Senior Machine Learning Engineer, Zendar

• This role is ideal for an ML engineer who is passionate to work on model optimization while remaining open to working across all aspects of the ML and perception pipeline, including model design, data collection and preprocessing, as well as model testing and evaluation
• Experience optimizing deep neural networks for real-time performance
• Proficiency in modern Python and C++
• Familiarity with model quantization, quantized aware training, NAS and model pruning, and other techniques for efficient deployment on edge devices
• Experience in training, testing, and verifying optimized neural network models
• Deep understanding of challenges in machine learning pipeline design such as data collection and processing, model test and evaluation
• Proficiency in Python
• Familiarity with professional software development tools, such as source control (git), unit testing, and profiling
• Strong communication skills and proven ability to collaborate effectively across function

Desirable

• You will be one of the first ML hires in our Paris office, with significant potential for growth, and you'll play a foundational role in building and shaping our Europe ML team as we continue to invest in its expansion over time
• This is a unique opportunity to drive impact while staying closely connected to our US team
• You will work closely with the perception team to shape our perception module for future production series, while also collaborating with chip designers to influence the development of compute architectures that align with our pipeline’s requirements
• As the key expert on edge deployment, you will also work closely with our product team and external partners to bring our solution to market

• Stage 1. Applied
• Stage 2. Review
• Stage 3. Hiring manager screen
• Stage 4. Technical Interview
• Stage 5. Technical Interview
• Stage 6. Onsite

• Performance-Based Bonus
• Medical, Dental, and Vision Insurance
• Unlimited PTO
• Equity
• Hybrid Work Model
• Daily Catered Lunch & Stocked Fridge

Total funding: $26.8m

Radar technology presents a promising solution for autonomous vehicles and robots to see the obstacles around them. Yet, existing sensors are too low-resolution and struggle under challenging conditions. Solutions are beginning to arise for self-driving cars, but tackling challenges for fully autonomous robotics is significantly more difficult.