About the Role We are looking for an AI Lead for our team of Data Scientists in Pune. This role will focus on leading the development, deployment, and monitoring of AI and machine learning solutions, including Generative AI (GenAI) technologies such as chatbots. The ideal candidate will have experience working in an onshore-offshore model, with a strong background in AI/ML development and operational best practices. This role requires close collaboration with the onshore AI Manager and cross-functional teams including AI Ops, ML Engineering, and Data Engineering. Key Responsibilities AI Model Development & Deployment: •Lead the offshore team in building, deploying, and managing AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems). •Collaborate with AI Engineers to integrate models into enterprise applications and workflows. •Support the implementation of CI/CD pipelines for efficient model deployment and scaling. Monitoring & Performance Optimization: •Develop monitoring systems to track model performance, latency, and drift. •Implement feedback loops for continuous model improvement in collaboration with data scientists. •Monitor GenAI outputs for issues like bias, hallucinations, and security vulnerabilities. MLOps & Automation Best Practices: •Establish MLOps practices to support continuous integration and deployment of AI models. •Automate model retraining, versioning, and rollback strategies. •Collaborate with AI Ops and Data Engineers to ensure smooth data and model pipelines. Security & Compliance: •Implement security measures to safeguard AI systems from data leaks, prompt injections, and unauthorized access. •Ensure AI solutions comply with relevant privacy and regulatory standards (e.g., HIPAA, GDPR). •Regularly audit AI pipelines for ethical practices and data governance. Collaboration & Communication: •Work closely with the onshore AI Manager and cross-functional teams to align AI initiatives with business goals. •Facilitate effective communication between onshore and offshore teams. •Contribute to documentation, playbooks, and best practices for AI operations. Team Leadership & Development: •Manage and mentor a team of data scientists, fostering professional growth and collaboration. •Encourage an innovative, problem-solving culture within the team. Qualifications & Skills Education: •Bachelors or Masters degree in Computer Science, Data Science, AI, or a related field. •Certifications in cloud platforms (Azure, AWS, GCP) or MLOps frameworks are a plus. Experience: •5 years of experience in Data Science, with 2+ years of experience leading AI/ML development and operations in onshore/offshore model. •Hands-on experience with deploying AI models, including LLMs and GenAI solutions. •Experience working with cloud AI platforms (Azure AI, AWS SageMaker, Google Vertex AI). Technical Skills: •Proficient in Python and SQL •Familiarity with MLOps tools like MLflow, Kubeflow, or Airflow. •Experience with monitoring tools (Prometheus, Grafana) for AI performance. •Knowledge of containerization and orchestration tools (Docker, Kubernetes). •Proficiency in scripting languages like Python or Bash. •Understanding of CI/CD pipelines (Jenkins, GitHub Actions) for model deployment. Soft Skills: •Strong problem-solving abilities and a proactive approach to troubleshooting. •Excellent collaboration skills with cross-functional teams. •Results-driven mindset with a focus on operational efficiency and scalability. •Ability to thrive in a fast-paced, dynamic environment.

AI/ML Engineer LLM PII Detection Department: Data Science / AI Engineering Role Overview We are seeking a skilled AI/ML Engineer to join our team focused on building and fine-tuning local LLM models for PII detection at scale (50+ PB of data). In this role, you will work closely with our AI Expert (Team Lead) to develop, deploy, and optimize state-of-the-art AI models that can detect Personally Identifiable Information (PII) across diverse data sources—including documents, databases, knowledge graphs, code, and more. Key Responsibilities Model Development: Assist in designing, training, and fine-tuning local LLM models for PII detection. Develop generative AI agents that utilize data schema and metadata to enhance PII detection process - reducing workload sizes with smart sampling. Framework Implementation: Utilize frameworks such as Ray, llama.cpp, ollama, vLLM, and PyTorch to build and scale AI models. Implement and support distributed computing frameworks to process and analyze large-scale datasets efficiently. Deployment & Optimization: Support the deployment of AI/ML solutions on both Azure and on-premise infrastructures. Monitor model performance, troubleshoot issues, and iterate to ensure optimal performance with evolving data. Collaboration: Work collaboratively with cross-functional teams—including data engineering, security, and compliance—to align AI solutions with business needs. Participate in code reviews, share insights, and document best practices to maintain high standards across projects. Continuous Improvement: Engage in ongoing learning and development of new AI methodologies. Contribute to the enhancement of model robustness and scalability, ensuring our systems handle 50+ PB of data reliably. Technical Proficiency: Hands-on experience with Python and ML frameworks (especially PyTorch). Familiarity with distributed computing tools such as Ray/Pyspark. Experience with LLM frameworks/tools such as llama.cpp, ollama, and vLLM. Data Handling: Ability to work with very large datasets and implement scalable, distributed solutions. Prior exposure to AI model development and fine-tuning for specialized tasks. Deployment Expertise: Experience deploying AI/ML models on Azure cloud platforms and/or on-premise environments. Communication & Collaboration: Strong communication skills to effectively collaborate with team members and cross-functional stakeholders. A proactive approach to problem-solving and a commitment to quality. Experience in PII detection, data privacy projects, or related fields. Basic understanding of data security and compliance frameworks. Familiarity with generative AI techniques and prompt engineering. Previous exposure to the fintech, payments, or security domains is a plus.

Role & responsibilities Develop, test, and maintain Al apps and machine learning models using Python. Create and maintain Al bots based on custom/ application APls. Implement data manipulation and analysis using libraries such as NumPy and Pandas Troubleshoot and debug Al applications and fine tune models. Participate in code reviews to ensure code quality and share knowledge with the team Stay updated with the latest advancements in Al and machine learning technologies. Ensure that solutions are scalable, maintainable, and meet the best practices for security, performance and data management Stay current with emerging technologies and trends in process automation and make Python Full Stack Developer recommendations for incorporating them into client solutions Collaborate, validate, and provide frequent updates to internal stakeholders throughout the project lifecycle Continuously research emerging technologies and determine credible solution Positively and constructively engage with clients and operations teams where required. Qualifications Experience in Azure. Proficiency in Python as the primary programming language. • Building LLM powered applications in a production environment. Knowledge of Python backend frameworks like Django or Flask, FastAPl etc. Knowledge of LLM internals and good knowledge of LLM ecosystem both private (Open Al, Gemini, Anthropic etc) and open source. Experience with version control systems like Git/ Github, Devops knowledge. Strong experience with NumPy and Pandas libraries for data manipulation and analysis. Solid understanding of machine learning principles and algorithms Preferred candidate profile • Experience with Langchain. • Knowledge of ReactJS(with Next & TypeScipt) Azure(deployment on webapps, Functions) • Familiarity with Hugging Face Transformers for natural language processing. • Experience in BPO Outsourcing/ IT outsourcing Qualifications • Bachelor's degree in Computer Science, Artificial Intelligence, Engineering, or a related field, or equivalent work experience. • 3-5 years of experience in Al, machine learning, and Python development. • Proven ability to work independently and as part of a team.

Role Summary The Project Manager is a results-driven and innovative project leader within DataForce. The Project Manager is responsible for leading successful execution of the life cycle of a range of AI-Data projects, through the utilization of expertise and technical skills to manage project budgets, timelines, and quality requirements. The Project Manager has accountability for fostering professional client relationships, managing and coordinating external vendors, and leading and collaborating with cross-functional project teams and partners. Role Responsibilities The Project Manager is ultimately responsible for the quality of work, profitability, and performance of their projects. Oversee all aspects of the management of projects from hand-off through project completion to ensure project success against defined KPIs Develop and maintain project plans, workflows, guidelines, and resource materials Provide effective analysis and reporting of project performance Track, monitor, and control project financial, timeline and quality performance Organize and deliver a Post Project Review Provide effective risk management through identification, escalation, mitigation, and effective resolution of issues Execute projects autonomously, while successfully coordinating with cross-functional project teams as required to procure required resources and support Serve as a primary point of contact for clients and both internal and external stakeholders Proactively identify opportunities, provide recommendations, and drive improvements to maximize operational efficiency and implement scalable solutions Establish, strengthen, and expand client relationships, support development of new business opportunities and overall profitable revenue growth Assist in the hiring process of new team members and train them Contribute to the development of the knowledge and capability of the department, team, colleagues in industry, and technology advancements. Complete all other tasks that are deemed appropriate for this role and assigned by the manager/supervisor Job requirements Role Requirements Knowledge, Skills and Abilities Solid understanding of data collection, annotation, and transcription activities, ideally in an AI setting Excellent leadership, interpersonal, and relationship-building skills Effective written and verbal communication skills Effective use of platforms/systems to plan, organize, and prioritize to ensure the successful completion of projects Established expertise in project management skills and methodologies Outstanding teamwork and collaboration skills Demonstrated exceptional analytical, critical-thinking, problem-solving and decision-making skills Established competency in the use of business applications and collaboration tools, including but not limited to the Microsoft suite of applications (Outlook, Excel, Word, PowerPoint, SharePoint, Teams) and Google Workspace suite of products Role Requirements Education and/or Experience Minimum Bachelors degree or its equivalent 5+ years relevant project management experience or experience in other roles with similar responsibilities Experience managing AI Machine Learning data-related projects, including speech, text and computer vision data collection, data curation and annotation projects Demonstrated success in end-to-end management of projects (total project lifecycle) Experience with project financials including proposals, RFPs, RFQs, MSAs, budgets, GM, quotes and SOWs Experience working with a high-performance, collaborative, and constructive peer group Ability to apply technology in solving business problems Experience managing information technology, data management, or similar technical projects AI industry experience Established expertise in applying PMI/PMP management principles, methods, and standards Business English language proficiency Preferred Role Requirements PMP or equivalent certification Experience working with support ticketing systems Experience managing projects with crowdsourcing and remote resourcing solutions Experience working in a multinational/multicultural virtual working environment Experience in working in a cross-functional/matrix organization Fluency in a language other than English language.

Role Summary The Project Manager is a results-driven and innovative project leader within DataForce. The Project Manager is responsible for leading successful execution of the life cycle of a range of AI-Data projects, through the utilization of expertise and technical skills to manage project budgets, timelines, and quality requirements. The Project Manager has accountability for fostering professional client relationships, managing and coordinating external vendors, and leading and collaborating with cross-functional project teams and partners. Role Responsibilities: The Project Manager is ultimately responsible for the quality of work, profitability, and performance of their projects. Oversee all aspects of the management of projects from hand-off through project completion to ensure project success against defined KPIs Develop and maintain project plans, workflows, guidelines, and resource materials Provide effective analysis and reporting of project performance Track, monitor, and control project financial, timeline and quality performance Organize and deliver a Post Project Review Provide effective risk management through identification, escalation, mitigation, and effective resolution of issues Execute projects autonomously, while successfully coordinating with cross-functional project teams as required to procure required resources and support Serve as a primary point of contact for clients and both internal and external stakeholders Proactively identify opportunities, provide recommendations, and drive improvements to maximize operational efficiency and implement scalable solutions Establish, strengthen, and expand client relationships, support development of new business opportunities and overall profitable revenue growth Assist in the hiring process of new team members and train them Contribute to the development of the knowledge and capability of the department, team, colleagues in industry, and technology advancements. Complete all other tasks that are deemed appropriate for this role and assigned by the manager/supervisor Role Requirements: Knowledge, Skills and Abilities Solid understanding of data collection, annotation, and transcription activities, ideally in an AI setting Excellent leadership, interpersonal, and relationship-building skills Effective written and verbal communication skills Effective use of platforms/systems to plan, organize, and prioritize to ensure the successful completion of projects Established expertise in project management skills and methodologies Outstanding teamwork and collaboration skills Demonstrated exceptional analytical, critical-thinking, problem-solving and decision-making skills Established competency in the use of business applications and collaboration tools, including but not limited to the Microsoft suite of applications (Outlook, Excel, Word, PowerPoint, SharePoint, Teams) and Google Workspace suite of products. Role Requirements: Education and/or Experience Minimum Bachelors degree or its equivalent 5+ years relevant project management experience or experience in other roles with similar responsibilities Experience managing AI Machine Learning data-related projects, including speech, text and computer vision data collection, data curation and annotation projects Demonstrated success in end-to-end management of projects (total project lifecycle) Experience with project financials including proposals, RFPs, RFQs, MSAs, budgets, GM, quotes and SOWs Experience working with a high-performance, collaborative, and constructive peer group Ability to apply technology in solving business problems Experience managing information technology, data management, or similar technical projects AI industry experience Established expertise in applying PMI/PMP management principles, methods, and standards Business English language proficiency Preferred Role Requirements PMP or equivalent certification Experience working with support ticketing systems Experience managing projects with crowdsourcing and remote resourcing solutions Experience working in a multinational/multicultural virtual working environment Experience in working in a cross-functional/matrix organization Fluency in a language other than English language.

Position -AIML Engineer Location - Pune Experience - 3 -6 Years Education : Degree in Computer Science or Electronics/ E&Tc or Mechatronics Roles & Responsibilit y - Experience : -Min. 3 years of experience with development in Computer vision, Machine Learning, Deep Learning and associated implementation of algorithms -Knowledge and experience in -Data Science/Data Analysis techniques -Hands on experience of programming in Python, R and MATLAB or Octave -Python Frameworks for AI such as TensorFlow, PySpark, Theano etc. & libraries like PyTorch, Pandas, Numpy, etc. -Algorithms such as Regression, SVM, Decision tree, KNN and Neural Networks Skills & Attribute s: -Fast learner and Problem solving -Innovative thinking -Excellent communication skills -Integrity, accountability and transparency -International working mindset If interested kindly share updated CV on poonam@hrworksindia.com OR Contact on 9209078944

Role: GCP Data Engineer Location: Bangalore Experience: 6-12 years Mode: work from office Job Description: We are seeking a talented GCP Data Engineer to join our team and help us design and implement robust data pipelines and analytics solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in BigQuery , DataFlow , Cloud Composer , and DataProc , along with experience in AI/ML tools such as Google Vertex AI or Dialogflow . Key Responsibilities: Design, develop, and maintain data pipelines and workflows using DataFlow , Cloud Composer , and DataProc . Develop optimized queries and manage large-scale datasets using BigQuery . Collaborate with cross-functional teams to gather requirements and translate business needs into scalable data solutions. Implement best practices for data engineering, including version control, CI/CD pipelines, and data governance. Work on AI/ML use cases, leveraging Google Vertex AI or Dialogflow to create intelligent solutions. Perform data transformations, aggregations, and ETL processes to prepare data for analytics and reporting. Monitor and troubleshoot data workflows to ensure reliability, scalability, and performance. Document technical processes and provide guidance to junior team members. Qualifications: Experience: 3-5+ years of professional experience in GCP data engineering or related fields. Skills: Proficiency in BigQuery , DataFlow , Cloud Composer , and DataProc . Exposure to Google Vertex AI , Dialogflow , or other AI/ML platforms. Strong programming skills in Python , SQL , and familiarity with Terraform for GCP infrastructure. Experience with distributed data processing frameworks like Apache Spark is a plus. Knowledge of data security, governance, and best practices for cloud platforms

About The Role : Title: Sales Ex COE - Client Success AI Apps Development Specialist Role (Job Profile):Analytics and Modeling Specialist Management Level:Specialist (ML9) About Accenture: We are: Sales Excellence. Sales Excellence at Accenture empowers our people to compete, win and grow. We provide everything they need to grow their client portfolios, optimize their deals and enable their sales talent, all driven by sales intelligence. The team will be aligned to the Client Success, which is a new function to support Accenture's approach to putting client value and client experience at the heart of everything we do to foster client love. Our ambition is that every client loves working with Accenture and believes we're the ideal partner to help them create and realize their vision for the future beyond their expectations. You are: An experienced AI Engineer with a flair for leveraging AI/ML for business innovation. You enjoy driving business innovation through the strategic implementation of cutting-edge technologies. You specialize in developing and deploying automation solutions using Azure, GCP enabling organizations to scale operations efficiently. Leveraging generative AI, you transform unstructured data into actionable insights, facilitating informed decision-making and positioning businesses at the forefront of technological advancement. The work: The Center of Excellence (COE) enables Sales Excellence to deliver best-in-class service offerings to Accenture leaders, practitioners, and sales teams. As a member of the COE Analytics Modeling Analysis team, you will generate business insights to help Accenture to improve its processes, boost sales and maximize profitability. You will build models and tools that help business leaders to automate and innovate business processes or operations leveraging GenAI. You will work closely with business to identify GenAI use cases and ML opportunities. You will also contribute to generating actionable insights and user-friendly solutions based on unstructured data. You will manage access to these tools and monitoring their usage. You will: Develop and implement AI solutions to address business challenges and enhance innovation. Design and deploy automation strategies to optimize operational efficiency. Assist with AI/ML predictive analytics using tools such as Python, nodejs. Utilize generative AI techniques to process and extract insights from unstructured data. Collaborate with cross-functional teams to integrate AI technologies into existing systems. Stay abreast of industry trends and emerging technologies to drive continuous improvement. Evaluate and test AI models, ensuring their effectiveness in delivering desired outcomes. Contribute to the scalability of operations through the application of advanced AI methodologies. Participate in the full AI development lifecycle, from concept to deployment. Collaborate with stakeholders to understand business requirements and align AI solutions with organizational goals. Continuously assess and refine AI models to adapt to evolving business needs. Here's what you need: Bachelor's degree or equivalent experience. At least 3 years of professional experience in AI/ML including: - Generative AI skills leveraging LLMs - Natural language processing techniques - Machine learning or deep learning algorithms - Hands-on expertise in coding Python and SQL. Strong communication skills in both oral and written English. Excellent time management and organizational skills. Proficiency in project management. Strong business acumen and attention to detail. Extra credit if you have: Master or doctoral degree in Computer Science or a similar field. Experience with survey data analysis using Qualtrics tools. Experience with Sales, Marketing, Pricing, or Finance data. Qualifications You may also need: A home office or work area that is suitable for productive remote work, per local guidelines. This includes a safe, ergonomic workspace and a high-speed internet connection that is stable and secure.

Gen AI Developers Generative AI - GPT3, ML Ops and Python(3+yrs) Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools Hybrid-Noida Immediate joiner Garima-8383973628 Garimaimaginators@gmail.com Required Candidate profile vector databases RDBMS, MongoDB and NoSQL databases

Dear Candidate, Please find below Job Description . Kindly share your resume on divya.grover@thethreeacross.com and whatsapp on 8448403677 Job Title: AI Engineer Experience: 5 to 10 years Location: Pune and Bangalore Job Overview: We are looking for a skilled AI Engineer with strong expertise in software engineering and data science to join our team. The ideal candidate will have experience in Python development, Docker, basic cloud technologies, and version control (GitHub). This role will offer the opportunity to contribute to innovative AI-driven solutions in a collaborative and dynamic environment. Key Responsibilities: Develop and implement machine learning and AI models to solve complex business problems. Design and build scalable and maintainable software solutions. Collaborate with cross-functional teams to gather requirements and deliver high-quality AI solutions. Create and optimize data pipelines to support AI/ML models. Write clean, efficient, and reusable Python code for AI model development. Leverage Docker for containerization of applications and deployment. Use version control systems like GitHub to maintain codebase integrity and collaborate with team members. Deploy AI models on cloud platforms (AWS, GCP, Azure) and ensure scalability and reliability. Troubleshoot and optimize AI models for performance improvements. Must-Have Skills: Basic Data Science : Knowledge of machine learning algorithms and techniques. Strong Software Engineering Skills : Ability to write high-quality, maintainable, and scalable software. Python Development : Proficiency in Python for AI/ML model development and deployment. Docker : Experience with Docker for containerization and deployment. Basic Cloud Knowledge : Familiarity with cloud platforms (AWS ) for hosting and scaling AI systems. GitHub : Proficiency in using GitHub for version control and collaboration. Good-to-Have Skills: Microsoft Stack : Familiarity with Microsoft technologies such as Azure, .NET, and other related tools. Qualifications: Bachelors or Master’s degree in Computer Science, Engineering, or related field. Regards Divya Grover

Fresher or 3+ years of experience in AI/ML development with a focus on Generative AI and LLMs. Design, develop, and implement AI/ML models, including Generative AI and LLM-based solutions.

Message to applicants applying to work in the U.S. and/or Canada: When available, the salary range posted for this position reflects the projected hiring range for new hire, full-time salaries in U.S. and/or Canada locations, not including equity or benefits. For non-sales roles the hiring ranges reflect base salary only; employees are also eligible to receive annual bonuses. Hiring ranges for sales positions include base and incentive compensation target. Individual pay is determined by the candidates hiring location and additional factors, including but not limited to skillset, experience, and relevant education, certifications, or training. Applicants may not be eligible for the full salary range based on their U.S. or Canada hiring location. The recruiter can share more details about compensation for the role in your location during the hiring process. U.S. employees have access to quality medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, short and long-term disability coverage, basic life insurance and numerous wellbeing offerings. Employees receive up to twelve paid holidays per calendar year, which includes one floating holiday (for non-exempt employees), plus a day off for their birthday. Non-Exempt new hires accrue up to 16 days of vacation time off each year, at a rate of 4.92 hours per pay period. Exempt new hires participate in Cisco s flexible Vacation Time Off policy, which does not place a defined limit on how much vacation time eligible employees may use, but is subject to availability and some business limitations. All new hires are eligible for Sick Time Off subject to Cisco s Sick Time Off Policy and will have eighty (80) hours of sick time off provided on their hire date and on January 1st of each year thereafter. Up to 80 hours of unused sick time will be carried forward from one calendar year to the next such that the maximum number of sick time hours an employee may have available is 160 hours. Employees in Illinois have a unique time off program designed specifically with local requirements in mind. All employees also have access to paid time away to deal with critical or emergency issues. We offer additional paid time to volunteer and give back to the community. Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components. For quota-based incentive pay, Cisco typically pays as follows: .75% of incentive target for each 1% of revenue attainment up to 50% of quota;

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Job function: Device Drivers development & support For this role we are seeking a talented and motivated Software Engineer with expertise in operating systems, android frameworks and linux kernel. The candidate will have opportunities to work on wide range of features across the Android Stack and Linux kernel. Develop end to end solutions involving both user space and kernel space with optimal resource usage adhering to Android framework, Linux system & kernel programing principles. Collaborate with systems, multimedia, architecture, and other teams to develop system-level Skills/experience: Experience level "“ 8 to 13 Good understanding of microprocessor, multiprocessor architecture. ARM, DSP, etc Good understanding of basic real-time/embedded programming concepts & real time operating systems concepts Hands on experience with Android Application Framework, Android native daemons/services, AIDL HALs Hands on experience with system programming on any Linux/Unix OS Hands on experience in debugging with T32, gdb and crash analysis using android tombstones, T32, crash utility etc., Experience in Git, Android Make, Android Tools, Android Studio, Adb. Experience in developing linux kernel drivers & modifying kernel code is a plus Knowledge on usage of AI models, familiarity with python for AI/ML related software development is a plus Drivers development/support on USB, Storage, I2C,SPI,Slimbus, etc Good understanding and proficiency in C and assembly Experience in using debugging tools like Lauterbach and Trace tools. Ability to analyze, triage and debug complex system level problems and issues Good analytical and problem solving skills Good communication skills Excellent knowledge of OS fundamentals, data structure, Linux kernel and the device driver model Minimum Qualifications: "¢ Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. "¢ 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

About The Role : As a Director in Data Advisory, you are responsible for defining and executing data advisory engagements for clients. Your role focused on Building, selling and delivering Data based solutions and Invents data capabilities. As a data advisory practitioner, you should have a point of view and understanding of build vs. buy, performance considerations, hosting, Data Lake, Data Mesh, reporting & analytics. Additional Responsibilities Include: Demonstrate the ability to hold strategic CXO conversations, ability to sell Capgemini Invents data capabilities to internal and external customers. Build and nurture a high-performing data advisory team, fostering growth and skill development Lead the development and execution of data strategy roadmaps and architectural design for clients, ensuring alignment with business objectives Manage and provide technical leadership to large data programs or multiple programs implementation based on the requirement using agile technologies Drive revenue growth by identifying, proposing, and winning new data advisory opportunities across key accounts. Create data-based assets and enable asset-based selling Stay updated with the latest technologies to incorporate innovative tools and methodologies into architectural designs Primary Skills Bachelors/Masters Degree in Computer Engineering, Computer Science, or a related field. 16+ years of Experience in leading and delivering large-scale data solutions, managing enterprise-level projects, and overseeing technical and advisory teams. Proficiency in at least 2 cloud technologies AWS, Azure, GCP, with extensive experience deploying AI-driven solutions at scale. Hands-on experience in creating data warehouse, Data lakes, ETL/ELT, Data pipelines, and reporting/analytic tools and environment Good knowledge in in Gen AI area and how data can support the advent of GenAI Proven experience in deploying cloud solutions at scale, with expertise in architecting, designing, and delivering AI-powered data solutions for large-scale projects. 5+ years of Hands-on Expertise in building and managing data advisory practices, with a strong focus on Cloud, AI/ML, data modeling, Data ops, and Datalake. Deep Expertise in one of the sectors like Life Sciences, CPR, Auto or Manufacturing Secondary Skills Strong customer orientation, decision making, problem solving, communication and presentation skills Very good collaboration skills and ability to interact with multi-cultural and multi-functional teams spread across geographies

Conduct live online training Update training materials with industry trends Create practical exercises & projects Adapt teaching methods for all learning levels

Must have skills: Generative AI - GPT3, ML Ops and Python Proficient in Python, with experience in machine learning, deep learning, and NLP processing. Experience in developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs. Proficient in Langchain, LLM Prompt Engineering: The engineer prompts and optimizes few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations. Model Evaluation & Optimization: Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration. Response Quality: Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app. It is essential to have a solid understanding of data structures, algorithms, and principles of software engineering. Experience with vector databases RDBMS, MongoDB and NoSQL databases. Proficiency in working with embeddings. Strong distributed systems skills and system architecture skills Experienced in building and running a large platform at scale. Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark, or similar statistical tools. Experience as data modeling ML/NLP scientist. including, but not limited to, Performance tuning, fine-tuning, RLHF, and performance optimization. Validated background with ML toolkits, such as PyTorch, TensorFlow, Keras, Langchain, Llamadindex, SparkML, or Databricks. Proficient with the integration of data from multiple data sources Experience with NoSQL databases, such as HBase, ElasticSearch, and MongoDB API Design. API/Data mapping to schema. Experienced in and strong knowledge of using AI/ML and more particularly LLMs eager to apply this rapidly changing technology. Good Knowledge of Kubernetes, and RESTful design. Prior experience in developing public cloud services or open-source ML software is an advantage

Urgent Requirement Position - AI/ML Developer Location - Noida Sector- 62, C51, Near - Sector 59 Metro Station Company - Mckinsol Technologies Timing - 7:00PM to 4:00AM ( U.S Shift ) Roles and Responsibilities Design, develop, test, and deploy AI/ML models using Python and SQL scripting languages. Collaborate with cross-functional teams to integrate ML solutions into existing systems. Troubleshoot issues related to data quality, model performance, and system integration. Develop scalable data pipelines using AWS services such as S3, Lambda, Step Functions. Ensure compliance with security standards by implementing secure coding practices. Desired Candidate Profile 1-5 years of experience in developing AI/ML models or similar roles. Strong proficiency in Python programming language with expertise in machine learning libraries like scikit-learn or TensorFlow. Familiarity with cloud computing platforms (AWS) for deploying applications. Experience working with relational databases (SQL) for data storage and retrieval.

Job Description We are seeking a skilled Generative AI Engineer with a strong background in Python to join our dynamic team. In this role, you will integrate backend development expertise with the latest advancements in AI to create impactful solutions. If you excel in a fast-paced environment and enjoy tackling complex challenges, we encourage you to apply. Key Responsibilities: Generative AI Development Develop and implement generative AI models using frameworks like LangChain or Llama-Index. Apply prompt engineering techniques to design effective queries and ensure optimal LLM responses for diverse use cases. Master advanced LLM functionalities, including prompt optimization, hyperparameter tuning, and response caching. Implement Retrieval-Augmented Generation (RAG) workows by integrating vector databases like Pinecone, Weaviate, Supabase, or PGVector for ecient similarity searches. Work with embeddings and build solutions that leverage similarity search for personalized query resolution. Explore and process multimodal data, including image and video understanding and generation. Integrate observability tools for monitoring and evaluating LLM performance to ensure system reliability. Backend Engineering Build and maintain scalable backend systems using Python frameworks such as FastAPI, Django, or Flask. Design and implement RESTful APIs for seamless communication between systems and services. Optimize database performance with relational databases (PostgreSQL, MySQL) and integrate vector databases (Pinecone, PGVector, Weaviate, Supabase) for advanced AI workows. Implement asynchronous programming and adhere to clean code principles for maintainable, high-quality code. Seamlessly integrate third-party SDKs and APIs, ensuring robust interoperability with external systems. Develop backend pipelines for handling multimodal data processing, and supporting text, image, and video workows. Manage and schedule background tasks with tools like Celery, cron jobs, or equivalent job queuing systems. Leverage containerization tools such as Docker for ecient and reproducible deployments. Ensure security and scalability of backend systems with adherence to industry best practices. Qualications: Essential : Strong Programming Skills: Prociency in Python and experience with backend frameworks like FastAPI, Django, or Flask. Generative AI Expertise: Knowledge of frameworks like LangChain, Llama-Index, or similar tools, with experience in prompt engineering and Retrieval-Augmented Generation (RAG). Data Management: Hands-on experience with relational databases (PostgreSQL, MySQL) and vector databases (Pinecone, Weaviate, Supabase, PGVector) for embeddings and similarity search. Machine Learning Knowledge: Familiarity with LLMs, embeddings, and multimodal AI applications involving text, images, or video. Deployment Experience: Prociency in deploying AI models in production environments using Docker and managing pipelines for scalability and reliability. Testing and Debugging: Strong skills in writing and managing unit and integration tests (e.g., Pytest), along with application debugging and performance optimization. Asynchronous Programming: Understanding of asynchronous programming concepts for handling concurrent tasks eciently. Preferred: Cloud Prociency: Familiarity with platforms like AWS, GCP, or Azure, including serverless applications and VM setups. Frontend Basics: Understanding of HTML, CSS, and optionally JavaScript frameworks like Angular or React for better collaboration with frontend teams. Observability and Monitoring: Experience with observability tools to track and evaluate LLM performance in real-time. Cutting-Edge Tech: Awareness of trends in generative AI, including multimodal AI applications and advanced agentic workows. Security Practices: Knowledge of secure coding practices and backend system hardening. Certications: Relevant certications in AI, machine learning, or cloud technologies are a plus.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior AIML Engineer Experience : 6+ Yrs Location: Pune Skillsets- AIML , Gen AI, MLOps, AWS, Python, ML(Machine Learning), Data Science , SQL,AWS Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. The Role: As our Tech Lead in AI/ML, you will play a crucial role in the hands-on development of mentoring peers and delivery of AI products powered by our internal AI models and machine learning pipelines. You'll identify new opportunities for AI solutions throughout the organization, and set the direction and roadmap required to implement MLOPS. You will partner with the team through the creation of AI models, and develop, and deploy LLM-based applications in production, evaluating and improving their performance and accuracy over time. Collaborating closely with Product, Research, and Engineering teams, youll ensure seamless integration of AI technologies into our products, setting new standards for data quality and model performance. Responsibilities: Design, develop, and maintain a AI/ML platform that is accurate, secure, and fast Lead workstreams within a lean and agile environment from requirements gathering to creating a plan of actionable tasks for the team Provide coaching, and mentorship to members of the data team on architecture, software development best practices, and new technologies Establish evaluation criteria for data quality tracking and production ML model tracking Partner with product, research, and engineering to ensure product changes integrate effectively . Required Qualifications: 6+ years in MLOps, ML engineering, MLOps, and data science with 2+ years leading and mentoring agile teams. Proven expertise in deploying essential MLOps components like CI/CD, model registry, and input loading. Skilled in creating and launching diverse models (statistical, LLM, GenAI, GPT 3.5/4.0) from POC to production. Proven ability to manage projects and programs, leading small teams (2-5 members) and directly handling data analysis, modeling, data pipeline setup, and MLOps Skilled in AIML, using platforms like AWS, Amazon Bedrock, and Snowflake, and proficient in Python, SQL, Tableau, and Alteryx 3+ years of experience working with Jupyter Notebooks, Git, GitHub, JIRA, and weights & biases, enhancing collaboration and version control in project development. Significant collaboration with research teams, contributing hands-on research skills that advance project outcomes. Preferred Qualifications: 2+ years of Tech Lead and management experience; taking on role as player coach and providing mentorship. Experience migrating data sets and workflows between legacy data platforms and services. Familiarity with stream processing and event driven architecture Comfortable moving quickly and working in a fast-paced, agile XP, lean environment. Experience in leading offshore and nearshore teams is highly valued.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior AIML Engineer Experience : 6+ Yrs Location: Pune Skillsets- AIML , Gen AI, MLOps, AWS, Python, ML(Machine Learning), Data Science , SQL,AWS Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. The Role: As our Tech Lead in AI/ML, you will play a crucial role in the hands-on development of mentoring peers and delivery of AI products powered by our internal AI models and machine learning pipelines. You'll identify new opportunities for AI solutions throughout the organization, and set the direction and roadmap required to implement MLOPS. You will partner with the team through the creation of AI models, and develop, and deploy LLM-based applications in production, evaluating and improving their performance and accuracy over time. Collaborating closely with Product, Research, and Engineering teams, youll ensure seamless integration of AI technologies into our products, setting new standards for data quality and model performance. Responsibilities: Design, develop, and maintain a AI/ML platform that is accurate, secure, and fast Lead workstreams within a lean and agile environment from requirements gathering to creating a plan of actionable tasks for the team Provide coaching, and mentorship to members of the data team on architecture, software development best practices, and new technologies Establish evaluation criteria for data quality tracking and production ML model tracking Partner with product, research, and engineering to ensure product changes integrate effectively . Required Qualifications: 6+ years in MLOps, ML engineering, MLOps, and data science with 2+ years leading and mentoring agile teams. Proven expertise in deploying essential MLOps components like CI/CD, model registry, and input loading. Skilled in creating and launching diverse models (statistical, LLM, GenAI, GPT 3.5/4.0) from POC to production. Proven ability to manage projects and programs, leading small teams (2-5 members) and directly handling data analysis, modeling, data pipeline setup, and MLOps Skilled in AIML, using platforms like AWS, Amazon Bedrock, and Snowflake, and proficient in Python, SQL, Tableau, and Alteryx 3+ years of experience working with Jupyter Notebooks, Git, GitHub, JIRA, and weights & biases, enhancing collaboration and version control in project development. Significant collaboration with research teams, contributing hands-on research skills that advance project outcomes. Preferred Qualifications: 2+ years of Tech Lead and management experience; taking on role as player coach and providing mentorship. Experience migrating data sets and workflows between legacy data platforms and services. Familiarity with stream processing and event driven architecture Comfortable moving quickly and working in a fast-paced, agile XP, lean environment. Experience in leading offshore and nearshore teams is highly valued.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: AI Operations (AI Ops) Engineer Experience : 8+ Yrs Location: Pune, Hyderabad, Gurugram Skillsets- Azure, Gen AI, MLOps, Python, ML(Machine Learning), Data Science , SQL Job Summary: AI Operations (AI Ops) Engineer AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Key Responsibilities: Technical Operations: Review, Implement and support enterprise-level AI platforms and services to drive IT operation excellence. Ensuring that new use cases are onboarded smoothly and operationalized Optimization: Analyze business processes to identify areas for automation and work with business stakeholders and IT teams to determine requirements and design software bots to reduce operational toil. AI Ops & Model Deployment: Lead the operationalization and deployment of AI/ML models into production environments, ensuring they are highly available, scalable, and performant. Implement and monitor Continuous Integration (CI) and Continuous Deployment (CD) pipelines. Python Development: Design and develop Python-based solutions for automating and managing the lifecycle of AI/ML models, including data ingestion, model training, and real-time prediction workflows. API Integration: Build and maintain robust APIs for model serving and integration with other systems. Ensure seamless communication between models, data pipelines, and consumer applications. LLM Concepts and Implementation: Apply knowledge of Large Language Models (LLMs) to develop AI-driven applications and services, ensuring models are optimized and performing efficiently in production. ML Ops: Implement and maintain Machine Learning Operations (ML Ops) practices for version control, monitoring, logging, and debugging of AI/ML models in production. Support model retraining, versioning, and A/B testing. Cloud Infrastructure: Leverage Azure Cloud services for hosting and scaling AI applications, ensuring security, compliance, and performance. Implement infrastructure as code (IaC) using tools like Azure DevOps. Collaboration: Work closely with backend engineers, data engineers/developers, infrastructure engineers , operational SMEs and business stakeholders to tackle evolving challenges in the field of AI/ML to ensure AI solutions meet business requirements and performance benchmarks. Monitoring & Optimization: Continuously monitor the performance of deployed AI models and optimize them for efficiency, cost-effectiveness, and accuracy. Implement alerting and logging mechanisms by scripts or through observability solution. Documentation & Best Practices: Document AI Ops processes, Use cases, tools, and workflows. Establish and enforce best practices for managing AI models in production environments. Required Skills & Qualifications:(Python Developer + ML-Engineer + MLOPS+ Azure) Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. -Data ScienePython: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. MLOPS Engineer APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. Data Science LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Data Engineer Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. DE Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: AI Operations (AI Ops) Engineer Experience : 8+ Yrs Location: Pune, Hyderabad, Gurugram Skillsets- Azure, Gen AI, MLOps, Python, ML(Machine Learning), Data Science , SQL Job Summary: AI Operations (AI Ops) Engineer AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Key Responsibilities: Technical Operations: Review, Implement and support enterprise-level AI platforms and services to drive IT operation excellence. Ensuring that new use cases are onboarded smoothly and operationalized Optimization: Analyze business processes to identify areas for automation and work with business stakeholders and IT teams to determine requirements and design software bots to reduce operational toil. AI Ops & Model Deployment: Lead the operationalization and deployment of AI/ML models into production environments, ensuring they are highly available, scalable, and performant. Implement and monitor Continuous Integration (CI) and Continuous Deployment (CD) pipelines. Python Development: Design and develop Python-based solutions for automating and managing the lifecycle of AI/ML models, including data ingestion, model training, and real-time prediction workflows. API Integration: Build and maintain robust APIs for model serving and integration with other systems. Ensure seamless communication between models, data pipelines, and consumer applications. LLM Concepts and Implementation: Apply knowledge of Large Language Models (LLMs) to develop AI-driven applications and services, ensuring models are optimized and performing efficiently in production. ML Ops: Implement and maintain Machine Learning Operations (ML Ops) practices for version control, monitoring, logging, and debugging of AI/ML models in production. Support model retraining, versioning, and A/B testing. Cloud Infrastructure: Leverage Azure Cloud services for hosting and scaling AI applications, ensuring security, compliance, and performance. Implement infrastructure as code (IaC) using tools like Azure DevOps. Collaboration: Work closely with backend engineers, data engineers/developers, infrastructure engineers , operational SMEs and business stakeholders to tackle evolving challenges in the field of AI/ML to ensure AI solutions meet business requirements and performance benchmarks. Monitoring & Optimization: Continuously monitor the performance of deployed AI models and optimize them for efficiency, cost-effectiveness, and accuracy. Implement alerting and logging mechanisms by scripts or through observability solution. Documentation & Best Practices: Document AI Ops processes, Use cases, tools, and workflows. Establish and enforce best practices for managing AI models in production environments. Required Skills & Qualifications:(Python Developer + ML-Engineer + MLOPS+ Azure) Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. -Data ScienePython: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. MLOPS Engineer APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. Data Science LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Data Engineer Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. DE Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred.

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 Generative AI System Design:Architect and implement advanced generative AI models, focusing on applications such as image and text generation, content creation, and synthetic data generation. Model Development and Optimization:Develop, fine-tune, and optimize generative AI models, ensuring they meet performance, scalability, and business objectives. AI/ML Integration:Apply solid data science principles to enhance AI/ML models, using statistical analysis and machine learning techniques to improve model accuracy and efficiency. Cross-functional Collaboration:Work closely with data engineers, software developers, and product managers to integrate generative AI models into products and services, aligning with business objectives. Innovation Leadership:Stay at the forefront of AI/ML and generative AI advancements, driving the adoption of new technologies and best practices within the team. Ethical AI Implementation:Ensure that AI models are designed and deployed with ethical considerations, adhering to industry standards and regulatory requirements Your Profile Education & Experience:bachelors or masters degree in computer science, AI, Machine Learning, Data Science, or a related field, with 5+ years of experience in AI/ML, particularly with generative AI models. Technical Skills:Strong expertise in developing and deploying generative AI models. Proficiency in Python and experience with AI development libraries such as TensorFlow and PyTorch. Experience with Azure OpenAI, Open Source LLMs, and LangChain. Data Science Expertise:Solid experience in applying data science principles, including statistical analysis, data preprocessing, and machine learning, to enhance AI/ML models. Techniques/Approaches:Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and zero-shot learning. Domain Knowledge:Familiarity with NLP or computer vision related to generative AI applications. 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.Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

Role: Senior Manager Exp: 14+ years Budget: 35LPA Location: Bangalore Must Have: Fincrime (KYC, AML, Fraud), Presales, Transformation. Good to Have: RPA, AI, ML, etc Notice Period: Immediate to 30 Days.

Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : Python (Programming Language) Good to have skills : AWS Comprehend Minimum 2 year(s) of experience is required Educational Qualification : BE coding python programming Job Requirements :Key Responsibilities :A Designing, developing, and researching Machine Learning systems, models, and schemes through data science B data analytics prototypes Understanding of Natural Language ProcessingNLP, C Natural Language Understanding NLU and Natural Language Generation NLG Technical Experience :A Python, Pandas,scikit-learn, Tenserflow,pytorch,matplotlib,NLTK B Amazon SageMaker, Amazon Transcribe, Amazon Comprehend, Machine Learning C Lex, Amazon Kendratranscribe, AIML Linguistic, Amazon Bedrock AWS CloudFormation, AWS IAM,Amazon CloudWatch, AWS AppSync API, AWS Lambda Professional & Technical Skills: Must To Have Skills:Proficiency in Python. Good To Have Skills:Experience with AWS Comprehend and Amazon SageMaker. Experience in designing, building, and configuring applications to meet business process and application requirements. Solid grasp of data visualization tools. Strong understanding of software engineering principles. Experience with agile development methodologies.Professional Attributes :1:Excellent verbal and written communications skill 2:Problem Solving ability 3:Willingness to work within a team and prepare to accept delegated workEducational Qualification:Bachelor of Engineering, MCA Qualification BE coding python programming