lead the development and assessment of AI architectures, ensuring they align with business goals and objectives. Evaluate existing AI solutions, identifying areas for improvement, optimization, and innovation. Operating Model Design: Design robust operating models for Generative AI implementations, considering scalability, efficiency, and business impact. Collaborate with cross-functional teams to integrate AI capabilities seamlessly into existing operational workflows. Develop comprehensive blueprints for Generative AI solutions, outlining technical specifications, data requirements, and integration points. Ensure blueprints adhere to industry best practices and standards. Roadmap Building: Create strategic roadmaps for the implementation and evolution of Generative AI solutions. Define milestones, key performance indicators (KPIs), and success criteria to measure the progress of AI initiatives. Incubating GenAI Solutions: Identify emerging trends and technologies in Generative AI and incubate innovative solutions. Work closely with research and development teams to experiment and prototype new Generative AI concepts. Oversee the end-to-end implementation of Generative AI solutions, collaborating with engineering teams to ensure successful deployment. Provide technical leadership and guidance throughout the implementation lifecycle. Qualifications Who we are looking for? Bachelors or advanced degree in Computer Science, Artificial Intelligence, or a related field. 15+ years of hands-on experience in AI, with a focus on Generative AI. Proven track record of designing and implementing successful AI solutions in real-world business environments. In-depth knowledge of AI architectures, frameworks, and tools. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities, with experience working cross-functionally. Demonstrated leadership in driving AI initiatives from conception to deployment. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools & Techniques: Proficiency in Python programming language and key libraries like Pandas, TensorFlow, PyTorch, and Keras. Understanding and implemention knowledge of deep learning architectures such as CNNs, RNNs, and GANs. Good software engineering practices, including code modularization, documentation, and testing Familiarity with cloud platforms like AWS, Google Cloud, or Microsoft Azure can be beneficial for deploying and scaling GenAI models. If you are a visionary AI architect with a passion for innovation and a proven track record of delivering impactful Generative AI solutions, we invite you to apply and contribute to our dynamic and forward-thinking organization.

Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s)

Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Communications & Media - AI & Data Architectures Title :- Ind & Func AI Value Strategy Manager Job location :- Bangalore About S&C - Global Network:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU? Accenture has committed to invest USD 3Billion into GenAI in next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role AI Architecture Strategy and Assessment: Lead the development and assessment of AI architectures, ensuring they align with business goals and objectives. Evaluate existing AI solutions, identifying areas for improvement, optimization, and innovation. Operating Model Design: Design robust operating models for Generative AI implementations, considering scalability, efficiency, and business impact. Collaborate with cross-functional teams to integrate AI capabilities seamlessly into existing operational workflows. Develop comprehensive blueprints for Generative AI solutions, outlining technical specifications, data requirements, and integration points. Ensure blueprints adhere to industry best practices and standards. Roadmap Building: Create strategic roadmaps for the implementation and evolution of Generative AI solutions. Define milestones, key performance indicators (KPIs), and success criteria to measure the progress of AI initiatives. Incubating GenAI Solutions: Identify emerging trends and technologies in Generative AI and incubate innovative solutions. Work closely with research and development teams to experiment and prototype new Generative AI concepts. Oversee the end-to-end implementation of Generative AI solutions, collaborating with engineering teams to ensure successful deployment. Provide technical leadership and guidance throughout the implementation lifecycle. Qualifications Who we are looking for? Bachelors or advanced degree in Computer Science, Artificial Intelligence, or a related field. 15+ years of hands-on experience in AI, with a focus on Generative AI. Proven track record of designing and implementing successful AI solutions in real-world business environments. In-depth knowledge of AI architectures, frameworks, and tools. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities, with experience working cross-functionally. Demonstrated leadership in driving AI initiatives from conception to deployment. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools & Techniques: Proficiency in Python programming language and key libraries like Pandas, TensorFlow, PyTorch, and Keras. Understanding and implemention knowledge of deep learning architectures such as CNNs, RNNs, and GANs. Good software engineering practices, including code modularization, documentation, and testing Familiarity with cloud platforms like AWS, Google Cloud, or Microsoft Azure can be beneficial for deploying and scaling GenAI models. If you are a visionary AI architect with a passion for innovation and a proven track record of delivering impactful Generative AI solutions, we invite you to apply and contribute to our dynamic and forward-thinking organization. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

Entity :- Accenture Strategy Consulting Team :- Strategy Consulting Global Network Practice :- Communications Media - AI Data Architectures Title :- IF Decision Sci Practitioner Consultant Job location :- Bangalore, Hyderabad About SC - Global Network:- Accenture Strategy Consulting Global Network - Data AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT'S IN IT FOR YOU Accenture has committed to invest USD 3Billion into GenAI in the next 3 years. We will continually invest in your learning and growth. Youll work with Accenture's highly skilled and experienced practitioners, and Accenture will support you in growing your own career path and interests. You'll be part of a diverse, vibrant, global Accenture Data and AI community, continually pushing the boundaries of business capabilities. What you would do in this role ML Maturity Assessment: Conduct comprehensive assessments of the organizations ML maturity, identifying strengths, weaknesses, and areas for improvement. Provide strategic recommendations to enhance the overall ML capability and align it with business objectives. ML Ops Roadmap Processes: Develop ML Ops roadmaps and establish robust processes for the end-to-end machine learning lifecycle, including data preparation, model training, deployment, and monitoring. Implement best practices in ML Ops to ensure efficiency, scalability, and reliability of ML systems. Implementation of Gen AI Solutions: Lead the design and implementation of state-of-the-art Generative AI solutions, leveraging deep learning frameworks such as TensorFlow and PyTorch. Drive innovation in Gen AI, staying abreast of the latest advancements and incorporating cutting-edge technologies into solutions. Incubating and Designing: Proactively identify opportunities for ML and / or Gen AI applications within the organization. Work closely with cross-functional teams to incubate and design bespoke ML solutions tailored to business requirements. Technical Leadership: Provide technical leadership and mentorship to data scientists, engineers, and other team members. Collaborate with stakeholders to ensure alignment between technical solutions and business objectives. Collaboration and Communication: Collaborate with business stakeholders to understand their needs and translate them into ML and Gen AI requirements. Effectively communicate complex technical concepts to non-technical audiences. Qualifications Who we are looking for Bachelors or advanced degree in Computer Science, Data Science, or a related field. Over 8 years of hands-on experience in machine learning, with a focus on architecting end-to-end solutions. Proven expertise in conducting ML maturity assessments and developing ML Ops roadmaps. Hands-on experience in operationalizing the Machine learning system on a cloud and / or an On-Prem platform. Experience in implementing Generative AI solutions, including incubation, design, and deployment will be a big plus. Proficiency in deep learning frameworks such as TensorFlow and PyTorch. Good knowledge of ML Ops best practices and processes. Excellent problem-solving skills and ability to design scalable and reliable ML architectures. Strong leadership and communication skills, with a track record of leading successful ML initiatives. Experience in Telecom or Hi Tech or Software and platform industry desirable Tools Techniques: TensorFlow, PyTorch, Scikit-learn, Keras NumPy, Pandas Matplotlib, Seaborn TensorFlow Serving, Docker and Kubernetes Good software engineering practices, including code modularization, documentation, and testing. Experience with open API , Integration architecture , microservices If you are a visionary Machine Learning Architect with a passion for advancing ML maturity, implementing cutting-edge Gen AI solutions, and driving innovation, we invite you to apply and contribute to our organizations success. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

Core Job Responsibilities: Develop end-to-end ML pipelines encompassing the ML lifecycle from data ingestion, data transformation, model training, model validation, model serving, and model evaluation over time. Collaborate closely with AI scientists to accelerate productionization of ML algorithms. Setup CI/CD/CT pipelines for ML algorithms. Deploy models as a service both on-cloud and on-prem. Learn and apply new tools, technologies, and industry best practices. Key Qualifications MS in Computer Science, Software Engineering, or equivalent field Experience with Cloud Platforms, especially GCP and Azure, and related skills: Docker, Kubernetes, edge computing Familiarity with task orchestration tools such as MLflow, Kubeflow, Airflow, Vertex AI, Azure ML, etc. Fluency in at least one general purpose programming language. Python or Java preferred. Strong DevOps skills: Linux/Unix environment, testing, troubleshooting, automation, Git, , dependency management, and build tools (GCP Cloud Build, Jenkins, Gitlab CI/CD, Github Actions, etc.). Data engineering skills a plus, such as Beam, Spark, Pandas, SQL, Kafka, GCP Dataflow, etc. 3+ years of experience, including academic experience, in any of the above. Work Experience MS in Computer Science, Software Engineering, or equivalent field Experience with Cloud Platforms, especially GCP and Azure, and related skills: Docker, Kubernetes, edge computing Familiarity with task orchestration tools such as MLflow, Kubeflow, Airflow, Vertex AI, Azure ML, etc. Fluency in at least one general purpose programming language. Python or Java preferred. Strong DevOps skills: Linux/Unix environment, testing, troubleshooting, automation, Git, , dependency management, and build tools (GCP Cloud Build, Jenkins, Gitlab CI/CD, Github Actions, etc.). Data engineering skills a plus, such as Beam, Spark, Pandas, SQL, Kafka, GCP Dataflow, etc. 3+ years of experience, including academic experience, in any of the above. Role & responsibilities

As an Associate Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for: Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors Communicating with internal and external clients to understand and define business needs and appropriate modelling techniques to provide analytical solutions. Evaluating modelling results and communicating the results to technical and non-technical audiences. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides Preferred technical and professional experience Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms Experience and working knowledge in COBOL & JAVA would be preferred Experience in python and pyspark will be added advantage

Hiring for Gen AI Min exp 5yrs Loc:-Blr CTC:-20lpa For more details 9205018536(prabhsimer) prabhsimer.imaginators@gmail.com Required Candidate profile skills:- Proficiency in Python, Node.Js, C#, HTML, and JavaScript. Exp with AI Libraries/Packages such as TensorFlow, Keras, Pytorch,Generative AI frameworks.

2+ yrs exp in AI/ML, implementing & optimizing solutions using Deep Learning, NLP, Tensorflow, Keras, XGBoost, etc. Expertise in closed/open source LLMs (GPT 3.5/4/4 Turbo, LLAMA2, Falcon). Expert in Python. Deployed AI/ML as services on Cloud/K8s. Required Candidate profile Familiarity with development methodologies and writing Python unit tests. Preferred experience includes working with Open Source LLMs such as LLAMA2 and Falcon, with emphasis on fine-tuning.

2+ yrs exp in AI/ML, implementing & optimizing solutions using Deep Learning, NLP, Tensorflow, Keras, XGBoost, etc. Expertise in closed/open source LLMs (GPT 3.5/4/4 Turbo, LLAMA2, Falcon). Expert in Python. Deployed AI/ML as services on Cloud/K8s. Required Candidate profile Familiarity with development methodologies and writing Python unit tests. Preferred experience includes working with Open Source LLMs such as LLAMA2 and Falcon, with emphasis on fine-tuning.

AI Development and Implementation: Design, develop, and deploy cutting-edge AI solutions using GenAI technologies. Implement and optimize Large Language Models (LLMs) for natural language processing (NLP) applications. Leverage Retrieval-Augmented Generation (RAG) techniques to enhance AI-driven insights and decision-making. Requirements Quality Management: Integrate AI models with Requirements Management Software tool to ensure high-quality requirements management. Develop custom AI algorithms to automate requirement validation, improve quality, and detect inconsistencies. Solution Optimization and Integration: Fine-tune NLP models to align with domain-specific needs and improve accuracy. Collaborate with cross-functional teams to integrate AI solutions into enterprise workflows. Mentorship and Leadership: Mentor junior developers on AI best practices, tools, and frameworks. Lead brainstorming sessions to explore innovative AI applications and solutions. Research and Innovation: Stay updated with the latest advancements in AI, GenAI, LLMs, and RAG to continuously enhance systems. Conduct proof-of-concept projects to evaluate emerging technologies for business use cases. Required education Bachelor's Degree Required technical and professional expertise Programming Expertise: Proficient in Python with demonstrated experience in AI and ML development. GenAI and LLMs: Strong expertise in GenAI concepts, including the design, deployment, and optimization of Large Language Models (LLMs). NLP Skills: Advanced knowledge of NLP techniques for text analysis, summarization, and contextual understanding. RAG Expertise: Hands-on experience with Retrieval-Augmented Generation (RAG) to enhance knowledge retrieval systems. Tools and Frameworks: Proficiency with AI frameworks like TensorFlow, PyTorch, Hugging Face, or similar. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying AI solutions. Preferred technical and professional experience DevOps and MLOps: Knowledge of deploying AI models in production environments using MLOps best practices. Data Engineering: Familiarity with data preparation, preprocessing pipelines, and working with unstructured datasets. Agile Methodologies: Experience working in Agile development environments for iterative delivery. Soft Skills: Strong problem-solving skills, attention to detail, and ability to communicate complex concepts to technical and non-technical stakeholders.

Design, develop, and optimize applications using Python or Go with a focus on AI and ML-driven functionalities. Work with frameworks like Langchain, Langgraph, and Langsmith to build advanced language processing solutions. Implement and manage Kubernetes operators to support scalable, distributed systems. Develop and enhance Retrieval-Augmented Generation (RAG) workflows, including optimization for performance and accuracy. Research, design, and implement Machine Learning, Deep Learning, and Neural Network models to solve complex problems. Apply advanced techniques in Natural Language Processing (NLP) to enhance system capabilities. Collaborate with cross-functional teams to integrate AI/ML solutions into existing products and platforms. Stay updated on the latest trends in AI/ML and cloud-native technologies to ensure the use of best practices. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 2+ years of experience. Hands-on experience with Langchain, Langgraph, or Langsmith frameworks. Solid understanding of Kubernetes operators and their deployment. Strong expertise in Machine Learning, Deep Learning, and Neural Networks. Proficiency in Natural Language Processing (NLP) and related libraries. Knowledge of Retrieval-Augmented Generation (RAG) workflows and optimization techniques. Familiarity with cloud-native technologies and distributed systems. Excellent problem-solving skills, a collaborative mindset, and a passion for innovation. Preferred technical and professional experience Prior experience working in AI/ML model optimization or inference pipelines. Exposure to containerization tools such as Docker and orchestration platforms like Kubernetes. Familiarity with vector databases and hybrid search solutions.