Principal Applied Scientist - Robotics

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.

Key Responsibilities

Solution Identification and Strategy

• Partner with science, engineering, product, and hardware leaders to identify strategic product needs where robotics, perception, and embodied AI can create measurable customer and business impact.
• Evaluate academic literature, industry benchmarks, robotics platforms, and commercially viable robot APIs to assess feasibility, technical difficulty, and delivery risks.
• Break down ambiguous robotics and AI problems into clear research plans, model architectures, data requirements, evaluation criteria, and production milestones.
• Set science quality standards for applied robotics workstreams, including perception accuracy, latency, robustness, safety, reliability, and operational feedback metrics.
• Prioritize solutions using the scientific process, including modeling approaches, evaluation techniques, data collection strategies, and risk/reward tradeoffs.

Applied Research and Model Development

• Lead the design and execution of research programs and POCs for sensors, multi\-sensor fusion, real\-time signal processing, and perception systems.
• Develop and guide approaches for object detection, tracking, activity recognition, scene understanding, and related perception capabilities in real\-world environments.
• Advance multimodal AI systems that combine signals such as camera, depth, lidar, audio, telemetry, proprioception, and task context.
• Apply reinforcement learning, action\-conditioned planning, decision\-making, and reasoning methods to enable robot behaviors that are robust, measurable, and product\-relevant.
• Define dataset strategy, data quality criteria, labeling approaches, simulation or synthetic data opportunities, and evaluation protocols for robotics and embodied AI use cases.
• Guide model training, fine\-tuning, optimization, inference design, and compute/latency tradeoffs for real\-time or near\-real\-time deployment scenarios.

Solution Delivery and Production Integration

• Lead full\-stack execution across experimentation, data pipelines, model development, evaluation, deployment integration, and production monitoring.
• Partner closely with software engineering, machine learning engineering, hardware teams, and product stakeholders to integrate AI capabilities into robotic systems and services.
• Evaluate and review high\-complexity code, establish best practices for repositories, version control, code review, documentation, testing, and delivery readiness.
• Define operational metrics and user feedback loops to assess delivered solutions in production and inform future technical strategy.
• Serve as an escalation point for complex robotics, AI, perception, and systems integration issues, driving root\-cause analysis and durable solutions.

Research Leadership and Influence

• Demonstrate thought leadership in at least one business\-critical area such as robot perception, multimodal systems, sensor fusion, reinforcement learning, or embodied AI.
• Translate research insights into clear technical recommendations, patents, white papers, design documents, demos, or conference\-quality publications where appropriate.
• Mentor and guide scientists and engineers, raising the bar for applied research rigor, experimentation quality, and production readiness.
• Establish productive collaborations with internal teams, external research groups, academic partners, or commercial robotics ecosystem partners where relevant.

Core Competencies

• Bias for action with a strong hands\-on orientation; able to move from ambiguous idea to prototype, evaluation, and production path quickly.
• Ability to execute full\-stack AI workflows spanning data, experimentation, modeling, evaluation, APIs, deployment, and feedback loops.
• Strong cross\-functional collaboration with hardware teams, software engineering, ML engineering, product, operations, and leadership stakeholders.
• Excellent judgment in balancing scientific rigor, product urgency, systems constraints, safety, reliability, and customer impact.
• Clear executive\-level communication; able to explain complex robotics and AI tradeoffs to technical and non\-technical audiences.

Required Technical Expertise

• Deep experience in machine learning, artificial intelligence, computer vision, perception, robotics, sensor fusion, real\-time signal processing, or a closely related field.
• Experience with perception capabilities such as object detection, tracking, activity recognition, scene understanding, localization, or state estimation.
• Experience designing multimodal AI systems that combine heterogeneous data sources and reason over context, actions, and temporal signals.
• Practical knowledge of reinforcement learning, planning, sequential decision\-making, robotics control interfaces, or action\-conditioned model behavior.
• Strong programming capability in applicable languages such as Python and/or C\+\+, and experience with modern ML frameworks and production\-oriented software practices.
• Familiarity with APIs, SDKs, or integration patterns from commercially viable robotics platforms.

Minimum Qualifications

• 15 years of experience in data science, machine learning, artificial intelligence, robotics, computer vision, signal processing, statistical modeling, data mining, or a related field; OR
• Bachelor's degree in Mathematics , Statistics, Computer Science, Data Science, Physics, Robotics, Electrical Engineering, Mechanical Engineering, or related field and 11 years of relevant experience; OR
• Master's degree in one of the above or related fields and 9 years of relevant experience; OR
• Doctorate in one of the above or related fields and 7 years of relevant experience.
• 7\+ years of hands\-on experience with Python, C\+\+, PyTorch , and ROS for software development, machine learning, and robotics applications.
• Demonstrated technical leadership guiding teams and stakeholders toward strategic goals.

Preferred Qualifications

• 16 years of experience in data science, machine learning, artificial intelligence, robotics, computer vision, perception, signal processing, or related field; OR equivalent degree\-based experience aligned to Oracle IC5 guidelines.
• 2 years of leadership experience with or without direct reports, including technical direction, mentoring, project planning, or cross\-functional execution.
• 2 years of experience working with operating budgets and/or project financials, where applicable.
• 5\+ years of experience creating technical publications, patents, white papers, peer\-reviewed conference or journal articles, or equivalent technical documentation.
• Demonstrated experience delivering robotics, embodied AI, perception, or multimodal systems from research concept into production or customer\-facing environments.
• Hands\-on experience with commercial robot platforms, robot SDKs/APIs, simulation environments, telemetry pipelines, and real\-time deployment constraints.

Success Profile

• Builds credibility as a senior applied science leader who can bridge research depth with pragmatic product delivery.
• Operates comfortably across sensors, models, APIs, hardware/software boundaries, and executive decision\-making forums.
• Raises the bar for AI adoption in robotics by creating reusable patterns, evaluation standards, and scalable delivery practices.