Data Engineering Manager 2 at Emerson autotmotive

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

01 Apr, 26

Salary

0.0

Posted On

01 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Machine Learning, Python, Azure AI Studio, Cognitive Services, MLOps, Data Preparation, Model Development, CI/CD, Power Platform, AutoML, Machine Learning, Collaboration, Problem Solving, Monitoring, Governance, Security

Industry

Automation Machinery Manufacturing

Description

In This Role, Your Responsibilities Will Be: As an Azure AI Engineer, you will be responsible for architecting and implementing end-to-end AI solutions using Azure Machine Learning, Azure AI Studio, Azure AI Foundry, Cognitive Services, and the Power Platform. You will leverage both prebuilt AI models and custom machine learning workflows to solve real business problems, integrate AI into enterprise systems, and ensure robust governance, monitoring, and lifecycle management. Who You Are: An Azure AI Engineer who can design, build, and operate intelligent solutions using Microsoft Azure’s AI and machine learning ecosystem. The ideal candidate combines strong technical expertise with a practical understanding of scalable, secure, and responsible AI development. While not every listed skill is mandatory, a solid mix of the capabilities below will position you for success in this role. Key Responsibilities AI Solution Design & Development Build, train, and deploy machine learning models using Azure Machine Learning, Python, Azure AI Foundry and Azure ML SDKs. Develop scalable AI pipelines using Azure ML pipelines, AutoML, and cloud-native best practices. Integrate Azure AI capabilities—Vision, Language, Speech, and Document Intelligence—into enterprise applications. Design and automate AI-driven solutions using the Power Platform (Power Apps, Power Automate, Power Virtual Agents) integrated with Azure AI Services. Utilize Azure AI Studio, Azure AI Foundry to rapidly prototype and deliver generative AI, agentic AI and cognitive solutions. Cross-Functional Collaboration Partner with data engineers, analytics teams, and business stakeholders to translate business needs into impactful AI solutions. Collaborate with Power Platform developers to embed AI models and cognitive services into low-code applications and workflows. Contribute to architecture decisions ensuring scalability, maintainability, and alignment with enterprise cloud standards. Communicate technical concepts clearly to both technical and non-technical audiences. Responsible AI, Security & Governance Apply Responsible AI guidelines, ensuring fairness, explainability, and ethical use of machine learning models. Enforce data privacy, compliance, and security standards across all AI workloads. Support model versioning, governance, and lifecycle management. MLOps, Monitoring & Optimization Implement monitoring and observability for AI workloads using Azure Monitor, Application Insights, and MLflow (where applicable). Optimize model performance, reliability, and cost efficiency across training and inference workloads. Contribute to CI/CD workflows for ML and Power Platform integrations using Azure DevOps or GitHub Actions. For This Role, You Will Need: Bachelor’s degree in computer science, Computer Engineering, IT, or related discipline. Hands-on experience designing and deploying AI/ML solutions on Microsoft Azure. Experience with Azure AI Studio, Azure AI Foundry, Azure ML Designer, AutoML, and Prompt engineering Flow. Strong proficiency in Python and Azure SDKs for ML and Cognitive Services. Solid understanding of machine learning concepts: data preparation, model development, evaluation, and deployment. Experience with cloud-native development and CI/CD for ML pipelines. Strong communication, collaboration, and problem-solving skills. Preferred Qualifications That Set You Apart: Exposure to Microsoft Power Platform and integrating Azure AI models/services into Power Apps, Power Automate, and Copilots. Familiarity with MLOps practices and tools such as MLflow, Azure DevOps, or GitHub Actions. Microsoft certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate) are an added advantage. Working knowledge of Power BI for embedding or visualizing AI-driven insights. Our Culture & Commitment to You At Emerson, we prioritize a workplace where every employee is valued, respected, and empowered to grow. We foster an environment that encourages innovation, collaboration, and diverse perspectives—because we know that great ideas come from great teams. Our commitment to ongoing career development and growing an inclusive culture ensures you have the support to thrive. Whether through mentorship, training, or leadership opportunities, we invest in your success so you can make a lasting impact. We believe diverse teams, working together are key to driving growth and delivering business results. We recognize the importance of employee wellbeing. We prioritize providing competitive benefits plans, a variety of medical insurance plans, Employee Assistance Program, employee resource groups, recognition, and much more. Our culture offers flexible time off plans, including paid parental leave (maternal and paternal), vacation and holiday leave.

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Responsibilities

The Azure AI Engineer will architect and implement end-to-end AI solutions using various Azure tools and services. Responsibilities include building and deploying machine learning models, integrating AI capabilities into enterprise applications, and ensuring responsible AI practices.