Emerson - Machine Learning Engineer - LLM Models

Job DescriptionJob Summary :- As a Senior Machine Learning Developer 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 solutions.In this Role, Your Responsibilities Will Be :- 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 metrics.- Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective.Who 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 :- Bachelors degree in computer science, Data Science, Statistics, or a related field or a master's degree or higher is preferred.- More than 5 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, Hugging Face Transformers, LangChain, or similar).- Experience designing and optimizing prompts for large language models (LLMs).- Multimodal AI.- Proficiency in React, Angular for building interactive AI-powered UIs.- Experience integrating ML models into web applications using REST APIs, WebSockets, or GraphQL.- Ability to fine-tune foundation models on domain-specific data.- Understanding of ethical AI, bias mitigation, and model interpretability in generative systems.- Deep understanding of transformer-based models (e.g., GPT, LLaMA, Claude), diffusion models, and generative adversarial networks (GANs).- Experience with LangChain, Semantic Kernel, AutoGen, or similar frameworks for building AI agents.- Designing agents that can plan, reason, and interact with APIs, databases, and external tools.- Experience 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 preferred.- Hands-on experience with Azure Machine Learning, Azure OpenAI, Azure Cognitive Services, and Azure Functions.- Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical collaborators.Preferred Qualifications that Set You Apart :- Prior experience in engineering domain, process control industry would be nice to have.- Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to have.- Possession 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. (ref:hirist.tech)