18 Ai Ml Jobs

Role: Solution Architect (AI/ML Specialization) Full time Professional About Onix : Onix is a Google Cloud Premier Partner serving over 1,400 customers, including several of the world's largest corporations, enabling them to effectively leverage Google Cloud Platform across industries and use cases. Onix specialises in Google Cloud Solutions such as generative AI, workload migrations, data & analytics, data infrastructure and visualisation, infrastructure services, application modernisation, collaboration & productivity, and location-based services. Onix is a 12-time Google Partner of the Year award winner and a Google Cloud Managed Services Partner. Summary: We are seeking a skilled and customer-focused AI/ML Solution Architect to join Onixs Solution Engineering team. This role blends deep technical expertise with presales acumen to architect, evangelise, and deliver cutting-edge AI and ML solutions on GCP and multi-cloud platforms. You will engage directly with clients in high-impact discussions, guiding them through the art of the possible with generative AI, MLOps, and cloud-native tools. As a key technical advisor, you will participate in strategic discovery sessions, lead solution ideation and architecture reviews , and collaborate closely with clients, sales, and engineering teams to shape transformational AI/ML initiatives. Your insights will help drive client success, showcase technical feasibility , and demonstrate business value through proofs of concept and impactful solution designs. Key Responsibilities: Partner with sales and customer engineering teams in presales engagements to identify AI/ML opportunities and craft tailored solution architectures. Design scalable, cloud-native AI/ML solutions primarily on Google Cloud Platform (GCP) leveraging tools like Vertex AI, LangChain, OpenAI APIs, and MLOps frameworks . Lead technical workshops, client demos, and architecture sessions to articulate value, drive alignment, and win stakeholder confidence. Review solution proposals across teams to ensure architectural integrity, scalability, and adherence to best practices . Stay ahead of the curve by assessing emerging GenAI tools and frameworks to validate new ideas and accelerate innovation . Required Qualifications: Bachelors degree in Computer Science, Engineering, or a related field; Master’s degree preferred. Extensive hands-on experience with cloud platforms , especially GCP (AWS and Azure exposure is a plus). Strong understanding of AI/ML tools and systems , including TensorFlow, PyTorch, Vertex AI, OpenAI, LangChain , and MLOps pipelines . 4–5 years of experience in data science, software development, or machine learning , with proficiency in languages like Python, Java, or JavaScript. Proven experience applying ML technologies to real-world industry use cases , with a solid grasp of data lifecycle and cloud deployment strategies. Exceptional client-facing communication and solution storytelling skills , with a track record in technical presales or consulting roles .

Job Title: GenAI Engineer (Senior/Lead) Industry: AI/ML, Enterprise Applications, Healthcare (if applicable) Role Summary: We are seeking an experienced GenAI Engineer to integrate LLM APIs, build AI-driven applications, optimize model performance, and deploy AI services at scale. The ideal candidate has expertise in Python-based AI development, LLM orchestration, cloud deployment, and enterprise AI integration. Key Responsibilities: AI Application Development: Build and maintain Python-based AI services using LangChain and CrewAI. Implement RAG-based retrieval and Agentic AI workflows. LLM Integration & Optimization: Integrate OpenAI, Bard, Claude, Azure OpenAI APIs. Optimize API calls using temperature, top-p, max tokens, and reduce hallucinations using embedding-based retrieval (FAISS, Pinecone). Model Evaluation & Performance Tuning: Assess AI models using Model Scoring, fine-tune embeddings, and enhance similarity search for retrieval-augmented applications. API & Microservices Development: Design scalable RESTful API services. Secure AI endpoints using OAuth2, JWT authentication, and API rate limiting. Cloud Deployment & Orchestration: Deploy AI-powered applications using AWS Lambda, Kubernetes, Docker, CI/CD pipelines. Implement LangChain for AI workflow automation. Agile Development & Innovation: Work in Scrum teams, estimate tasks accurately, and contribute to incremental AI feature releases. Tech Stack & Tools: AI/ML: PyTorch, TensorFlow, Hugging Face, Pinecone LLMs & APIs: OpenAI, LangChain, CrewAI Cloud & DevOps: AWS, Azure, Kubernetes, Docker, CI/CD Security & Compliance: OAuth2, JWT, HIPAA Preferred Qualifications: Experience with AI/ML, LLM integrations, and enterprise cloud solutions. Proven expertise in GenAI API orchestration, prompt engineering, and embedding retrieval. Strong knowledge of scalable AI architectures and security best practices. Notice Period - immediate to 45 days

Role & responsibilities Design robust and scalable AI/ML architectures that support the development and deployment of machine learning models and AI solutions. Develop and guide the implementation of end-to-end AI/ML solutions, including model development, data processing, and system integration. Evaluate and recommend the latest AI/ML technologies, frameworks, and tools to enhance system capabilities and performance. Collaborate with software engineers and other development teams to integrate AI/ML solutions into existing systems and applications. Ensure seamless operation and performance. Work with cross-functional teams, including developers, data scientists, machine learning engineers, and business stakeholders, to understand requirements and design solutions that align with business objectives. Create and maintain comprehensive documentation for AI/ML architectures, including design specifications, deployment procedures, and best practices. Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective Ensure that AI/ML systems comply with security standards and regulatory requirements. Implement best practices for data privacy and protection. Preferred candidate profile Bachelors degree in computer science, Data Science, Statistics, or a related field or a master's degree or higher is preferred. Total 10-15 years of industry experience More than 3 years of experience in designing and implementing AI/ML architectures, with a proven track record of successful projects. Extensive experience with machine learning frameworks (e.g., Go, TensorFlow, PyTorch), programming languages C#, .Net, NodeJS and data processing tools. Strong understanding of system architecture principles, including distributed systems, microservices, and cloud computing. Experience with Microsoft Azure cloud services and their AI/ML offerings Experience with event-handling systems such as Kafka Experience with big data technologies and data engineering practices. Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Job Description: Head of Center of Excellence for Artificial Intelligence At Jiobp, we believe Digital solutions and platforms are at the core of our customer experience, operational reliability, competitive differentiation and growth. At the core of our Digital strategy is setting up a Center of Excellence (CoE) for Artificial Intelligence. We are seeking an experienced Head of Center of Excellence (CoE) for Artificial Intelligence at Jiobp. The AI CoE Head will be expected to set up a CoE from scratch , including creating a vision , roadmap for AI adoption at scale, hiring required talent , mobilize the right technology platforms, drive identification of AI use cases , develop & deploy AI models and drive competency development of AI at scale within Jiobp. Additionally, he is expected to develop a network of partners in this space and drive innovation at scale by collaborating with other teams both within and outside the company. Experience: Around 14 + Years of experience of which last 7 -10 years have been in AI and Analytics Should have done AI Vision and Roadmap for a client or a company, Program management, Stakeholder management, Value realization. Most likely should have been a Data Scientist at some point of his/her career. Must have worked in executing AI use cases end to end including understanding of Business case, Architecture, Data Engineering, AI Model development, model, refinement and value realization. Should understand the various roles that are needed to run an AI CoE. Good to have consulting experience from BIG 4 or any other Tier 1 company in the related field. Strong Retail/ Consumer industry driven business knowledge and also AI use cases in this domain will be an advantage. Key Responsibilities: Set up the AI CoE including building the team from scratch, set up processes and methods for executing AI Use cases. Work with the CDO and advise him on emerging trends by exploring research papers, working with start-ups, develop key partnerships and applying cutting-edge technologies to create innovative solutions. Work with the CDO and create a compelling vision and multiyear AI Roadmap for Jiobp. Ensure use cases are identified in consultation with business, play a key role by educating the business on new possibilities using AI. Overall manage the AI Agenda for Jiobp to develop, enhance, and implement algorithms and models to address complex business challenges. Collaborate closely with project teams, customer stakeholders, and internal business units to devise creative analytical approaches for solving both technical and business challenges. Guide the team on complex use cases and solutions. Ensure clear and effective communication by producing high-quality documentation and presentations. Required Skills and Qualifications: Strong proficiency in deep learning techniques, neural networks, and machine learning algorithms. Good understanding of Image and Video Analytics, conversational AI and Generative AI. Experience in applying deep learning to structured and unstructured data for solving real-world challenges. Expertise in deploying and optimizing machine learning and deep learning models in production environments. Excellent written and verbal communication skills for technical documentation, reports, and client presentations. Educational background B Tech/ MCA B Tech + M Tech M.Stat/B.Stat M.Sc Mathematics / M. Sc Physics

Mandatory Skills Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup. Experience in designing and implementing machine learning models using scikit-learn and TensorFlow. Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch. Cloud AI services experience, particularly in AWS SageMaker and AWS Bedrock. MLOps & DevOps: Knowledge of data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes). API Development: Ability to develop and maintain APIs following RESTful principles. Technical proficiency in Elastic, Python, YAML, and system integrations. Nice to Have skills - Experience with Observability, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.

Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 4 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: 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, Agentic Framework 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 4 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 Utilize optimization tools and techniques, including MIP (Mixed Integer Programming. Deep knowledge of classical AIML (regression, classification, time series, clustering) Drive DevOps and MLOps practices, covering CI/CD 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.

Role & responsibilities : Key Responsibilities: We are seeking a highly skilled and motivated AI Engineer to join our team. In this role, you will leverage your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions that enhance business processes and deliver value to our clients. Candidates must have extensive experience in the Microsoft environment and be experts in Microsoft CoPilot and related technologies. You will collaborate with cross-functional teams to create innovative solutions using Microsoft tools and platforms. Responsibilities: Agent Development: Design, implement, and optimize AI agents using Microsoft CoPilot and related technologies. Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration: Deploy AI solutions within client environments, ensuring scalability and seamless integration with existing systems. Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation: Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support: Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement: Stay updated on advancements in AI, machine learning, and Microsofts AI technologies. Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills: Strong knowledge of Microsoft Power Automate, Azure AI, and CoPilot features. Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. Understanding of conversational AI technologies and chatbot frameworks. Experience with data analysis tools and techniques to uncover insights and optimize models.

Job Title Senior AI ML Engineer Location : Pune, India About Springer Nature Group Springer Nature opens the doors to discovery for researchers, educators, clinicians, and other professionals. Every day, around the globe, our imprints, books, journals, platforms, and technology solutions reach millions of people. For over 175 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood, and used by our communities enabling them to improve outcomes, make progress, and benefit the generations that follow. About Us Springer Nature AI Labs work on building innovative solutions to accelerate discovery and scientific progress for the research community. Along with researchers, we also help internal Springer Nature teams in integrating AI solutions in their products for a state-of-the-art experience. Our task here is to understand the pain points of our customers, develop problem statements together with them and come up with the most innovative, cost effective and scalable solution. Our team is responsible for staying up to date with the latest technology trends in the field of AI and GenAI. We conduct experiments to validate their implications and applications at Springer Nature. About the Role The purpose of the AIML Engineer role at Springer Nature is to enhance the publishing cycle using advanced AI and ML skills. This role focuses on improving operational efficiency and decision-making by developing and deploying AI/ML solutions to streamline processes, improve data accuracy, and enable new capabilities. Key responsibilities include staying updated on AI/ML trends, ensuring system scalability and reliability, improving data quality, detailed data analysis, enhancing user experience, and driving business insights. Key Responsibilities Develop end-to-end AI/ML solutions, from data collection and preprocessing to model development, deployment, and maintenance. Collaborate with data scientists to preprocess data and create features for model training. Implement and maintain AI infrastructure, including data pipelines and model deployment systems. Evaluate and compare different AI/ML models to select the most appropriate ones for specific tasks. Develop and deploy machine learning models. Optimize model performance and scalability for production environments. Research and experiment with new AI technologies to drive innovation. Communicate findings and insights to non-technical stakeholders through data visualization and storytelling. Apply machine learning, deep learning, Gen AI techniques to solve complex problems in areas such as natural language processing, computer vision, and predictive analytics. Monitor and maintain deployed models, including retraining and updating them as needed. Within 3 Months: Onboarding time, learning that things exist and working on simple tasks/tickets. Get familiar with Springer Nature's technology stack, including AI/ML frameworks and cloud platforms (Google Cloud). Begin developing and deploying AI/ML models under the guidance of senior team members. Participate in team agile processes and ceremonies, including daily stand-ups, planning, and retrospectives. Collaborate with data scientists to preprocess data and create features for model training. Share insights and opinions on building scalable and reliable AI/ML solutions. By 3-6 Months: Getting used to things, overview of the projects, and start working on it independently Become an active contributor to AI/ML solution development, focusing on optimizing model performance and scalability for production environments. Help improve AI infrastructure, including data pipelines and model deployment systems. Develop a solid understanding of Springer Nature's editorial processes and how AI/ML solutions can enhance operational efficiency. Engage in technical discussions with the team to improve product architecture and code quality. Communicate findings and insights to non-technical stakeholders through data visualization and storytelling. By 6-12 Months: Add value to products using the tools Lead the development and deployment of machine learning models and ensure their ongoing performance and scalability. Research and experiment with new AI technologies to drive innovation within the team. Onboard new team members and support their integration into the team’s agile processes. Participate in blameless post-mortems to identify and implement improvements. Proactively provide feedback and coaching to junior members of the team. Advocate for defining and implementing non-functional requirements and influence the design of the system architecture. Engage in user research to better understand the needs of researchers and other users of Springer Nature’s platforms. Required Qualifications/ About You Bachelor's or master's degree in computer science, Engineering, or related field. 6+ years of experience in AI/ML engineering, with a strong understanding of machine learning algorithms and deep learning frameworks Proficiency in programming languages such as Python, R and Data structures, Algorithms. Strong understanding of machine learning concepts and algorithms. Experience with software engineering practices and methodologies, including version control, testing, and deployment. Excellent problem-solving and data analytical skills. Effective communication and teamwork skills. Experience in Generative AI, LLM, building RAG applications, model optimization. Hands on experience in NLP or Computer Vision. Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for deploying AI/ML Having a good command of English is important; collaboration is important in our day to day work, so being able to communicate your ideas and understand others’ is key.For all roles in all locations, we offer a competitive, industry-benchmarked salary. What we offer The global setup of the team and the organization, our complex system and environment and its variety are giving a chance to further develop yourself while working with team members around the globe, and international stakeholders. At Springer Nature, we value the diversity of our teams and work to build an inclusive culture, where people are treated fairly and can bring their differences to work and thrive. We empower our colleagues and value their diverse perspectives as we strive to attract, nurture and develop the very best talent. Springer Nature was awarded Diversity Team of the Year at the 2022 British Diversity Awards. Find out more about our DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion If you have any access needs related to disability, neurodivergence or a chronic condition, please contact us so we can make all necessary accommodation. For more information about career opportunities in Springer Nature please visit https://springernature.wd3.myworkdayjobs.com/SpringerNatureCareers #LI-HD1

We are hiring for top "MNC". "Urgent requirement" of Gen AI / Open AI Interested candidates can share their resume on ritu.aggarwal@thehrsolutions.in or can contact on 9220708560 / 8130178358 . Location : Pan India Experience : 4 or 4+ years Mandatory Skills : Generative AI, Chat GPT, Chat BOT, AI ML, Azure Role Overview: We are seeking a skilled OpenAI Developer to join our dynamic team. The ideal candidate will have a robust understanding of AI and machine learning, with particular expertise in integrating OpenAI models with Microsoft's Power Platform, including Power Automate and Power Virtual Agents, and Azure cognitive services. Key Responsibilities: Develop, implement, and optimize OpenAI models for various applications, including chatbots and customer support. Integrate OpenAI models with Power Automate for streamlined workflows and Power Virtual Agents for enhanced user interaction. Design and develop backend services using Python or .NET to support OpenAI-powered solutions. Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services to extend functionality and improve AI solutions. Regularly review and fine-tune OpenAI models to ensure maximum accuracy and relevance for custom datasets. Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Stay updated with the latest advancements in OpenAI and Azure services to bring innovation to our solutions. Required Skills and Experience: Bachelor's degree in Computer Science, Engineering, or a related field. Proficient in Python and/or .NET for backend development. Experience with OpenAI GPT models and their applications. Hands-on experience with Microsoft Power Automate and Power Virtual Agents. Familiarity with Azure cognitive services. Strong understanding of machine learning concepts, including model training, fine-tuning, and evaluation. Good knowledge of Natural Language Processing (NLP) techniques. Ability to work in a team-oriented environment and deliver on tight deadlines. Excellent problem-solving and analytical skills. Experience with Google Cloud Build, Jenkins or other similar CI/CD tools Desirable Skills: Master's degree or further education in AI, machine learning, or a related field. Previous experience in customer support or chatbot development. Certifications in Microsoft Azure or OpenAI technologies. Role & responsibilities

We are recruiting for 100+ AI/ ML/ Data Science/ NLP SM/ Managers/ Architects and engineers for our Client which is a Fortune 500 IT MNC for Hyederabad, Bangalore, Mumbai, Pune, Chennai, Pune, Kolkata, Gurgaon, Jaipur etc. Exp. 4 to 20 yrs.

Data Scientist - Python R Expertise Location - Bangalore Exp- 6 to 10 years Key Responsibilities: Develop machine learning and statistical models for various business needs, including regression, classification, and time series analysis. Implement models using Python and relevant libraries such as scikit-learn, pandas, and numpy. Apply machine learning techniques such as Linear Regression, Random Forest, Classification, and Ensemble methods. Convert R code to Python and ensure seamless integration between the two languages. Utilize R for data manipulation and analysis using tidyverse, dplyr, and data.table. Optimize and enhance existing R code for performance and scalability. Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions. Follow best practices in software engineering to produce clean, manageable and testable code. Stay updated with the latest industry trends and advancements in data science and machine learning. Required Skills and Qualifications: Bachelors or Master’s degree in Computer Science, Statistics, Data Science, or a related field. 6+ years of IT experience with a min of 3+ years in Data Science (AI/ML) Proven experience as a Data Scientist or similar role with hands-on experience in Python and R. Strong knowledge of machine learning algorithms and statistical modeling techniques. Proficiency in Python libraries such as scikit-learn, pandas, numpy, and matplotlib. Expertise in R programming, particularly with tidyverse, dplyr, tidymodels, and data.table. Experience with relational databases and SQL. Ability to convert R code to Python efficiently. Familiarity with software engineering principles and best practices. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Ability to manage multiple projects and meet deadlines. .

Job Title AI ML Engineer Location : Pune, India About Springer Nature Group Springer Nature opens the doors to discovery for researchers, educators, clinicians, and other professionals. Every day, around the globe, our imprints, books, journals, platforms, and technology solutions reach millions of people. For over 175 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood, and used by our communities – enabling them to improve outcomes, make progress, and benefit the generations that follow. About Us Springer Nature AI Labs work on building innovative solutions to accelerate discovery and scientific progress for the research community. Along with researchers, we also help internal Springer Nature teams in integrating AI solutions in their products for a state-of-the-art experience. Our task here is to understand the pain points of our customers, develop problem statements together with them and come up with the most innovative, cost effective and scalable solution. Our team is responsible for staying up to date with the latest technology trends in the field of AI and GenAI. We conduct experiments to validate their implications and applications at Springer Nature. About the Role The purpose of the AIML Engineer role at Springer Nature is to enhance the publishing cycle using advanced AI and ML skills. This role focuses on improving operational efficiency and decision-making by developing and deploying AI/ML solutions to streamline processes, improve data accuracy, and enable new capabilities. Key responsibilities include staying updated on AI/ML trends, ensuring system scalability and reliability, improving data quality, detailed data analysis, enhancing user experience, and driving business insights. Key Responsibilities Develop end-to-end AI/ML solutions, from data collection and preprocessing to model development, deployment, and maintenance. Collaborate with data scientists to preprocess data and create features for model training. Implement and maintain AI infrastructure, including data pipelines and model deployment systems. Evaluate and compare different AI/ML models to select the most appropriate ones for specific tasks. Develop and deploy machine learning models. Optimize model performance and scalability for production environments. Research and experiment with new AI technologies to drive innovation. Communicate findings and insights to non-technical stakeholders through data visualization and storytelling. Apply machine learning, deep learning, Gen AI techniques to solve complex problems in areas such as natural language processing, computer vision, and predictive analytics. Monitor and maintain deployed models, including retraining and updating them as needed. Within 3 Months: Onboarding time, learning that things exist and working on simple tasks/tickets. Get familiar with Springer Nature's technology stack, including AI/ML frameworks and cloud platforms (Google Cloud). Begin developing and deploying AI/ML models under the guidance of senior team members. Participate in team agile processes and ceremonies, including daily stand-ups, planning, and retrospectives. Collaborate with data scientists to preprocess data and create features for model training. Share insights and opinions on building scalable and reliable AI/ML solutions. By 3-6 Months: Getting used to things, overview of the projects, and start working on it independently Become an active contributor to AI/ML solution development, focusing on optimizing model performance and scalability for production environments. Help improve AI infrastructure, including data pipelines and model deployment systems. Develop a solid understanding of Springer Nature's editorial processes and how AI/ML solutions can enhance operational efficiency. Engage in technical discussions with the team to improve product architecture and code quality. Communicate findings and insights to non-technical stakeholders through data visualization and storytelling. By 6-12 Months: Add value to products using the tools Lead the development and deployment of machine learning models and ensure their ongoing performance and scalability. Research and experiment with new AI technologies to drive innovation within the team. Onboard new team members and support their integration into the team’s agile processes. Participate in blameless post-mortems to identify and implement improvements. Proactively provide feedback and coaching to junior members of the team. Advocate for defining and implementing non-functional requirements and influence the design of the system architecture. Engage in user research to better understand the needs of researchers and other users of Springer Nature’s platforms. Required Qualifications/ About You Bachelor's or master's degree in computer science, Engineering, or related field. 3+ years of experience in AI/ML engineering, with a strong understanding of machine learning algorithms and deep learning frameworks Proficiency in programming languages such as Python, R and Data structures, Algorithms. Strong understanding of machine learning concepts and algorithms. Experience with software engineering practices and methodologies, including version control, testing, and deployment. Excellent problem-solving and data analytical skills. Effective communication and teamwork skills. Experience in Generative AI, LLM, building RAG applications, model optimization. Hands on experience in NLP or Computer Vision. Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for deploying AI/ML Having a good command of English is important; collaboration is important in our day to day work, so being able to communicate your ideas and understand others’ is key.For all roles in all locations, we offer a competitive, industry-benchmarked salary. What we offer The global setup of the team and the organization, our complex system and environment and its variety are giving a chance to further develop yourself while working with team members around the globe, and international stakeholders. At Springer Nature, we value the diversity of our teams and work to build an inclusive culture, where people are treated fairly and can bring their differences to work and thrive. We empower our colleagues and value their diverse perspectives as we strive to attract, nurture and develop the very best talent. Springer Nature was awarded Diversity Team of the Year at the 2022 British Diversity Awards. Find out more about our DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion If you have any access needs related to disability, neurodivergence or a chronic condition, please contact us so we can make all necessary accommodation. For more information about career opportunities in Springer Nature please visit https://springernature.wd3.myworkdayjobs.com/SpringerNatureCareers #LI-HD1

Role & responsibilities Key Responsibilities: Develop and implement machine learning models to solve complex business problems. Collaborate with data scientists and analysts to understand business requirements and translate them into technical solutions. Perform data preprocessing, feature engineering, and model evaluation to ensure high-quality outcomes. Utilize data science techniques to analyze and interpret large datasets, providing actionable insights. Work with cross-functional teams to integrate machine learning models into production systems. Stay up-to-date with the latest advancements in AI, ML, and data science technologies and methodologies. Document processes, methodologies, and results to ensure knowledge sharing and continuous improvement. Qualifications: Proven experience as an AI/ML Engineer with exposure to data science. Strong programming skills in languages such as Python, R, or Java. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Proficiency in data manipulation and analysis using tools like Pandas, NumPy, or SQL. Excellent problem-solving skills and the ability to work independently and collaboratively. Strong communication skills to convey complex technical concepts to non-technical stakeholders.

In-depth knowledge of machine learning algorithms and their applications including practical experience with and theoretical understanding of algorithms for classification, regression and clustering. Hands-on experience in computer vision and deep learning projects to solve real world problems involving vision tasks such as object detection, Object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation etc. Strong understanding of modern and traditional Computer Vision Algorithms. Experience in one of the Deep Learning Frameworks / Networks: PyTorch, TensorFlow, Darknet(YOLO v4 v5), U-Net, Mask R-CNN, EfficientDet, BERT etc. Proficiency with CNN architectures such as ResNet, VGG, UNet, MobileNet, pix2pix, and CycleGAN. Experienced user of libraries such as OpenCV, scikit-learn, matplotlib and pandas. Ability to transform research articles into working solutions to solve real-world problems. High proficiency in Python programming knowledge. Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools). Strong communication skills.

Role & responsibilities We are looking for Data Scientist position with US MNC company for permanent role, Remote. Preferred candidate profile Mandatory Skills : 5 Years + relevant experience in data science. Experience in RAG implementation pipeline. Experience with AI/ML Frameworks like TensorFlow, PyTorch, or similar. Proficiency in Programming Languages such as Python, SQL, and other relevant languages. Experience in the Financial Services Industry and an understanding of compliance standards. (Preferred) Experience with Master data management, Data Wrangling and ETL Processes. Experience with data and AI/ML Technologies: Such as NLP/NLU, Azure Cognitive Services, Azure Synapse Analytics, Azure data bricks and Azure ML service. Certification in Data Science or AI/ML.

We are seeking a AI Product Manager to take ownership of defining, building, and scaling our core products. In this role, you will act as the bridge between technical teams (engineering, AI/ML) and business stakeholders.

Hiring for No-1 IT MNC for HRO Transformation for Mumbai Salary Up-to -65LPA Min -15 + Yrs Of exp in HRO Outsourcing Industry with at least 8+yrs in managing large HR Transformation & HR technology platforms Exp. Call@WhatsApp- Kajal - 8595849767

Should be comfortable Traveling USA and other Client locations and Stay for 3-4 months in a year. This is a key Technology leadership role envisioned to be a Chief Technology Architect leveraging our Key Strategic Priorities. This person will Leverage technical expertise, business acumen and fluid communication skills to translate the possible into reality. The candidate will be able to design solutions that span multiple platforms and include integration and authentication across systems, articulate design considerations, trade-offs, benefits, and recommendations. The potential candidate should have the ability to drive global client meetings across multiple technology stacks, manage the architecture solution implementation, and build trusted relationship with clients. Responsible for setting up and scaling ACIs Technology and Domain Centers of Excellence to expand our practices and deliver tangible value to our global clients Specific Responsibilities include: Execute technology vision aligned to the Organization roadmap for exponential growth Influence, enable, and scale our delivery roles and teams across to ensure consistent and high-quality delivery. Look for opportunities to scale efficiencies and new ways of working across multiple projects and environments. Engage customer organizations at the C-level, helping clients drive enterprise-wide agenda across multiple technology stacks Track and control the developments for annual operating and capital budgets for purchasing, staffing, and technology operations. Lead efforts to bring continuity to our Salesforce and SAP engagement management and delivery methodology to all practitioners globally. Engage directly with senior client stakeholders to Support sales pre-sales activities by assessing opportunities, responding to RFPs, creating proposals and presentations, establishing relationships with clients and prospective clients, and helping to close sign new deals Lead Practice development, driving and orchestrating transformation and client solutions, teams, strategic roadmaps, and continuous improvement/optimization programs Establish and cultivate strong relationships with clients at senior levels as well as external and internal partners to maximize growth within an account/client portfolio Develop effective relationships with key internal executives, BU heads, Account Managers, Solution SMEs, and Sales leaders Partner across a highly matrixed technology consulting services and solutions organization to define, implement and deliver innovative Modern Application Transformation solutions for ACIs clients to successful outcomes. Develop client roadmaps, program building, incorporating intelligent processes and solution planning that drives our clients desired business outcomes. Create and maintain thorough architectural and design documentation for ACIs client solution platforms. Create and maintain an extensible cloud-based architecture that assure agile response to market needs of future features and capabilities. Establish key partnerships with technical leadership and most experienced and respected engineers on the client-side and articulate a strategic technical vision Collaborate with ACIs leadership to build an environment of collective responsibility and accountability. Learn specifics of the customers Business Architecture, Application Architecture, Infrastructure Architecture and Data Architecture and take all of them into account while designing solutions Create ideas that can improve business capabilities or introduce new ones for our customers Understand the market for new practices and technologies that may result in competitive advantage or improved ways of working. Deliver customer experience to enhance and retain CSAT above 95%, increase business sustenance and life while helping to increase ACV. Requirements 15+ years experience in multiple technologies (cross-stack) and have a deep understanding of business domains, technical stacks, programming languages, environments, and managed cloud services Deep domain expertise of cloud application development solutions (e.g. PaaS, Serverless, API Management), container orchestration (e.g. Kubernetes, Cloud Foundry), continuous integration technologies (e.g. Jenkins, Spinnaker, Azure for DevOps), web application server technologies, cloud application design, software architecture and practices (design/development/deployment, Agile, SCRUM), breadth of technical experience, and technical aptitude to learn and adjust to new technologies and cloud trends The ability to quickly acquire knowledge, go beyond current technical competencies to work with previously unknown tools and/or techniques Experience with marketing automation, analytics, and CRM systems to deliver real time client results to our clients' platforms. Understanding of infrastructure scalability, accessibility, and user interfaces. Exceptional management skills with direct experience in managing multiple client delivery projects. Cloud Platforms (Amazon Web Services (AWS), Azure, GCP); SAP Stack including S/4 HANA & C/4 HANA Salesforce Stack DevOps, Automation CI/CD Customer Experience: AEM, Commerce Cloud ServiceNow Data & Analytics in the cloud API, Microservices and Integration Note : Interested professionals can share their resume to raghav.b@aciinfotech.com +91-9985737316