Machine Learning Engineer

Job Summary:As a Machine Learning Engineer at Emerson, you will be responsible for developing, implementing, and optimizing machine learning models and systems. You will collaborate closely with data scientists, software engineers, and other collaborators to translate data insights into practical, scalable solutionsDesign, build, and deploy machine learning models and algorithms to solve specific business problems. Optimize models for performance and scalability.Work with large data sets to preprocess, clean, and transform data for use in machine learning models. Develop and maintain data pipelines.Monitor and evaluate the performance of deployed models, making adjustments and improvements as needed to ensure accuracy and reliability.Work with multi-functional teams such as data scientists, analysts, and product managers to understand requirements and deliver machine learning solutions that meet business needs.Keep up with the latest research and trends in machine learning and artificial intelligence. Explore and implement new techniques and technologies to enhance model performance.Document model development processes, code, and standard methodologies. Provide clear and comprehensive reports on model performance and metricsParticipate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint RetrospectiveIn this Role, Your Responsibilities Will b e:Design, build, and deploy machine learning models and algorithms to solve specific business problems. Optimize models for performance and scalability.Work with large data sets to preprocess, clean, and transform data for use in machine learning models. Develop and maintain data pipelines.Monitor and evaluate the performance of deployed models, making adjustments and improvements as needed to ensure accuracy and reliability.Work with multi-functional teams such as data scientists, analysts, and product managers to understand requirements and deliver machine learning solutions that meet business needs.Keep up with the latest research and trends in machine learning and artificial intelligence. Explore and implement new techniques and technologies to enhance model performance.Document model development processes, code, and standard methodologies. Provide clear and comprehensive reports on model performance and metricsParticipate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint RetrospectiveWho You Are:You quickly and decisively act in constantly evolving, unexpected situations. You adjust communication content and style to meet the needs of diverse partners. You always keep the end in sight; puts in extra effort to meet deadlines. You analyze multiple and diverse sources of information to define problems accurately before moving to solutions. You observe situational and group dynamics and select best-fit approach.For This Role, You Will Need:Bachelor's degree in computer science, Data Science, Statistics, or a related field or a master's degree or higher is preferred.More than 3 years of experience in machine learning engineering or a related role, with a strong track record of developing and deploying machine learning models.Proficiency in programming languages such as Python or R. Experience with machine learning frameworks (e.g., Go, TensorFlow, PyTorch, scikit-learn).Experience with Azure Cognitive servicesExperience with data processing and manipulation tools and libraries (e.g., pandas, NumPy).Strong analytical and problem-solving skills, with the ability to handle complex and large-scale data sets.Experience with deploying machine learning models to production environments, including knowledge of containerization technologies (e.g., Docker or equivalent) and cloud platforms, Microsoft Azure is preferredExcellent verbal and written communication skills, with the ability to explain technical concepts to non-technical collaboratorsPreferred Qualifications that Set You Apart:Prior experience in engineering domain would be nice to havePrior experience in working with teams in Scaled Agile Framework (SAFe) is nice to havePossession of relevant certification/s in data science from reputed universities specializing in AI.Familiarity with version control systems (e.g., Git) and CI/CD pipelines.Understanding of standard processes in software development and methodologies.