7848 Tensorflow Jobs - Page 8

Artificial Intelligence Machine learning. Experience: 6+ Years of experience.Location: Pan India. Mandatory: Deep understanding of AI and machine learning algorithms, including large language models (LLMs). Like Azure OpenAI, Mystral proficiency in deployment of LLM on On Prem or local Server Good to have: Integration with , Gemini ,Knowledge of Agentic AI and Agentic RAG Cloud ComputingMandatory: Proficiency in cloud platforms like Azure for deploying AI solutions and using existing AI capability of cloud platform. Good understanding of Azure Container Registry, Azure Container Instance and App Services Good to have: Proficiency in cloud platforms like AWS, Google Cloud for deploying AI solutions Programming SkillsMandatory: Strong coding skills in languages such as Python. Fast API, Flask API creation and integration of API from third party tools like SNOW, Sharepoint. Strong skills in UI development in Angular, Streamlit, HTML, CSS, Java script Expertise in TensorFlow, PyTorch, and relevant AI/ML libraries to fine-tune models Good to have: Integration with monitoring tools (e.g., Solarwinds, Splunk, NewRelic) Data Engineering Mandatory: Data flow diagram and data security at rest and motion. Good to have: Collaboration with team to analyze business data and understand to implement the solution and ensure data security and compliance Solution ArchitectureMandatory: Ability to design and implement scalable AI, GenAI solutions tailored to business needs. Architecture, design development and walkthrough with customer. Designing Hardware and Software requirement to deploy GenAI solution for On-Prem or Cloud. Good understanding of Multi factor Authentication. Good to have:Cost estimation for GenAI solution deployment on Cloud Platform.

As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

As a Principle Engineer - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Foster a collaborative and supportive work environment, promoting open communication and teamwork. Demonstrate strong leadership skills, with the ability to inspire and motivate team members to perform at their best. Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be able to identify problems, generate effective solutions, and troubleshoot issues that may arise while working on complex projects. Must Display Adaptability to changing circumstances, new technology, and shifting priorities. Nice-to-have skills Qualifications Qualifications 11-12 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Job Description Lead the design and development of robust machine learning and deep learning architectures tailored to solve real-world business challenges. Build and optimize models using frameworks like TensorFlow, PyTorch, and Keras, ensuring high accuracy and performance. Architect and oversee end-to-end data pipelines, including data ingestion, preprocessing, and feature engineering for AI workloads. Research, prototype, and productionize novel algorithms in areas such as computer vision, NLP, and reinforcement learning. Deploy models using cloud platforms (AWS/Azure/GCP), leveraging GPU/TPU infrastructure, and integrating into CI/CD workflows using Docker and other tools. Tune hyperparameters, manage model drift, and implement monitoring to ensure sustained model performance in production. Collaborate with engineering, data science, and product teams to align AI initiatives with business goals. Ensure robust documentation, version control, and adherence to MLOps principles throughout the development lifecycle. Stay ahead of trends in AI/ML and guide the team on best practices, tools, and frameworks. Requirements Required Skills and Qualifications: Education: Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related technical field. Experience: 4–5 years of experience in developing and deploying machine learning or deep learning solutions in real-world environments. Technical Expertise: Proficient in Python and ML libraries: NumPy, Pandas, Scikit-learn, Matplotlib, etc. Deep experience with TensorFlow, PyTorch, and Keras. Strong grasp of neural networks, CNNs, RNNs, Transformers, and GANs. Experience with GPU/TPU acceleration, model optimization, and distributed training. Familiarity with cloud platforms (AWS, Azure, or GCP) for scalable AI deployments. Hands-on with Docker, version control, and CI/CD tools for deployment automation. Experience in NLP, Computer Vision, or Reinforcement Learning projects is a strong plus. Preferred Traits: Strong problem-solving and architectural thinking Ability to work in agile, cross-functional teams Passion for innovation and applying AI to business use cases

Job Description Some careers shine brighter than others. If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further. HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions. We are currently seeking an experienced professional to join our team in the role of Senior Consultant Specialist The individual in this role as ML Engineer will be accountable for Design, develop, and deploy machine learning models and algorithms to solve business problems. Below are the key responsibilities / activities that need to be planned, attested and executed under the remit of this role by working effectively and collaboratively with the different delivery teams. In this role, you will: Design, develop, and deploy machine learning models and algorithms to solve business problems. Preprocess and analyze large datasets to extract meaningful insights. Build and optimize data pipelines (Extract data from Oracle, Elasticsearch, storage buckets, etc.) for training and deploying ML models. Collaborate with data scientists, software engineers, and stakeholders to integrate ML solutions into production systems. Monitor and maintain deployed models to ensure performance and accuracy over time. Research and implement state-of-the-art machine learning techniques and tools. Document processes, experiments, and results for reproducibility and knowledge sharing. Stay up to date with tech, prototype with and learn new technologies, proactive in technology communities Develop & maintain ML models for Credit monitoring domain. E.g. Perpetual credit montiroing Develop innovative solutions in areas such as machine learning, Natural Language Processing (NLP), advanced and semantic information search, extraction, induction, classification and exploration Create products that provide a great user experience along with high performance, security, quality, and stability Requirements To be successful in this role, you should meet the following requirements: Minimum 10 years of software development experience. 5+ years of relevant experience in ML technologies mentioned below. Excellent problem-solving and communication skills. Strong experience in Python (3.x). Excellent working knowledge on scikit-learn, TensorFlow / PyTorch, Docker/Kubernetes. Good experience of SQL, Oracle/PostgreSQL, any NoSQL database, File buckets. Experience in using data from data lake Excellent knowledge and demonstrable experience in using open-source NLP packages such as NLTK, Word2Vec, SpaCy. Experience in setting up supervised & unsupervised learning models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization Solid understanding of ML algorithms, ML statistics, and data structures. Excellent interpersonal, presentation and analytical skills. Familiarity with MLOps practices for model deployment and monitoring. Experience working in banking domain with exposure credit monitoring Experience in automating the continuous integration/continuous delivery pipeline within a DevOps Product/Service team driving a culture of continuous improvement Location : Pune and Bangalore You’ll achieve more when you join HSBC. www.hsbc.com/careers HSBC is committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and opportunities to grow within an inclusive and diverse environment. Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website. Issued by – HSBC Software Development India

Job Description Some careers shine brighter than others. If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further. HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions. We are currently seeking an experienced professional to join our team in the role of Consultant Specialist The individual in this role as ML Engineer will be accountable for Design, develop, and deploy machine learning models and algorithms to solve business problems. Below are the key responsibilities / activities that need to be planned, attested and executed under the remit of this role by working effectively and collaboratively with the different delivery teams. In this role, you will: Design, develop, and deploy machine learning models and algorithms to solve business problems. Preprocess and analyze large datasets to extract meaningful insights. Build and optimize data pipelines (Extract data from Oracle, Elasticsearch, storage buckets, etc.) for training and deploying ML models. Collaborate with data scientists, software engineers, and stakeholders to integrate ML solutions into production systems. Monitor and maintain deployed models to ensure performance and accuracy over time. Research and implement state-of-the-art machine learning techniques and tools. Document processes, experiments, and results for reproducibility and knowledge sharing. Stay up to date with tech, prototype with and learn new technologies, proactive in technology communities Develop & maintain ML models for Credit monitoring domain. E.g. Perpetual credit montiroing Develop innovative solutions in areas such as machine learning, Natural Language Processing (NLP), advanced and semantic information search, extraction, induction, classification and exploration Create products that provide a great user experience along with high performance, security, quality, and stability Requirements To be successful in this role, you should meet the following requirements: Minimum 10 years of software development experience. 5+ years of relevant experience in ML technologies mentioned below. Excellent problem-solving and communication skills. Strong experience in Python (3.x). Excellent working knowledge on scikit-learn, TensorFlow / PyTorch, Docker/Kubernetes. Good experience of SQL, Oracle/PostgreSQL, any NoSQL database, File buckets. Experience in using data from data lake Excellent knowledge and demonstrable experience in using open-source NLP packages such as NLTK, Word2Vec, SpaCy. Experience in setting up supervised & unsupervised learning models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization Solid understanding of ML algorithms, ML statistics, and data structures. Excellent interpersonal, presentation and analytical skills. Familiarity with MLOps practices for model deployment and monitoring. Experience working in banking domain with exposure credit monitoring Experience in automating the continuous integration/continuous delivery pipeline within a DevOps Product/Service team driving a culture of continuous improvement Location : Pune and Bangalore You’ll achieve more when you join HSBC. www.hsbc.com/careers HSBC is committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and opportunities to grow within an inclusive and diverse environment. Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement, which is available on our website. Issued by – HSBC Software Development India

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 3-7 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

We are seeking a talented individual to join our Data Science team at Marsh. This role will be based in Mumbai. This is a hybrid role that has a requirement of working at least three days a week in the office. Senior Manager - Data Science (AI - CoE) This role at Knowledge Services aims to provide colleagues with an exposure towards key risks faced by businesses and utilize Artificial intelligence to manage, transfer or mitigate them. Incumbent is expected to be an expert of Generative AI (OpenAI API’s), Prompt Engineering, Data Science algorithms, Business Analytics and Data Manipulation. Incumbent will also have an opportunity to contribute to cutting edge analytics platform and products. Expertise in Python is a must. Experience with Insurance or Banking industry is a plus. This position is for an individual contributor in AI and Data Science, who will develop and implement leading-edge techniques in artificial intelligence, machine learning, predictive modeling, and natural language processing as applied in commercial insurance and risk management. This position consults with senior colleagues on complex financial and statistical analyses, and develops approaches for new, market-leading AI-based tools. We will count on you to Understand and refine the Math and Statistics behind the complex AI models Build AI and machine learning algorithms based on the business ask Keep up pace with new trends in the AI world Mine and analyze data to drive optimization and implement business strategies Deploy API’s on the cloud platforms by understanding the technical ask Develop statistical custom data models and algorithms from scratch to enhance current value proposition and new product development What you need to have: Develops solutions based on Large Language Models, Advanced transformers, Advanced deep learning/Neural networks models Expertise in image based advanced models, Object detection, Video/Image processing, multimodal RAG’s and other image and video models Develops and deploys API based business solutions on AWS platforms Coordinates with technology colleagues within and outside the team for support, manage, enhance and retrains deployed models Keeps pace with the fast-evolving world of AI, large language models and other type of AI solutions in the market and able to apply research level knowledge to benefit Marsh advisory businesses Designs, develops and contributes to Data architecture for complex enterprise level applications Deploys solutions on AWS cloud platforms Understands business problems to create an approach that starts with determining structured and unstructured data needs and availability, builds AI/ML models, and finalizes with results that unlock insight for clients/colleagues, deploy these solutions on web framework and enterprise wide platforms Demonstrates skill in advanced statistical analysis, data mining, and/or research techniques, combined with broader awareness of the business and ongoing research, while functioning in a collaborative role with the Data Science team and across the wider organization Stays current with ongoing research in the field and brings new approaches to the team Coaches team members on the delivery of AI-based tools and analyses and presentation of findings Master’s Degree in Engineering, Computer Science, Data Science or related field 7+ years of experience in the field of Data Science, AI research or similar fields Expert Data Scientist, including expertise with AI and machine learning model building Ability to influence others within and outside of the job function regarding approach and procedures Superior detail orientation, excellent communication and interpersonal skills Expertise of modern programming languages such as Python, including NumPy, Keras, TensorFlow, SQL, and PyTorch etc Familiar with Hugging face and is library of models What makes you stand out? Building, training and deploying advanced models from the scratch to the production Business impact with AI models Understanding of insurance and risk management Knowledge and demonstrated experience of advance AI concepts like training language, voice, image or computer vision models Experience of building data visualization in Plotly/Dash/D3.js Hands on experience with stochastic or econometric modelling Why join our team: We help you be your best through professional development opportunities, interesting work and supportive leaders. We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities. Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being. Marsh, a business of Marsh McLennan (NYSE: MMC), is the world’s top insurance broker and risk advisor. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person. R_313481

GCP Cloud Architecture. Model Deployment Lifecycle Knowledge of creating Training & Serving Pipeline Familiar with any one of workflow: Kubeflow, Airflow, ML Flow, Argo etc" Strong in Python Adequate SQL skill Must have skill : Python, SQL, ML Engineer (Model Deployment/MLOPS), ML Pipeline-(Kubeflow, Airflow Flow, Argo etc,) Preferred Skill: Pytorch, TensorFlow, Exp in hiper scaler/Cloud Service, Deep learning framework,

Mandatory Skill : Gen AI, LLM, GPT-3, RAG, Lang chain, Llama, AI/ML, DL, NLP or Computer Vision, Python, Tensorflow, Pytorch, Django, Keras, Pandas, NumPy Preferred Skill: AWS or GCP or Azure Cloud, MLOps, GPT-4, SQL, Scikit-learn, Matplotlib, Seaborn, Hadoop, Spark, or Apache Flink, Banking exposure Required Skill Programming Languages: Proficiency in Python, R, or Java. Experience with libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, etc. Machine Learning: Strong understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning. Data Science: Experience with data analysis, data visualization, and statistical modeling. Proficiency in using tools like Pandas, NumPy, Matplotlib, and Seaborn. Big Data Technologies: Familiarity with big data processing frameworks like Hadoop, Spark, or Apache Flink. Cloud Platforms: Experience with cloud services such as AWS, Google Cloud, or Azure for deploying AI solutions. Natural Language Processing (NLP): Knowledge of NLP techniques and tools such as NLTK, SpaCy, or GPT-3. Computer Vision: Experience with computer vision techniques and libraries such as OpenCV, YOLO, or Fast R-CNN. Problem-Solving: Strong analytical and problem-solving skills with the ability to think critically and creatively. Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Team Collaboration: Ability to work effectively in a collaborative team environment and contribute to team success.

Ciklum is looking for a Senior Data Scientist to join our team full-time in India. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live. About the role: As a Senior Data Scientist, become a part of a cross-functional development team working for A healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions. Our client is a leader in SaaS technology for healthcare, They offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem. With their expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace. Responsibilities: Development of prototype solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets Work on exploratory data analysis so you can navigate a dataset and come out with broad conclusions based on initial appraisals Provide optimization recommendations that drive KPIs established by product, marketing, operations, PR teams, and others Interacts with engineering teams and ensures that solutions meet customer requirements in terms of functionality, performance, availability, scalability, and reliability Work directly with business analysts and data engineers to understand and support their use cases Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions Drive innovation by exploring new experimentation methods and statistical techniques that could sharpen or speed up our product decision-making processes Cross-trains other team members on technologies being developed, while also continuously learning new technologies from other team members Contribute to unit’s activities and community building, participate in conferences, and provide excellence in exercise and best practices Requirements: We know that sometimes, you can’t tick every box. We would still love to hear from you if you think you’re a good fit! 5+ years of development of Data Science solutions with a proven track record of leveraging analytics to drive significant business impact Bachelor's/Master's degree in Mathematics, Statistics, Computer Science, Operations Research, Econometrics or related field Proven ability to relate and solve business problems through machine learning and statistics 4+ years of experience applying various machine learning techniques: regression, classification, clustering, dimensional reduction, time series prediction, and/or outlier detection, recommendation systems Understanding of advantages and drawbacks of machine learning algorithms as well as their usage constraints including performance 4+ years of experience in Python development of machine learning solutions and statistical analysis: Pandas, SciPy, Scikit-learn, XGBoost, LightGBM, and/or statsmodels, imbalanced-learn libraries and ML libraries like scikit-learn, TensorFlow, PyTorch, data wrangling and visualization (e.g., Pandas, NumPy, Matplotlib, Seaborn Experience in working with large-scale datasets, including time series and healthcare data Experience with NLP, deep learning and GenAI Experience diving into data to consider hidden patterns and conducting error analysis 2+ years experience in data visualization: Power BI, Tableau, and/or Python libraries like Matplotlib and Seaborn Experience with SQL for data processing, data manipulation, sampling, reporting 3+ years experience creating/maintaining of OOP Machine Learning solutions Understanding of CRISP-ML(Q) / TDSP concept 1+ year of experience with MLOps: integration of reliable Machine Learning Pipelines in Production, Docker, containerization, orchestration 2+ years of experience with Clouds (AWS, Azure, GCP) and Clouds AI And ML Services(e.g. Amazon Sage Maker, Azure ML) Excellent time and project management skills, with the ability to manage detailed work and communicate project status effectively to all levels Desirable: Probability Theory & Statistics knowledge and intuition as well as understanding of Mathematics behind Machine Learning 1+ year of experience in Deep Learning solution development with Tensorflow or PyTorch libraries Data Science / Machine Learning certifications, or research experience with papers being published Experience with Kubernetes Experience with Databricks, Snowflake platforms 1+ year of BigData experience, i.e. Hadoop / Spark Experience with No-SQL, and/or columnar/graph databases What`s in it for you? Care: your mental and physical health is our priority. We ensure comprehensive company-paid medical insurance, as well as financial and legal consultation Tailored education path: boost your skills and knowledge with our regular internal events (meetups, conferences, workshops), Udemy license, language courses and company-paid certifications Growth environment: share your experience and level up your expertise with a community of skilled professionals, locally and globally Opportunities: we value our specialists and always find the best options for them. Our Resourcing Team helps change a project if needed to help you grow, excel professionally, and fulfil your potential Global impact: work on large-scale projects that redefine industries with international and fast-growing clients Welcoming environment: feel empowered with a friendly team, open-door policy, informal atmosphere within the company and regular team-building events About us: India is a strategic growth market for Ciklum. Be a part of a big story created right now. Let’s grow our delivery center in India together! Boost your skills and knowledge: create and innovate with like-minded professionals — all of that within a global company with a local spirit and start-up soul. Supported by Recognize Partners and expanding globally, we will engineer the experiences of tomorrow! Be bold, not bored! Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum.

Artificial Intelligence Machine learning. Mandatory : Deep understanding of AI and machine learning algorithms, including large language models (LLMs). Like Azure OpenAI, Mystral proficiency in deployment of LLM on On Prem or local Server Good to have : Integration with , Gemini ,Knowledge of Agentic AI and Agentic RAG Cloud ComputingMandatory : Proficiency in cloud platforms like Azure for deploying AI solutions and using existing AI capability of cloud platform. Good understanding of Azure Container Registry, Azure Container Instance and App Services Good to have : Proficiency in cloud platforms like AWS, Google Cloud for deploying AI solutions Programming SkillsMandatory : Strong coding skills in languages such as Python. Fast API, Flask API creation and integration of API from third party tools like SNOW, Sharepoint. Strong skills in UI development in Angular, Streamlit, HTML, CSS, Java script Expertise in TensorFlow, PyTorch, and relevant AI/ML libraries to fine-tune models Good to have : Integration with monitoring tools (e.g., Solarwinds, Splunk, NewRelic) Data Engineering Mandatory : Data flow diagram and data security at rest and motion. Good to have : Collaboration with team to analyze business data and understand to implement the solution and ensure data security and compliance Solution ArchitectureMandatory : Ability to design and implement scalable AI, GenAI solutions tailored to business needs. Architecture, design development and walkthrough with customer. Designing Hardware and Software requirement to deploy GenAI solution for On-Prem or Cloud. Good understanding of Multi factor Authentication. Good to have: Cost estimation for GenAI solution deployment on Cloud Platform.

Role Purpose The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters Do 1. Instrumental in understanding the requirements and design of the product/ software Develop software solutions by studying information needs, studying systems flow, data usage and work processes Investigating problem areas followed by the software development life cycle Facilitate root cause analysis of the system issues and problem statement Identify ideas to improve system performance and impact availability Analyze client requirements and convert requirements to feasible design Collaborate with functional teams or systems analysts who carry out the detailed investigation into software requirements Conferring with project managers to obtain information on software capabilities 2. Perform coding and ensure optimal software/ module development Determine operational feasibility by evaluating analysis, problem definition, requirements, software development and proposed software Develop and automate processes for software validation by setting up and designing test cases/scenarios/usage cases, and executing these cases Modifying software to fix errors, adapt it to new hardware, improve its performance, or upgrade interfaces. Analyzing information to recommend and plan the installation of new systems or modifications of an existing system Ensuring that code is error free or has no bugs and test failure Preparing reports on programming project specifications, activities and status Ensure all the codes are raised as per the norm defined for project / program / account with clear description and replication patterns Compile timely, comprehensive and accurate documentation and reports as requested Coordinating with the team on daily project status and progress and documenting it Providing feedback on usability and serviceability, trace the result to quality risk and report it to concerned stakeholders 3. Status Reporting and Customer Focus on an ongoing basis with respect to project and its execution Capturing all the requirements and clarifications from the client for better quality work Taking feedback on the regular basis to ensure smooth and on time delivery Participating in continuing education and training to remain current on best practices, learn new programming languages, and better assist other team members. Consulting with engineering staff to evaluate software-hardware interfaces and develop specifications and performance requirements Document and demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code Documenting very necessary details and reports in a formal way for proper understanding of software from client proposal to implementation Ensure good quality of interaction with customer w.r.t. e-mail content, fault report tracking, voice calls, business etiquette etc Timely Response to customer requests and no instances of complaints either internally or externally

Description About the Role: As a Cognitive SON Architect, you will be responsible for designing, developing, and implementing AI-driven solutions to enhance the performance, scalability, and self-management of telecommunications networks. You will work in close collaboration with cross-functional teams to build and deploy intelligent network automation tools leveraging machine learning, artificial intelligence, and advanced analytics. The goal is to deliver innovative solutions to optimize the operation and evolution of modern mobile networks, particularly focusing on 5G and beyond. Requirements Skills & Qualifications: Education: A bachelor’s or master’s degree in Telecommunications, Computer Science, Electrical Engineering, or a related field. Experience: Proven experience (typically 5+ years) in network architecture, SON, or AI/ML applications within telecommunications. Strong background in network optimization, particularly in RAN, 5G, or related technologies. Experience with Cognitive SON technologies, automation, and self-optimizing networks is highly desirable. Technical Expertise: Strong programming skills in languages such as Python, Java, Microservices. Proficiency in AI/ML algorithms, data modeling, and statistical methods. In-depth knowledge of RAN technologies, 5G, and network management protocols. Experience with cloud computing, big data platforms, and software-defined networking (SDN) is a plus. Desirable Skills: Familiarity with network orchestration and management tools (e.g., NFV, SDN). Experience with programming languages such as Python, Java, or similar, used for AI/ML solutions. Hands-on experience with tools like TensorFlow, PyTorch, or other machine learning frameworks. Knowledge of 5G and future mobile network standards (e.g., 3GPP, O-RAN). Skills: Strong problem-solving abilities and a passion for developing innovative solutions. Excellent communication skills to work with cross-functional teams and stakeholders. Ability to understand and translate business requirements into technical solutions. Job responsibilities Key Responsibilities: Design & Architecture: Define the architecture for Cognitive SON solutions, integrating AI/ML techniques to automate network management tasks such as self-healing, self-optimization, and self-configuration. Technology Development: Develop innovative algorithms, models, and tools to enhance the cognitive capabilities of SON systems, utilizing AI/ML techniques to solve complex network optimization challenges. Network Optimization: Work on optimizing radio access networks (RAN) by developing solutions that adapt in real-time to network conditions and demands. This includes interference management, load balancing, and energy efficiency. AI/ML Integration: Collaborate with data scientists to implement machine learning and artificial intelligence methods for predictive analytics, anomaly detection, and decision-making in the SON context. End-to-End Solution Design: Lead the design of end-to-end SON solutions, ensuring seamless integration with existing network management systems, 5G infrastructure, and other products. Collaboration: Work closely with product managers, engineers, and stakeholders to ensure the successful delivery of Cognitive SON features and the alignment of solution development with business goals. Research and Innovation: Stay updated with the latest trends and advancements in AI/ML, network automation, and self-organizing networks, and contribute to the continuous innovation in solutions. Customer Interaction: Engage with customers to understand their network challenges and provide solutions that leverage Cognitive SON technology to address their needs and pain points. What we offer Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally. Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today. Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way! High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do. About GlobalLogic GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.

Solutions Architect / Technical Lead - AI & Automation1 Key Responsibilities Solution Architecture & Development: Design end-to-end solutions using Node.JS (backend) and Vue.JS (frontend) for custom portals and administration interfaces. Integrate Azure AI services , Google OCR , and Azure OCR into client workflows. AI/ML Engineering: Develop and optimize vision-based AI models ( Layout Parsing/LP, Layout Inference/LI, Layout Transformation/LT ) using Python . Implement NLP pipelines for document extraction, classification, and data enrichment. Cloud & Database Management: Architect and optimize MongoDB databases hosted on Azure for scalability, security, and performance. Manage cloud infrastructure (Azure) for AI workloads, including containerization and serverless deployments. Technical Leadership: Lead cross-functional teams (AI engineers, DevOps, BAs) in solution delivery. Troubleshoot complex technical issues in OCR accuracy, AI model drift, or system integration. Client Enablement: Advise clients on technical best practices for scaling AI solutions. Document architectures, conduct knowledge transfers, and mentor junior engineers. Required Technical Expertise Frontend/Portal: Vue.JS (advanced components, state management), Node.JS (Express, REST/GraphQL APIs). AI/ML Stack: Python (PyTorch/TensorFlow), Azure AI (Cognitive Services, Computer Vision), NLP techniques (NER, summarization). Layout Engineering LP/LI/LT for complex documents (invoices, contracts). OCR Technologies: Production experience with Google Vision OCR and Azure Form Recognizer . Database & Cloud: MongoDB (sharding, aggregation, indexing) hosted on Azure (Cosmos DB, Blob Storage, AKS). Infrastructure-as-Code (Terraform/Bicep), CI/CD pipelines (Azure DevOps). Experience: 10+ years in software development, including 5+ years specializing in AI/ML, OCR, or document automation . Proven track record deploying enterprise-scale solutions in cloud environments (Azure preferred). Preferred Qualifications Certifications Azure Solutions Architect Expert , MongoDB Certified Developer , or Google Cloud AI/ML. Experience with alternative OCR tools (ABBYY, Tesseract) or AI platforms (GCP Vertex AI, AWS SageMaker). Knowledge of DocuSign CLM , Coupa , or SAP Ariba integrations. Familiarity with Kubernetes , Docker , and MLOps practices.

AI Ops Engineer2 Job TitleAI Ops EngineerExperience35 yearsAbout the RoleWe are seeking a hands-on and proactive AI Ops Engineer to operationalize andsupport the deployment of large language model (LLM) workflows, including agentic AIapplications, across Marvells enterprise ecosystem.This role requires strong prompt engineering capabilities, the ability to triage AI pipelineissues, and a deep understanding of how LLM-based agents interact with tools,memory, and APIs. You will be expected to diagnose and remediate real-time problems,from prompt quality issues to model behavior anomalies. Key ResponsibilitiesDesign, fine-tune, and manage prompts for various LLM use cases tailored to Marvellsenterprise operations.Operate, monitor, and troubleshoot agentic AI applications, including identifying whetherissues stem from:Prompt quality or structureModel configuration or performanceTool usage, API failures, or memory/recall issuesBuild diagnostics and playbooks to triage LLM-driven failures, including handling fallbackstrategies, retries, or re-routing to human workflows.Collaborate with architects, ML engineers, and DevOps to optimize agent orchestrationacross platforms like LangGraph, CrewAI, AutoGen, or similar.Support integration of agentic systems with enterprise apps like Jira, ServiceNow, Glean, orConfluence using REST APIs, webhooks, and adapters.Implement observability and logging best practices for model outputs, latency, and agentperformance metrics.Contribute to building self-healing mechanisms and alerting strategies for production-gradeAI workflows.Required Qualifications 36 years of experience in software engineering, DevOps, or ML Ops with exposure toAI/LLM workflows.Strong foundation in prompt engineering and experience with LLMs like GPT, Claude,LLaMA, etc.Practical understanding of AIOps platforms or operational AI use cases (incident triage,log summarization, root cause analysis, etc.).Exposure to agentic AI architectures, such as LangGraph, AutoGen, CrewAI, etc.Familiarity with scripting (Python), RESTful APIs, and basic system debugging.Strong analytical skills and the ability to trace issues across multi-step pipelines andasynchronous agents. Good-To-HaveGleanDevRevCodiumCursorAtlassian AIDatabricks Mosaic AI

🚀 We're Hiring: Founding AI Engineer @ Vakta.AI 🚀 Ready to revolutionize conversational AI from the ground up? Join us as a Founding AI Engineer at Vakta.AI and build intelligent voice solutions that will transform how people interact with technology. At Vakta.AI , we're creating India's most sophisticated conversational AI platform — from advanced natural language understanding to contextual dialogue systems and personalized AI assistants. We're solving complex problems in human-computer interaction that no one else is addressing at this scale. Why this is a game-changing opportunity: You'll be a founding team member , working directly with our core team to shape the technical vision and build revolutionary products from scratch. Competitive salary + substantial ESOPs — we want you to grow with us and share in our journey to success. You'll tackle cutting-edge challenges in conversational AI that will directly impact how millions of users experience technology. Massive growth potential, complete ownership, and the opportunity to build and lead your own engineering team as we scale. What we're looking for: Strong expertise in AI/ML (conversational AI, NLP, transformer architectures, or related domains) Proficiency with Python and frameworks like PyTorch, TensorFlow, or Hugging Face Someone who thrives on rapid prototyping and shipping, with experience in building production-scale AI systems A startup mentality: entrepreneurial, adaptable, and excited about pushing boundaries Additional details: Excellent salary + equity (ESOPs) — competitive package, negotiable for exceptional candidates We need someone who can start immediately (or within a few weeks!) Location: Hybrid/Remote with flexibility

Who We Are: Netcore Cloud is a MarTech platform helping businesses design, execute, and optimize campaigns across multiple channels. With a strong focus on leveraging data, machine learning, and AI, we empower our clients to make smarter marketing decisions and deliver exceptional customer experiences. Our team is passionate about innovation and collaboration, and we are looking for a talented Senior Data Scientist to join our team and work on impactful, high-scale projects. Role Summary: As a Senior Data Scientist, you’ll work on developing, deploying, and optimizing advanced machine learning solutions across a range of problem statements such as personalization, customer segmentation, predictive modeling, and NLP. This is a high-impact role that will allow you to collaborate across cross-functional teams and contribute directly to our product innovation roadmap. What You'll Do: Model Development and Innovation : Design and implement ML models for problems including recommendation engines, user segmentation, conversion prediction, and NLP-based automation Stay on top of the latest research in AI/ML and evaluate new approaches (e.g., LLMs, generative AI) for practical application. Optimise model performance, scalability, and interpretability for production systems. MLOps & Deployment Contribute to the deployment of models into production environments using MLOps best practices. Leverage platforms such as AWS SageMaker or Google Vertex AI for training, tuning, and scaling models. Data & Experimentation Work with large-scale, real-time datasets to derive actionable insights and build data pipelines for ML training and evaluation. Design and run experiments (A/B testing, uplift modeling, etc.) to validate hypotheses and improve product KPIs. Technology and Tools : Work with large-scale datasets, ensuring data quality and scalability of solutions. Leverage cloud platforms like AWS, GCP for model training and deployment. Utilize tools and libraries such as Python, TensorFlow, PyTorch, Scikit-learn, and Spark for development. With so much innovation happening around Gen AI and LLMs, we prefer folks who have already exposed themselves to this exciting opportunity via AWS Bedrock or Google Vertex. Cross-functional Collaboration Partner with product, engineering, and marketing teams to understand business requirements and translate them into data science solutions. Who You Are: Education : Bachelors from Tier 1 premier institute in relevant field, or; Master’s or PhD in Computer Science, Data Science, Mathematics, or a related field. Experience : 4–6 years of hands-on experience in machine learning or data science roles. Proven expertise in machine learning, deep learning, NLP, and recommendation systems. Hands-on experience deploying ML models in production at scale. Experience in a product-focused or customer-facing domain such as Martech, Adtech, or B2B SaaS is a plus. Technical Skills : Proficiency in Python, SQL, and ML frameworks like TensorFlow or PyTorch. Strong understanding of statistical methods, predictive modeling, and algorithm design. Familiarity with cloud-based solutions (AWS Sagemaker, GCP AI Platform, or similar). Soft Skills : Strong analytical and problem-solving mindset. Excellent communication skills to articulate data-driven insights. A passion for innovation and staying up-to-date with the latest trends in AI/ML. Why Join Us: Opportunity to work on cutting-edge AI/ML projects impacting millions of users. Be part of a collaborative, innovation-driven team in a fast-growing Martech company. Competitive compensation and growth opportunities in a fast-paced environment. We’d love to hear how your background can contribute to building the next generation of intelligent marketing solutions. Apply now or reach out for a conversation. :)

About the Role: We are seeking a highly skilled and experienced Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will be responsible for the design, development, deployment, and maintenance of machine learning models and systems that drive our [mention specific business area or product, e.g., recommendation engine, fraud detection system, autonomous vehicles]. You will work closely with data scientists, software engineers, and product managers to translate business needs into scalable and reliable machine learning solutions. This is a key role in shaping the future of CBRE and requires a strong technical foundation combined with a passion for innovation and problem-solving. Responsibilities: Model Development & Deployment: Design, develop, and deploy machine learning models using various algorithms (e.g., regression, classification, clustering, deep learning) to solve complex business problems. Select appropriate datasets and features for model training, ensuring data quality and integrity. Implement and optimize model training pipelines, including data preprocessing, feature engineering, model selection, and hyperparameter tuning. Deploy models to production environments using containerization technologies (e.g.,Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure). Monitor model performance in production, identify and troubleshoot issues, and implement model retraining and updates as needed. Infrastructure & Engineering: Develop and maintain APIs for model serving and integration with other systems. Write clean, well-documented, and testable code. Collaborate with software engineers to integrate models into existing products and services. Research & Innovation : Stay up to date with the latest advancements in machine learning and related technologies. Research and evaluate new algorithms, tools, and techniques to improve model performance and efficiency. Contribute to the development of new machine learning solutions and features. Proactively identify opportunities to leverage machine learning to solve business challenges. Collaboration & Communication: * Collaborate effectively with data scientists, software engineers, product managers, and other stakeholders. * Communicate technical concepts and findings clearly and concisely to both technical and non-technical audiences. * Participate in code reviews and contribute to the team's knowledge sharing. Qualifications: * Experience : 7+ years of experience in machine learning engineering or a related field. Technical Skills: Programming Languages : Proficient in Python and experience with other languages (e.g., Java, Scala, R) is a plus. Machine Learning Libraries : Strong experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Keras, etc. Data Processing : Experience with data manipulation and processing using libraries like Pandas, NumPy, and Spark. Model Deployment : Experience with model deployment frameworks and platforms (e.g., TensorFlow Serving, TorchServe, Seldon, AWS SageMaker, Google AI Platform, Azure Machine Learning). Databases : Experience with relational and NoSQL databases (e.g., SQL, MongoDB, Cassandra). Version Control : Experience with Git and other version control systems. DevOps : Familiarity with DevOps practices and tools. Strong understanding of machine learning concepts and algorithms : Regression, Classification, Clustering, Deep Learning etc. Soft Skills: Excellent problem-solving and analytical skills. Strong communication and collaboration skills.

Job Title - Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary : The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. Stay updated on the latest trends in data science and retail technology. Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional & Technical Skills : Strong analytical and statistical skills. Expertise in machine learning and AI. Experience with retail-specific datasets and KPIs. Proficiency in data visualization and reporting tools. Ability to work with large datasets and complex data structures. Strong communication skills to interact with both technical and non-technical stakeholders. A solid understanding of the retail business and consumer behavior. Programming Languages:Python, R, SQL, Scala Data Analysis Tools:Pandas, NumPy, Scikit-learn, TensorFlow, Keras Visualization Tools:Tableau, Power BI, Matplotlib, Seaborn Big Data Technologies:Hadoop, Spark, AWS, Google Cloud Databases:SQL, NoSQL (MongoDB, Cassandra) Additional Information: - Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Position Overview: We are seeking a talented and experienced Core AI Algorithm Developer to join our Lab45 AI Platform Team, Wipro. We are looking for candidates with 4 to 10 years of hands-on experience in developing cutting-edge AI algorithms, such as in Generative AI, LLM, Deep Learning, Unsupervised AI, etc. along with expertise in Python, TensorFlow, PyTorch, PySpark, distributed computing, Statistics, and cloud technologies. Candidate should have strong foundation in AI and good coding skills. Key Responsibilities: Develop and implement state-of-the-art AI algorithms and models to solve complex problems in diverse domains. Collaborate with cross-functional teams to understand business requirements and translate them into scalable AI production-grade solutions. Work with large datasets to extract insights, optimize algorithms, and enhance model performance. Contribute to the creation of intellectual property (IP) through patents, research papers, and innovative solutions. Stay abreast of the latest advancements in AI research and technologies and apply them to enhance our AI offerings. Collaborate with cross-functional teams to understand business requirements, gather feedback, and iterate on AI solutions. Strong communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams. Qualifications: Master's, or Ph.D. degree (preferred) in Computer Science, Artificial Intelligence, Machine Learning, or related field. 4 to 10 years of proven experience in developing cutting-edge AI algorithms and solutions. Strong proficiency in Python programming and familiarity with TensorFlow, PyTorch, PySpark, etc. Experience with distributed computing and cloud platforms (e.g., Azure, AWS, GCP). Demonstrated ability to work with large datasets and optimize algorithms for scalability and efficiency. Excellent problem-solving skills and a strong understanding of AI concepts and techniques. Proven track record of delivering high-quality, innovative solutions and contributing to IP creation (e.g., patents, research papers). Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions. Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness Mandatory Skills: Data Analysis. Experience: 3-5 Years.