802 Neural Networks Jobs - Page 21

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Dear Candidate, We are seeking an AI Software Developer to design and implement intelligent applications using machine learning, deep learning, and natural language processing. Key Responsibilities: Build, train, and deploy AI/ML models for real-world applications. Collaborate with data scientists to convert models into production-ready APIs. Optimize models for performance, scalability, and latency. Integrate AI capabilities into enterprise systems or consumer products. Monitor model performance and update based on new data. Required Skills & Qualifications: Proficiency in Python and frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with AI/ML deployment (e.g., Docker, FastAPI, AWS SageMaker). Knowledge of computer vision, NLP, or recommendation systems. Familiarity with MLOps practices and version control for models. Strong problem-solving and data structure knowledge. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

We, at the LVPEI Center for Innovation, have developed a variety of screening and diagnostic devices Precision imaging systems are crucial components of these devices and the visual information captured here helps the clinician / examiner to decide the status of the eye health To auto-detect and quantify various pathologies of eye we adopt Computer Vision and Machine Learning techniques These developments will help the innovation center to build automated disease detection systems and there by enhance quality of eye care This role gives the candidate an opportunity to work on unique data sets and explore various image processing algorithms and deep learning (algorithms & frameworks) This role majorly involves in organizing data for further analysis, making the models scalable and light-weight to implement them offline on mobile phone platforms Responsibilities Work on translating the computer vision research to its applications in screening and diagnosing eye pathologies. Create novel methods to annotate and organize the patient data for further analysis. Keep UpToDate with the rapid developments in Computer vision and deep learning Incorporate improvements to the model / algorithms design and architecture, leading to increased accuracy in pathology identification. Collaborate with interns at the center to Fastrack the development process. Conceptualize a development task, its dependencies and map out work flows for an assigned project Best practices of software documentation and maintian development logs. Required Skills First-hand experience in working with open source neural networks like ResNet /MobileNet /Inception. Experience of working with at least one among PyTorch / TensorFlow / Keras / MXNet / Theano Strong background in Data Science, data structures, statistics, algorithms like Regression, Classification Sound understanding in the areas of Computer Vision / Pattern Recognition / Image Processing. Online certifications will be an added advantage.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

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) DevelopmentDevelop 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

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Good to have skills : NAMinimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions, ensuring that they meet quality standards. You will work with various AI models, including generative AI, deep learning, and neural networks, while also exploring innovative applications such as chatbots and image processing. Collaboration with cross-functional teams will be essential as you contribute to the overall success of projects and drive advancements in AI technology. Roles & Responsibilities:- Expected to be a Subject Matter Expert with deep knowledge and experience.- Should have influencing and advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Facilitate knowledge sharing sessions to enhance team capabilities and understanding of AI technologies.- Mentor junior professionals to foster their growth and development in AI and machine learning. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning.- Experience with cloud-based AI services and deployment strategies.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Familiarity with data preprocessing and feature engineering techniques.- Ability to design and implement neural networks for various applications. Additional Information:- The candidate should have minimum 15 years of experience in Machine Learning.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions, ensuring that they meet quality standards. You will work with generative AI models and may also explore various advanced technologies such as deep learning, neural networks, chatbots, and image processing to enhance the functionality and efficiency of the systems you create. Collaboration with cross-functional teams will be essential to ensure that the solutions are robust and scalable, addressing the needs of diverse stakeholders. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Facilitate knowledge sharing and mentoring within the team to enhance overall performance.- Continuously evaluate and improve existing processes and systems to drive efficiency and innovation. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Experience with cloud-based AI services and deployment strategies.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Familiarity with natural language processing techniques and tools.- Ability to design and implement scalable AI solutions that meet production standards. Additional Information:- The candidate should have minimum 12 years of experience in Large Language Models.- This position is based at our Kolkata office.- A 15 years full time education is required. Qualification 15 years full time education

Job Title - S&C Global Network - AI - CMT ML Ops - Manager Management Level:7- Manager Location:Open Must-have skills: AI Architecture/ Gen AI Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. 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. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. 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. Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 8+ years Educational Qualification: Btech/ BE

Job Title - S&C Global Network - AI - CMT AI Architecture - Sr Manager Management Level:6-Senior Manager Location:Open Must-have skills: AI Architecture/ Gen AI Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. 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. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. 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. Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 12+ years Educational Qualification: Btech/ BE

Management Level :07- I&F Decision Sci Practitioner Manager Location :Mumbai Must-have skills :Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, QlikView, PowerBI, SAS VA, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills :Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled I&F Decision Sci Practitioner Manager to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for leading risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role also provides opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Lead the team in the development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for clients. Manage workstreams for large and small projects, overseeing the quality of deliverables for junior team members. Develop and frame Proof of Concept for key clients where applicable. Practice Enablement Mentor, guide, and counsel analysts and consultants. Support the development of the practice by driving innovations and initiatives. Support efforts of sales team to identify and win potential opportunities by assisting with RFPs, RFI. Assist in designing POVs, GTM collateral. Professional & Technical Skills: 7-12 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services / Risk Advisory with significant exposure to Credit Risk :PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior :Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk :Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML) :AML Scenarios/Alerts, Network Analysis Operational Risk :AMA Modeling, Operational Risk Reporting Modeling Techniques :Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools :SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters Degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities Industry Certifications :FRM, PRM, CFA preferred Excellent Communication and Interpersonal Skills About Our Company | Accenture Qualification Experience :Minimum 7-12 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification :Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Job Title :S&C GN - Data Science Senior Manager Location :Bengaluru, Gurugram, Mumbai, Kolkata, Pune, Chennai, Hyderabad Must have skills :Machine Learning, Deep Learning, Gen AI, NLP, Python, R, AI, SQL Good to have skills : Experience in Graph Neural Networks (GNNs) for complex relational data modeling. Expertise in LLM advancements, including fine-tuning, prompt engineering, and efficient deployment of Large Language Models. A track record of scientific publications or intellectual property generation demonstrating expertise in AI and data science. We are an innovative Data Science team specializing in the Contact Center domain, dedicated to transforming customer interactions through data-driven intelligence. As part of the Marketing Analytics team, we focus on enhancing contact center operations by leveraging machine learning, natural language processing (NLP), and advanced analytics. Our work involves analyzing customer conversations, predicting user behavior, and enhancing self-service capabilities to reduce call transfers and improve satisfaction. We build conversational AI models, real-time recommendation systems, and predictive analytics solutions that drive meaningful business impact. By integrating AI-driven insights with marketing strategies, we enable proactive customer engagement, personalized experiences, and operational efficiencies across various touchpoints. If you're passionate about applying data science to solve real-world customer experience challenges, this is the team for you! Professional & Technical Skills :As a Senior Manager in our Data Science team, you will play a key role in leveraging Generative AI and Machine Learning to enhance customer experiences and optimize contact center operations. Your responsibilities will include: Driving the strategy and execution of AI/ML initiatives to enhance customer interactions, automate responses, and improve self-service capabilities. Leading the development and deployment of scalable ML solutions for intent classification, sentiment analysis, and predictive analytics. Designing and implementing AI-driven customer segmentation and behavioral analysis frameworks for personalized recommendations and targeted engagement. Overseeing the optimization of conversational AI workflows by enhancing intent recognition, response generation, and real-time decision-making. Spearheading the analysis of large-scale customer interaction data to extract actionable insights and refine business strategies. Partnering with engineering, product, and marketing teams to integrate AI-driven solutions into enterprise platforms. This role offers the opportunity to work on cutting-edge AI and data science techniques, driving real-world impact in the contact center space. Leadership & Business Impact : Leading multiple AI/ML-driven projects from conceptualization to deployment, ensuring alignment with business objectives and client needs. Engaging with senior stakeholders and C-suite executives to translate AI insights into actionable business strategies. Managing high-performing data science teams, mentoring talent, and fostering a culture of innovation and excellence. Driving business development efforts, including identifying new opportunities, leading client presentations, and contributing to proposals and thought leadership. Establishing and strengthening partnerships with key clients, ensuring long-term collaboration and success. Shaping the organization's AI roadmap by staying ahead of industry trends, evaluating emerging technologies, and driving continuous improvement. This position is ideal for an experienced AI leader passionate about leveraging advanced analytics and machine learning to solve complex business problems and drive meaningful impact. About Our Company | AccentureQualification Experience & Educational Qualification : PhD with 10+ years of relevant experience, OR Masters degree with 12+ years of experience, OR Bachelors degree with 15+ years of experience

Job Title :S&C GN - Data Science Senior Manager Location :Bengaluru, Gurugram, Mumbai, Kolkata, Pune, Chennai, Hyderabad Must have skills :Machine Learning, Deep Learning, Gen AI, NLP, Python, R, AI, SQL Good to have skills : Experience in Graph Neural Networks (GNNs) for complex relational data modeling. Expertise in LLM advancements, including fine-tuning, prompt engineering, and efficient deployment of Large Language Models. A track record of scientific publications or intellectual property generation demonstrating expertise in AI and data science. We are an innovative Data Science team specializing in the Contact Center domain, dedicated to transforming customer interactions through data-driven intelligence. As part of the Marketing Analytics team, we focus on enhancing contact center operations by leveraging machine learning, natural language processing (NLP), and advanced analytics. Our work involves analyzing customer conversations, predicting user behavior, and enhancing self-service capabilities to reduce call transfers and improve satisfaction. We build conversational AI models, real-time recommendation systems, and predictive analytics solutions that drive meaningful business impact. By integrating AI-driven insights with marketing strategies, we enable proactive customer engagement, personalized experiences, and operational efficiencies across various touchpoints. If you're passionate about applying data science to solve real-world customer experience challenges, this is the team for you! Professional & Technical Skills :As a Senior Manager in our Data Science team, you will play a key role in leveraging Generative AI and Machine Learning to enhance customer experiences and optimize contact center operations. Your responsibilities will include: Driving the strategy and execution of AI/ML initiatives to enhance customer interactions, automate responses, and improve self-service capabilities. Leading the development and deployment of scalable ML solutions for intent classification, sentiment analysis, and predictive analytics. Designing and implementing AI-driven customer segmentation and behavioral analysis frameworks for personalized recommendations and targeted engagement. Overseeing the optimization of conversational AI workflows by enhancing intent recognition, response generation, and real-time decision-making. Spearheading the analysis of large-scale customer interaction data to extract actionable insights and refine business strategies. Partnering with engineering, product, and marketing teams to integrate AI-driven solutions into enterprise platforms. This role offers the opportunity to work on cutting-edge AI and data science techniques, driving real-world impact in the contact center space. Leadership & Business Impact : Leading multiple AI/ML-driven projects from conceptualization to deployment, ensuring alignment with business objectives and client needs. Engaging with senior stakeholders and C-suite executives to translate AI insights into actionable business strategies. Managing high-performing data science teams, mentoring talent, and fostering a culture of innovation and excellence. Driving business development efforts, including identifying new opportunities, leading client presentations, and contributing to proposals and thought leadership. Establishing and strengthening partnerships with key clients, ensuring long-term collaboration and success. Shaping the organization's AI roadmap by staying ahead of industry trends, evaluating emerging technologies, and driving continuous improvement. This position is ideal for an experienced AI leader passionate about leveraging advanced analytics and machine learning to solve complex business problems and drive meaningful impact. About Our Company | AccentureQualification Experience & Educational Qualification : PhD with 10+ years of relevant experience, OR Masters degree with 12+ years of experience, OR Bachelors degree with 15+ years of experience

Job Title - S&C Global Network - AI - CMT ML Ops Ass Manager Management Level:8- Associate Manager Location:Open Must-have skills: AI Architecture/ Gen AI Good to have skills: Ability to leverage design thinking, business process optimization, and stakeholder management skills. Job Summary : This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Roles & Responsibilities: Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. 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. Professional & Technical Skills: - Relevant experience in the required domain. - Strong analytical, problem-solving, and communication skills. - Ability to work in a fast-paced, dynamic environment. 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. Additional Information: - Opportunity to work on innovative projects. - Career growth and leadership exposure. About Our Company | Accenture Qualification Experience: 6+ years Educational Qualification: Btech/ BE

Join our Team About this Opportunity The complexity of running and optimizing the next generation of wireless networks, such as 5G with distributed edge compute, will require Machine Learning (ML) and Artificial Intelligence (AI) technologies. Ericsson is setting up an AI Accelerator Hub in India to fast-track our strategy execution, using Machine Intelligence (MI) to drive thought leadership, automate, and transform Ericsson s offerings and operations. We collaborate with academia and industry to develop state-of-the-art solutions that simplify and automate processes, creating new value through data insights. What you will do As a Senior Data Scientist, you will apply your knowledge of data science and ML tools backed with strong programming skills to solve real-world problems. Responsibilities: 1. Lead AI/ML features/capabilities in product/business areas 2. Define business metrics of success for AI/ML projects and translate them into model metrics 3. Lead end-to-end development and deployment of Generative AI solutions for enterprise use cases 4. Design and implement architectures for vector search, embedding models, and RAG systems 5. Fine-tune and evaluate large language models (LLMs) for domain-specific tasks 6. Collaborate with stakeholders to translate vague problems into concrete Generative AI use cases 7. Develop and deploy generative AI solutions using AWS services such as SageMaker, Bedrock, and other AWS AI tools. Provide technical expertise and guidance on implementing GenAI models and best practices within the AWS ecosystem. 8. Develop secure, scalable, and production-grade AI pipelines 9. Ensure ethical and responsible AI practices 10. Mentor junior team members in GenAI frameworks and best practices 11. Stay current with research and industry trends in Generative AI and apply cutting-edge techniques 12. Contribute to internal AI governance, tooling frameworks, and reusable components 13. Work with large datasets including petabytes of 4G/5G networks and IoT data 14. Propose/select/test predictive models and other ML systems 15. Define visualization and dashboarding requirements with business stakeholders 16. Build proof-of-concepts for business opportunities using AI/ML 17. Lead functional and technical analysis to define AI/ML-driven business opportunities 18. Work with multiple data sources and apply the right feature engineering to AI models 19. Lead studies and creative usage of new/existing data sources What you will bring 1. Bachelors/Masters/Ph.D. in Computer Science, Data Science, AI, ML, Electrical Engineering, or related disciplines from reputed institutes 2. 3+ years of applied ML/AI production-level experience 3. Strong programming skills (R/Python) 4. Proven ability to lead AI/ML projects end-to-end 5. Strong grounding in mathematics, probability, and statistics 6. Hands-on experience with data analysis, visualization techniques, and ML frameworks (Python, R, H2O, Keras, TensorFlow, Spark ML) 7. Experience with semi-structured/unstructured data for AI/ML models 8. Strong understanding of building AI models using Deep Neural Networks 9. Experience with Big Data technologies (Hadoop, Cassandra) 10. Ability to source and combine data from multiple sources for ML models Preferred Qualifications: 1. Good communication skills in English 2. Certifying MI MOOCs, a plus 3. Domain knowledge in Telecommunication/IoT, a plus 4. Experience with data visualization and dashboard creation, a plus 5. Knowledge of Cognitive models, a plus 6. Experience in partnering and collaborative co-creation in a global matrix organization. Why join Ericsson What happens once you apply Primary country and city: India (IN) || Bangalore Req ID: 766481

Skill required: Data Scientist - Data Science Designation: Specialist Qualifications: Any Graduation Years of Experience: 7 - 11 Years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com What would you do You will be aligned with our Insights & Intelligence vertical and help us generate insights by leveraging the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to our clients. You will also help us apply your expertise in building world-class solutions, conquering business problems, addressing technical challenges using AI Platforms and technologies. You will be required to utilize the existing frameworks, standards, patterns to create architectural foundation and services necessary for AI applications that scale from multi-user to enterprise-class and demonstrate yourself as an expert by actively blogging, publishing research papers, and creating awareness in this emerging area. You will be working as a part of Marketing & Customer Analytics team which provides a set of processes that measure, manage and analyze marketing activities in order to provide actionable insights and recommendations to marketing organizations in terms of optimizing ROI & performance efficiency in operations.Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. You should have exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst. You will be a core member of Accenture Operations global Applied Intelligence group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. The objectives of the team include but are not limited toLeading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience - Python, R, SAS, S-plus, MATLAB, STATA or SPSS. Experience working with large data sets and big data tools like Snowflake, AWS, Spark, etc. Solid knowledge in at least one of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc.), Multivariate Statistics, Non-parametric Methods, Reliability Models, Markov Models, Stochastic models, Bayesian Models Experience in atleast one of these business domainsCPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Roles and Responsibilities: In this role you are required to do analysis and solving of moderately complex problems Typically creates new solutions, leveraging and, where needed, adapting existing methods and procedures The person requires understanding of the strategic direction set by senior management as it relates to team goals Primary upward interaction is with direct supervisor or team leads Generally, interacts with peers and/or management levels at a client and/or within Accenture The person should require minimal guidance when determining methods and procedures on new assignments Decisions often impact the team in which they reside and occasionally impact other teams Individual would manage medium-small sized teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Please note that this role may require you to work in rotational shifts Qualification Any Graduation