Turing

Applied Research Engineer – Robotics Data & ML

United States

Not SpecifiedCompensation
Mid-level (3 to 4 years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, RoboticsIndustries

Requirements

The ideal candidate will 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 like perception pipelines, SLAM, or sensor fusion is necessary. Familiarity with basic ML training and evaluation, especially for computer vision or multi-modal data tasks, is required. The role also necessitates the ability to read and synthesize ML research papers relevant to robotics, experience with tools such as ROS, CVAT, Roboflow, or custom labeling platforms, and some exposure to model fine-tuning using frameworks like PyTorch, TensorFlow, or Hugging Face. Excellent written and verbal communication skills are essential for translating technical needs across disciplines.

Responsibilities

The Applied Research Engineer will define and evolve labeling schemas for robotic perception tasks, including 2D/3D detection, segmentation, grasp and manipulation point annotations, scene affordances, human-robot interaction, and sensor fusion. They will align annotation strategies with key robotics benchmarks and downstream model use cases like RL, imitation learning, and vision-based control. The role involves fine-tuning and evaluating small ML models for targeted robotics tasks under senior guidance and performing basic experiments to assess data effectiveness. Additionally, the engineer will contribute to quality control processes by building checklists, gold sets, and feedback loops, and collaborate with ML, robotics, and data labeling teams to translate model and benchmark requirements into clear data specifications. This includes writing clear documentation and presenting technical updates to collaborators and stakeholders.

Skills

Robotics
Machine Learning
Multi-sensor data processing
Computer Vision
Robotic Systems
Data Annotation
Model Fine-tuning
Data Specifications
Communication
Collaboration

Turing

AI-driven matching of businesses with engineers

About Turing

Turing provides tech services by using artificial intelligence to connect businesses with skilled software engineers for custom application development and on-demand engineering needs. The company has a large pool of over 3 million vetted engineers from 150 countries, allowing businesses to quickly find the right talent for their projects. When a company needs a developer, they specify the required skills, and Turing's AI matches them with the best candidates, streamlining the recruitment process and helping companies complete projects faster. Turing also supports engineers by offering access to high-paying remote job opportunities in the U.S., with a high rematch rate ensuring job stability. The goal of Turing is to enhance recruitment efficiency for businesses while providing valuable job opportunities for engineers.

Palo Alto, CaliforniaHeadquarters
2018Year Founded
$132.3MTotal Funding
SERIES_DCompany Stage
Enterprise Software, AI & Machine LearningIndustries
1,001-5,000Employees

Risks

Competition from platforms like DevZero offering cloud-based development environments.
Crowded market with new AI-driven talent platforms like Gaper and Aloa.
Potential brand confusion with South Korean company Turing Co.

Differentiation

Turing uses AI to match businesses with over 3 million vetted engineers.
Turing's Talent Cloud accelerates team building, similar to scaling servers on AWS.
Turing offers a 99% rematch rate for engineers, ensuring job stability.

Upsides

Remote work trend boosts demand for Turing's remote engineer connections.
Global tech talent shortage increases reliance on Turing's AI-powered talent matching.
Turing's AI-driven recruitment tools enhance hiring efficiency and accuracy.

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