Design, develop, and validate high-level controls for a powered leg exoskeleton, translating sensor data into safe, adaptive assistance across walking, stairs, slopes, and other activities.
Senior Software Engineer, Auto Labelling
📜 Description
- Orchestrate large-scale auto-labelling training, evaluation, and automation.
- Architect and scale pipelines for large datasets and user requests with distributed computing frameworks.
- Work with ML researchers and engineers to deploy new architectures into production.
🛠️ Requirements
- Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.
- 3+ years of experience developing solutions in ML systems or the ML software stack.
- Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads.
- Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference.
- Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code.
- Open-minded and collaborative team player with the willingness to help others.
- Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion perception models.
- Experience working with large Vision-Language Models (VLMs)
✨ Benefits
- Competitive compensation
- Equity awards
- Medical coverage
- Dental coverage
- Vision coverage
- Unlimited vacation
- Flexible hours
- Work-from-home support
- Develop an offline perception and auto-labelling system using computer vision and machine learning.
Full job description
- Be part of a team of multidisciplinary Research Scientists and Engineers working on building a cutting-edge offline perception and auto-labelling system leveraging computer vision, and machine learning.
- Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system.
- Architect and scale the pipeline to handle large-scale data and user requests using distributed computing frameworks.
- Collaborate with ML researchers and engineers to seamlessly deploy new architectures into the production environment.
- Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.
- 3+ years of experience developing solutions in ML systems or the ML software stack.
- Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads.
- Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference.
- Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code.
- Open-minded and collaborative team player with the willingness to help others.
- Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion perception models.
- Experience working with large Vision-Language Models (VLMs)
Similar jobs
Search more Software Engineer jobsBuild and evolve database migration tools, including the Migration Assistant and MOLT suite, while applying AI to reduce migration friction and ensure secure, correct workflows.
Develop and integrate embedded C++ software for satellite terminals, taking features from requirements through testing and commercial deployment while collaborating across hardware, firmware, and software teams.
Own pricing engineering end to end, turning business goals into reliable production systems while shaping technical direction for performance, correctness, and measurable outcomes.
Design and deliver secure, scalable services, APIs and applications for operational and regulatory systems, while shaping technical decisions, improving engineering practices and mentoring fellow engineers.
