Machine Learning Engineer

An amazing start-up, operating 6 months, is looking for the first Data expert to design and build the Data infrastructure for the research.

About the Role:

We're seeking an ML Platform Engineer to build and own the production infrastructure that transforms research innovations into deployed multi-disciplinary systems. You'll be the bridge between algorithm prototypes and real-world performance, managing everything from multi-disciplinary data pipelines to optimized edge deployment.

Key Responsibilities:

• Design and implement robust data collection platforms for multi-disciplinary environments, building ETL pipelines that handle massive datasets. (4 Giga Peer sec)
• Build and maintain SQL-based analytics tools, dashboards for algorithm performance, and data analysis.
• Profile and optimize inference performance across diverse hardware configurations, focusing on latency, memory usage, and power consumption for resource-constrained edge deployments.
• Develop MLOps pipelines including CI/CD for algorithm lifecycle management, automated testing frameworks, experiment tracking, model versioning, and deployment automation across cloud and edge environments.

Requirements:

• Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience).
• Experience building data pipelines for large-scale, multi-modal datasets with expertise in ETL frameworks.
• Experience with a leading cloud provider (GCP, Azure, or AWS).
• Solid understanding of real-time systems, performance profiling, and memory optimization for resource-constrained environments.
• Strong debugging and troubleshooting skills for production systems operating under performance constraints.
• Exceptional problem-solving capabilities, strong communication and collaboration skills, self-direction, and a startup mentality.
• Programming: Professional fluency in Python.
• Bonus skills: Proficiency in C/C++, CuPy, CUDA and modern ML frameworks (PyTorch, TensorFlow), with experience in compilation tools and runtime optimization libraries.