Top Machine Learning Jobs in India
As a Data Engineer at S&P Global, you'll design and maintain a data infrastructure essential for analytics and machine learning. Your role includes collaborating with stakeholders, building data pipelines, ensuring data compliance and quality, and optimizing algorithms for data-driven solutions.
As a Fullstack Engineer, you will design, develop, and deploy a scalable machine learning platform software to support data scientists in building and monitoring ML solutions. This role requires knowledge of AL/ML and practical experience in the machine learning lifecycle, focusing on high code quality and performance.
As a technical lead at PayPal, you will drive the development of the Enterprise AIML platform, focusing on innovation and customer-centric solutions. Your responsibilities include guiding AI/ML discussions, overseeing architecture and implementation, and mentoring team members to ensure project success.
The Senior IT Application Support Engineer will monitor, troubleshoot, and maintain applications on cloud services. This role involves incident management, providing technical leadership, and engaging with clients to resolve issues quickly. The candidate will work closely with engineering teams and product owners to enhance digital platforms and ensure reliability and performance.
Join Iron Mountain as a ML Engineer - Senior Software Engineer with 0-4 years experience in machine learning/data science. Required skills include Python, DL, NLP, GenAI, and prompt engineering. Experience with Kubeflow, mlflow, and performance tuning is desirable. Knowledge of MLOps/Data Engineering is a plus. Full job description in the job details.
The SAP ABAP Developer will design, develop, and enhance complex software solutions. Responsibilities include coding, testing, and debugging new software, promoting coding standards, mentoring teams, and interacting with various stakeholders to address project needs.
Seeking a Senior Data Scientist with strong technical foundation in data science and machine learning. Responsible for implementing machine learning models, data enrichment, feature selection, model evaluation, and deployment. Collaborate with product, sales, and engineering teams to shape the final solution. Attend client meetings to discuss solutions and provide insights.
The Lead Software Engineer will focus on optimization problems across business units using advanced methods such as genetic algorithms and simulated annealing. Responsibilities include designing optimization algorithms, collaborating with stakeholders to model business challenges, conducting data analysis, and leading architecture and code reviews to ensure quality solutions. The role promotes cloud-native and microservices architectures.
Featured Jobs
The Lead Senior Analyst will monitor data quality, develop dashboards, analyze data issues, implement data quality strategies, and ensure adherence to data governance standards while collaborating with various business functions.
The Associate in the BGM AI Center of Excellence will be responsible for developing AI capabilities by researching language models, building ML components, and driving AI initiatives within the organization. They will partner with various teams to create use cases and tools, and help integrate AI strategies into production workflows.
The role involves designing, developing, and executing testing strategies for software functionality, performance, and user experience. Responsibilities include implementing test plans, creating automated test scripts, collaborating with teams on requirements, conducting root cause analyses for defects, and participating in code reviews to promote quality.
As an AI/ML Test Automation Analyst, you will design and implement testing strategies, develop automated test scripts, and collaborate with cross-functional teams to ensure software quality. You will engage in root cause analysis of defects and participate in code reviews, while also contributing to continuous improvement in testing processes.
Design, develop, and improve software solutions by collaborating with product managers and engineers, ensuring scalable and secured code while adhering to industry standards. Responsible for contributing to technology communities and promoting code quality and knowledge sharing.
The Manager of Software Development will lead a team in enhancing wafer inspection products using advanced technology and software practices. Responsibilities include driving technical decisions, improving software for high-volume production, and leveraging machine learning to enhance performance.
The Financial Crime Data Analyst will implement data quality processes, conduct investigations related to data issues, execute cleansing and transformation tasks, and design automated data pipelines. The role also involves applying advanced analytics techniques to solve business problems and documenting findings.
The Specialist in Algorithm R&D will design and develop machine learning software solutions for semiconductor metrology, working with customers to define requirements, optimizing algorithms, implementing API solutions, writing unit tests, and documenting work.
As a Senior ML Engineer at Zuora, you will leverage AI technologies to enable monetization across platforms. Your role involves identifying opportunities, collaborating with stakeholders, building end-to-end ML models, and ensuring model effectiveness and maintenance in production while delivering tangible business results.
The Senior Data Scientist will develop analytic solutions utilizing statistical and data science techniques while communicating insights across various products and markets. This role involves data ingestion, aggregation, and processing to support strategic decision-making and product evolution.
Manager role at Mastercard focusing on architecting, developing, and maintaining advanced reporting and data visualization capabilities for data insights and analytical needs. Responsibilities include building solutions using Machine Learning, creating actionable insights, and driving the evolution of products with a focus on data science and engineering.
The Specialist role at Mastercard involves architecting, developing, and maintaining advanced reporting and data visualization capabilities. The candidate will focus on building solutions using Machine Learning, creating actionable insights, and driving product optimization and sales enablement through data science and engineering.
Lead Software Engineer role at Mastercard focusing on providing technical vision and leadership, participating in team prioritization discussions, automating build and deployment processes, driving code/design trade-off discussions, and mentoring team members. Required skills include AI-ML, Python, Java, Scala, Pandas, Spring boot, MLOPs, CICD, Jenkins, and API.
The role focuses on developing a cutting-edge AI platform to enhance developer productivity, utilizing advanced code generation, intelligent suggestions, and automated testing. Key responsibilities include improving code quality, optimizing infrastructure, and streamlining workflows through AI-driven tools. The role also involves collaboration with cross-functional teams to drive innovation in software development.
Lead an engineering team to build and innovate analytics solutions using Big Data and other technologies, ensuring scalable applications. Collaborate with cross-functional teams while mentoring engineers and advocating for technical excellence.
As a UI Engineer on the Hyperforce Developer Experience team, you will design and develop user-friendly interfaces for AI-powered tools, aiming to enhance developer productivity and experience. Your responsibilities include creating intuitive interfaces, optimizing AI models, and ensuring seamless integration with development workflows.
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The GenAI Architect at Nisum is responsible for leveraging expertise in AI, Generative AI, LLM, Machine Learning, and data science to guide teams through technical problems and deliver business impact. The role involves a strong focus on scalability, performance, and hands-on implementation of AI solutions in real-world scenarios.
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