6 Ml.Net Jobs

About Motadata Motadata is a renowned IT monitoring and management software company that has been transforming how businesses manage their ITOps since its inception. Our vision is to revolutionize the way organizations extract valuable insights from their IT networks. Bootstrapped since inception, Motadata has built up a formidable product suite comprising cutting-edge solutions, empowering enterprises to make informed decisions and optimize their IT infrastructure. As a market leader, we take pride in our ability to collect and analyze data from various sources, in any format, providing a unified view of IT monitoring data. Position Overview We are seeking a Senior Machine Learning Engineer to join our team, focused on enhancing our AIOps and IT Service Management (ITSM) product through the integration of cutting-edge AI/ML features and functionality. As part of our innovative approach to revolutionizing the IT industry, you will play a pivotal role in leveraging data analysis techniques and advanced machine learning algorithms to drive meaningful insights and optimize our product's performance. With a particular emphasis on end-to-end machine learning lifecycle management and MLOps, you will collaborate with cross-functional teams to develop, deploy, and continuously improve AI-driven solutions tailored to our customers' needs. From semantic search and AI chatbots to root cause analysis based on metrics, logs, and traces, you will have the opportunity to tackle diverse challenges and shape the future of intelligent IT operations. Role & Responsibility Lead the end-to-end machine learning lifecycle, understand the business problem statement, convert into ML problem statement, data acquisition, exploration, feature engineering, model selection, training, evaluation, deployment, and monitoring (MLOps). Should be able to lead the team of ML Engineers to solve the business problem and get it implemented in the product, QA validated and improvise based on the feedback from the customer. Collaborate with product managers to understand business needs and translate them into technical requirements for AI/ML solutions. Design, develop, and implement machine learning algorithms and models, including but not limited to statistics, regression, classification, clustering, and transformer-based architectures. Preprocess and analyze large datasets to extract meaningful insights and prepare data for model training. Build and optimize machine learning pipelines for model training and inference using relevant frameworks. Fine-tune existing models and/or train custom models to address specific use cases. Enhance the accuracy and performance of existing AI/ML models through monitoring, iterative refinement and optimization techniques. Collaborate closely with cross-functional teams to integrate AI/ML features seamlessly into our product, ensuring scalability, reliability, and maintainability. Document your work clearly and concisely for future reference and knowledge sharing within the team. Stay ahead of latest developments in machine learning research and technology and evaluate their potential applicability to our product roadmap. Skills And Qualifications Bachelor's or higher degree in Computer Science, Engineering, Mathematics, or related field. Minimum 5+ years of experience as a Machine Learning Engineer or similar role. Proficiency in data analysis techniques and tools to derive actionable insights from complex datasets. Solid understanding and practical experience with machine learning algorithms and techniques, including statistics, regression, classification, clustering, and transformer-based models. Hands-on experience with end-to-end machine learning lifecycle management and MLOps practices. Proficiency in programming languages such as Python and familiarity with at least one of the following : Java,Golang, .NET, Rust. Experience with machine learning frameworks/libraries (e.g. , TensorFlow, PyTorch, scikit-learn) and MLOps tools (e.g. , MLflow, Kubeflow). Experience with ML.NET and other machine learning frameworks. Familiarity with natural language processing (NLP) techniques and tools. Excellent communication and teamwork skills, with the ability to effectively convey complex technical concepts to diverse audiences. Proven track record of delivering high-quality, scalable machine learning solutions in a production environment. (ref:hirist.tech)

Architecture Design & Strategy: Define and implement the overarching AI/ML technology architecture, ensuring alignment with business goals and Agentic AI initiatives. Select and evaluate appropriate AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, ML.NET) and cloud platforms (AWS, Azure, GCP) based on project requirements and computational efficiency. Design scalable data pipelines for efficient data ingestion, processing, feature engineering, and model training. Develop and implement model deployment strategies, including cloud-based deployment and edge computing solutions. Establish architectural standards and best practices for AI/ML development. Location - Pan India Experience - 12 yrs minimum to 18 yrs Show more Show less

Proficient with the .NET framework & .NET Core Strong understanding of object-oriented programming Familiar with various design and architectural patterns Understanding fundamental design principles behind a scalable application Proficient with WPF Proficient in C#, with a good knowledge of its ecosystems Skill for writing reusable C# libraries Knowledge of concurrency patterns in C# Proficient with Microsoft SQL Server or Oracle Creating database schemas that represent and support business processes Proficient understanding of code versioning tool Git. Proficient with continuous integration and Deployment Familiarity with ASP.NET/BLAZOR/MAUI are added advantage Familiarity with Azure Repo & Azure Pipeline are added advantage Familiarity with ML.NET is added advantage Show more Show less

Company Description ShuffleLabs is a trusted partner for integration solutions, delivering excellent products and exceptional customer service. The flagship platform ShuffleExchange connects applications using APIs, simplifies integration development with visual tools, and makes implementation easy. ShuffleExchange provides simplicity and ease of use for complex integration needs. Role Description This is a full-time on-site role in Chennai for a Technical Lead at ShuffleLabs. The Technical Lead will be responsible for leading technical teams, designing and implementing software solutions, providing technical guidance, and ensuring project success through effective leadership and problem-solving. Roles & Responsibilities Architect and deliver iPaaS solutions that enable seamless integration between cloud, on-premise, and hybrid systems using modern technologies and enterprise best practices. Lead end-to-end solution design, ensuring robust data integration patterns (event-driven, pub-sub, messaging queues, ETL, API orchestration). Collaborate with cross-functional teams, product managers, and integration engineers to define technical roadmaps and align architecture with business goals. Incorporate AI/ML components into integration workflows for intelligent automation, data transformation, anomaly detection, and predictive routing. Define and implement scalable cloud integration strategies leveraging Microsoft Azure services (Logic Apps, Azure Functions, Event Grid, API Management). Guide integration architecture design, performance optimization, security protocols (OAuth2, OpenID Connect, API security), and SLA compliance. Evaluate and select iPaaS tools, integration frameworks, and middleware platforms aligned with customer needs and future scalability. Mentor development teams, enforce engineering standards, lead code and design reviews, and promote DevOps and CI/CD best practices. Produce architecture artifacts, technical specifications, white papers, and reusable design patterns for internal and client use. Lead cloud migration initiatives and legacy modernization efforts, especially for enterprise integration systems. Experience with hybrid and multi-cloud integration scenarios Core Technical Skills iPaaS / Integration Expertise: Integration patterns: RESTful/SOAP APIs, file-based transfers, message queues, ETL pipelines, webhooks Experience with iPaaS platforms: Azure Logic Apps , MuleSoft , Dell Boomi , Informatica , SnapLogic , or Workato (experience with Azure preferred) Strong knowledge of Azure Integration Services : Logic Apps, API Management, Service Bus, Event Grid, Azure Functions, Data Factory Microsoft Stack: .NET Core / .NET 6+, ASP.NET MVC, C#, Entity Framework, Web API Azure PaaS services (App Services, Azure SQL, Azure Cosmos DB, Azure Blob Storage) Experience with database design, normalization, and data modeling in SQL Server environments Power Platform (Power Automate, Power BI, Power Apps) knowledge is a plus DevOps & Cloud Infrastructure: Azure DevOps, CI/CD pipelines, ARM/Bicep templates, GitHub Actions, Jenkins Kubernetes (AKS), Docker, Terraform, Ansible Azure Monitoring, App Insights, and Log Analytics for integration health checks and diagnostics AI & Intelligent Integration Skills Integrate AI into iPaaS pipelines using Azure Cognitive Services , OpenAI APIs , or ML.NET for: Data extraction/classification from unstructured sources (OCR, NLP) Smart routing and workflow recommendations Predictive analytics and anomaly detection Intelligent chatbots and virtual assistants for API support Experience with AI-enriched integration use cases: RAG pipelines, auto-mapping schemas, adaptive decision-making, intelligent data validation Familiarity with vector databases (e.g., Pinecone, FAISS) and semantic search to enhance knowledge workflows Understanding of MLOps practices and integration of AI lifecycle into CI/CD pipelines Contribution to open-source integration or AI tools Soft Skills & Leadership Strategic thinker with deep technical expertise and strong business acumen in the iPaaS space Excellent communication skills with the ability to translate complex technical concepts into business terms Collaborative leader experienced in mentoring cross-functional engineering teams Strong problem-solving, prioritization, and project planning abilities in fast-paced, evolving environments Qualifications & Experience M.C.A. / B.E. / B. Tech in Computer Science or related field from a reputed institute Minimum 9+ years of experience in IT, with 3+ years in architectural or lead roles focused on integration technologies Proven experience designing and deploying enterprise-scale integration solutions using Microsoft Azure Experience implementing AI-driven features in cloud or integration platforms is highly desirable Certifications in Microsoft Azure (Architect, DevOps Engineer, AI Engineer) or iPaaS platforms are a strong plus Show more Show less

Proficient with the .NET framework & .NET Core Strong understanding of object-oriented programming Familiar with various design and architectural patterns Understanding fundamental design principles behind a scalable application Proficient with WPF Proficient in C#, with a good knowledge of its ecosystems Skill for writing reusable C# libraries Knowledge of concurrency patterns in C# Proficient with Microsoft SQL Server or Oracle Creating database schemas that represent and support business processes Proficient understanding of code versioning tool Git. Proficient with continuous integration and Deployment Familiarity with ASP.NET/BLAZOR/MAUI are added advantage Familiarity with Azure Repo & Azure Pipeline are added advantage Familiarity with ML.NET is added advantage Show more Show less

We are looking for a motivated and enthusiastic .NET Developer with 0 to 2 years of experience to join our growing team at Equitec. As a .NET Developer, you will be involved in developing, maintaining, and optimizing software applications using Microsoft technologies. You will have the opportunity to work with AI technologies and contribute to the integration of AI-driven features into our solutions. You will work closely with cross-functional teams to create high-quality, scalable applications while learning and growing in the exciting field of Artificial Intelligence. Key Responsibilities: - Develop and maintain web applications using .NET technologies (C#, ASP.NET Core, MVC, Web API). - Collaborate with senior developers to design, implement, and test features and enhancements. - Integrate AI capabilities into software solutions, such as machine learning models or intelligent automation. - Participate in the full software development lifecycle, including requirement analysis, coding, testing, and deployment. - Write clean, efficient, and maintainable code following best practices. - Troubleshoot, debug, and optimize existing applications. - Stay updated with the latest trends in .NET development and AI technologies. Role & responsibilities Preferred candidate profile - Programming Languages: Proficiency in C#, .NET Core, ASP.NET MVC/Web API. - Web Development: Knowledge of HTML, CSS, JavaScript, and front-end frameworks. - AI/ML Knowledge: Basic understanding of AI concepts and willingness to learn about AI technologies. - Databases: Familiarity with SQL Server or other relational databases. - Version Control: Experience using Git or other version control systems. - Problem-Solving: Strong analytical and problem-solving skills. - Communication: Good communication skills with the ability to work in a collaborative team environment. Preferred Qualifications: - AI/ML Frameworks: Exposure to AI tools like TensorFlow, ML.NET, or Python libraries (optional but beneficial). - Cloud Platforms: Experience with Azure or AWS for deploying AI solutions (a plus). - Software Development Practices: Familiarity with Agile methodologies and CI/CD pipelines. - Education: A degree in Computer Science, Engineering, or a related field (or equivalent experience) Why Join Equitec? - Career Growth: Learn and grow with cutting-edge technologies like AI, cloud computing, and modern .NET frameworks. - Collaborative Environment: Work with experienced professionals in an innovative and supportive environment. - Competitive Salary & Benefits: Competitive pay and benefits package, with performance-based incentives. - Learning & Development: Access to training and development resources to help you grow in your career. - Work-Life Balance: Flexible working hours and a focus on work-life balance.