Turing is seeking a hands-on Applied Research Engineer with expertise in robotics, machine learning, and multi-sensor data processing to join their Research & Delivery team.
The ideal candidate should have 3–5 years of experience in applied ML, computer vision, or robotic systems and be eager to build robust, high-quality datasets for modern perception, SLAM, and manipulation models.
Responsibilities include defining and evolving labeling schemas for robotic perception tasks, such as 2D/3D detection and segmentation, grasp and manipulation point annotations, scene affordances, and sensor fusion.
The role involves fine-tuning small ML models under the guidance of a senior engineer and contributing to quality control processes to ensure consistent labeling outcomes.
Strong communication skills and a collaborative mindset are essential for success in this technical and cross-functional role.
Requirements:
Candidates must have 3–5 years of hands-on experience in robotics, applied ML, or computer vision, with exposure to real-world sensor data or annotation workflows.
A strong understanding of robotics concepts, including perception pipelines, SLAM, and sensor fusion, is required.
Familiarity with basic ML training and evaluation, particularly for computer vision or multi-modal data tasks, is necessary.
The ability to read and synthesize ML research papers relevant to robotics is essential.
Experience with tools such as ROS, CVAT, Roboflow, or custom labeling platforms is required.
Some exposure to model fine-tuning using frameworks like PyTorch, TensorFlow, or Hugging Face is preferred.
Excellent written and verbal communication skills are necessary for translating technical needs across disciplines.
Benefits:
The position offers a competitive compensation package, with a base salary ranging from $170,000 to $200,000 plus equity.
Employees enjoy an amazing work culture characterized by a collaborative and supportive environment, working five days a week.
Team members have the opportunity to work alongside top talent from companies like Meta, Google, and LinkedIn, as well as individuals with deep startup experience.
Flexible working hours and a full-time remote opportunity are provided to employees.