Senior Data Scientist $$$ Offline

Our partner is an innovative technology company specializing in the development and implementation of cutting-edge solutions in embedded systems and radio frequency (RF) engineering.  

We are currently seeking a skilled and motivated Senior Data Scientist to lead our projects in this exciting and innovative field. 

In this role, you will be responsible for building models, developing simulations, and training machine learning models. You will ensure they are optimized to run efficiently across a variety of edge devices and operating systems. You will leverage your expertise in edge computing, model profiling and optimization to build robust and scalable data solutions. 

As part of our growing team, you will work closely with cross-functional teams to create cutting-edge applications that operate seamlessly at the edge, providing real-time analytics and decision-making capabilities. 

Key Responsibilities: 

- Model Development and Optimization: Design, train, and optimize models to be deployed on edge devices, ensuring they perform efficiently within the constraints of limited computing resources. 

- Performance: Leverage frameworks optimized for edge deployment such as TensorFlow Lite, PyTorch Mobile, and ONNX Runtime to ensure high performance and scalability. 

- Scalability & Maintainability: Design and implement reliable and robust data pipelines for edge devices, ensuring data integrity, scalability, and fault tolerance. Focus on building solutions that are maintainable and scalable in a production environment. 

- Testing and Validation: Perform rigorous testing and validation of models on edge devices to ensure they meet performance, reliability, and accuracy standards under various conditions. 

- Collaboration: Work closely with product managers, hardware engineers, and software developers to integrate predictive capabilities into existing systems and ensure seamless operation across different hardware platforms and operating systems. 

- Documentation: Maintain clear and comprehensive documentation for the deployment process, model performance, and optimization strategies. 

Key Requirements: 

- Background or experience in computational physics, simulations, mathematical modeling, or related fields, with the ability to apply scientific computing techniques to real-life problems.  

- Experience in building and deploying reliable, robust data solutions in production environments, particularly in the context of edge computing. Hands-on experience with edge devices (e.g., Raspberry Pi, NVIDIA Jetson, mobile devices) and IoT platforms.  

- Proven experience with machine learning frameworks optimized for edge deployment, including TensorFlow Lite, PyTorch Mobile, Tensor RT, or ONNX Runtime. 

- Strong understanding of hardware acceleration techniques (e.g., GPUs, TPUs, FPGAs) for performance optimization on edge devices. 

- Familiarity with CI/CD pipelines for code as well as model deployment and versioning. 

- Strong problem-solving skills, particularly in optimizing machine learning models for resource-constrained environments. 

- Excellent communication skills to collaborate with cross-functional teams and articulate technical concepts effectively. 

Why Join Us: 

- Innovative Projects: Work on exciting cutting-edge projects that push the boundaries of edge AI and machine learning technologies. 

- Dynamic Team: Collaborate with talented professionals in a fast-paced, creative environment. 

- Impactful Work: Contribute to building intelligent solutions that are deployed at the edge, making a direct impact on real-time decision-making across various industries. 

- The company offers a competitive salary, official employment, office-based work in Kyiv, and reservation from mobilization. 

If you're passionate about developing intelligent services on edge devices and optimizing machine learning models to run at scale, we would love to hear from you. Apply today and help us bring the future of edge AI to life!