Job Summary

If you are a professional looking for an opportunity to work with the global Emerson Systems and Software organization, this is a stimulating opportunity for you! The Machine Learning Operations Engineer will handle end-to-end processes from data analysis and feature engineering to model deployment and monitoring, and will demand a proactive and collaborative mindset, working closely with process owners, business stakeholders and engineering teams to deliver scalable, production-ready AI and automation solutions. The candidate will take ownership of the entire model lifecycle driving experimentation, validation, deployment, and continuous optimization to create high-impact, AI-powered business value.

In this Role, Your Responsibilities Will Be:

• Develop, train and deploy machine learning, deep learning AI models for a variety of business use cases such as classification, prediction, recommendation, NLP and Image Processing.
• Utilize Azure AI services and infrastructure for development, training, inferencing, and model lifecycle management.
• Design and implement end-to-end ML workflows from data ingestion and preprocessing to model deployment and monitoring.
• Collect, clean, and preprocess structured and unstructured data from multiple sources using industry-standard techniques such as normalization, feature engineering, dimensionality reduction, and optimization.
• Perform hyperparameter tuning, cross-validation, and performance evaluation using industry-standard metrics to ensure model robustness, relevance, and accuracy.
• Integrate models and services into business applications through RESTful APIs.
• Build and maintain scalable and reusable ML components and pipelines using Azure ML Studio, Kubeflow, and MLflow.
• Enforce and integrate AI guardrails: bias mitigation, security practices, explainability, compliance with ethical and regulatory standards.
• Support and collaborate on the integration of large language models (LLMs), embeddings, vector databases, and RAG techniques where applicable.
• Collaborate with cross-functional teams including software engineers, product managers, process owners, and architects to define and deliver AI-driven solutions.
• Communicate complex ML concepts, model outputs, and technical findings clearly to both technical and non-technical stakeholders.
• Stay current with the latest research, trends, and advancements in AI/ML and evaluate new tools and frameworks for potential adoption.
• Maintain comprehensive documentation of data pipelines, model architectures, training configurations, deployment steps, and experiment results.
• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field over 7+ years.
• Proven experience as a Data Scientist, ML Developer, or in a similar role.
• Strong command of Python and ML libraries (e.g., Azure ML Studio)
• ML Model Development: Strong grasp of statistical modelling, supervised/unsupervised learning, time-series forecasting, and NLP.
• Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration
• Proficiency in programming languages such as Python, R, or SQL.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control.
• Familiarity with cloud platforms (e.g., Azure (Primarily), AWS and deployment tools.
• Knowledge of DevOps platform

Who You Are:

You encourage diverse thinking to promote and nurture innovation. You readily take action on challenges, without unnecessary planning. You have a strong bottom-line orientation.

For this Role You Will Need:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field over 7+ years.
• Proven experience as a Data Scientist, ML Developer, or in a similar role.
• Strong command of Python and ML libraries (e.g., Azure ML Studio)
• ML Model Development: Strong grasp of statistical modelling, supervised/unsupervised learning, time-series forecasting, and NLP.
• Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration
• Proficiency in programming languages such as Python, R, or SQL.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control.
• Familiarity with cloud platforms (e.g., Azure (Primarily), AWS and deployment tools.
• Knowledge of DevOps platform

Preferred Qualifications:

• Knowledge of natural language processing (NLP) and custom/computer,
• Familiarity with marketing analytics, attribution modelling
• Working knowledge of BI tools for integrating ML insights into dashboards.
• Hands on MLOps experience, with an appreciation of the end-to-end CI/CD process
• Familiarity with DevOps practices and CI/CD pipelines.
• Experience with big data technologies (e.g., Hadoop, Spark, Graph ML) is added advantage
• Certifications in AI/ML

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.