Job
Description
BMC is looking for an experienced Data Science Engineer with hands-on experience with Classical ML, Deep Learning Networks and Large Language Models, knowledge to join us and design, develop, and implement microservice based edge applications , using the latest technologies.? In this role, you will be responsible for End-to-end design and execution of BMC Data Science tasks, while acting as a focal point and expert for our data science activities. You will research and interpret business needs, develop predictive models, and deploy completed solutions. You will provide expertise and recommendations for plans, programs, advance analysis, strategies, and policies. Here is how, through this exciting role, YOU will contribute to BMC's and your own success: Ideate, design, implement and maintain enterprise business software platform for edge and cloud, with a focus on Machine Learning and Generative AI Capabilities, using mainly Python Work with a globally distributed development team to perform requirements analysis, write design documents, design, develop and test software development projects. Understand real world deployment and usage scenarios from customers and product managers and translate them to AI/ML features that drive value of the product. Work closely with product managers and architects to understand requirements, present options, and design solutions. Work closely with customers and partners to analyze time-series data and suggest the right approaches to drive adoption. Analyze and clearly communicate both verbally and in written form the status of projects or issues along with risks and options to the stakeholders. To ensure youre set up for success, you will bring the following skillset & experience: You have 8+ years of hands-on experience in data science or machine learning roles. You have experience working with sensor data, time-series analysis, predictive maintenance, anomaly detection, or similar IoT-specific domains. You have strong understanding of the entire ML lifecycle: data collection, preprocessing, model training, deployment, monitoring, and continuous improvement. You have proven experience designing and deploying AI/ML models in real-world IoT or edge computing environments. You have strong knowledge of machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost). Whilst these are nice to have, our team can help you develop in the following skills: Experience with digital twins, real-time analytics, or streaming data systems. Contribution to open-source ML/AI/IoT projects or relevant publications. Experience with Agile development methodology and best practice in unit testin Experience with Kubernetes (kubectl, helm) will be an advantage. Experience with cloud platforms (AWS, Azure, GCP) and tools for ML deployment (SageMaker, Vertex AI, MLflow, etc.).
