Principal Applied Scientist - Robotics

Job Description

The IC4 Applied Scientist for Robotics, Perception, and Embodied AI will serve as a senior technical leader responsible for defining, prototyping, and delivering AI capabilities for commercially viable robotic systems. This role partners across science, software engineering, product, and hardware teams to identify high-impact opportunities, translate ambiguous product needs into research and engineering roadmaps, and guide end-to-end solution development from data collection and experimentation through production deployment.

The scientist will lead applied research in multi-sensor fusion, real-time signals, perception, multimodal reasoning, reinforcement learning, and action‑conditioned planning, with a strong bias for hands‑on execution and full‑stack delivery.

• Independently collaborates with science, engineering, and product teams to identify business and product needs to create and implement solutions, promote innovation, and drive model implementations.
• Independently performs literature reviews and state‑of‑the‑art analyses to understand the problem that needs to be solved.
• Creates a science plan to address product and/or business problems.
• Serves as a leading contributor on the identification of solutions based on the scientific process (e.g., including modeling approaches, evaluation techniques, data collections).

• Develops and pilots research proofs‑of‑concept (POCs) or research experiments to demonstrate the feasibility of proposed solutions, gather supporting evidence, and secure resources for applied research.
• Independently identifies and prepares datasets for use in applied research. Ensures datasets meet quality standards, and identifies gaps in the data.
• Contributes to the design of and conducts research on new theories, tools, and methodologies to transfer and apply state‑of‑the‑art technologies into products and services or make advancements in the field.

• Designs, develops, and optimizes ML and AI technologies, such as model training/fine‑tuning and computation optimizations.
• Designs and reviews the architecture of ML and AI solutions, such as data, model, training, and evaluation, employing best practices.

• Independently identifies meaningful insights from data and metadata sources from analysis and experiments.
• Interprets and communicates insights and findings to cross‑level and cross‑functional audience.
• Creates patents, white papers, or other technical documentation related to applied research outcomes.

• Develops efficient, bug‑free, medium‑complexity code from scratch, and properly maintains and organizes existing codebase.
• Implements best practices for version control, code review, and code delivery/deployment.
• Builds and maintains professional documentation for technical processes (experimentation, data collection and analyses, model building).
• Tests and reviews code for bugs.

• Collaborates with fellow technical teams to ensure the successful and timely delivery of solutions and integration of services.
• Collaborates with software engineers and/or machine learning engineers to deploy solutions into production environments.
• Participates in the peer review of solutions prior to delivery.
• Coordinates with team members for the delivery of solutions.
• Ensures delivered solutions successfully solve product and/or business problems.
• Independently collaborates with operational teams to evaluate and monitor solutions in production.

• Demonstrates advanced knowledge in at least one business‑critical applied research technology area.
• Applies advanced domain knowledge and industry best practices to applied research.

• Leads the publication and presentation of research findings and papers in conferences, research and industry outlets, etc.
• Participates in the scientific community by providing peer review and feedback.
• Establishes collaboration with internal research…