Job Description
Job 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)