Senior Director, Applied Science - Robotics

** Job Description*
* ** Oracle Cloud Infrastructure provides organizations around the world with computing infrastructure and software to help them innovate, unlock efficiencies, and operate more effectively.*
* ** As Senior Director, Robotics, you will lead a high-impact organization responsible for advancing Oracle's robotics strategy and delivering the technical, operational, and organizational capabilities required to deploy and manage robotic systems  will partner across applied science, engineering, product, hardware, security, operations, legal, finance, and executive leadership to translate customer and business needs into secure, reliable, and commercially viable robotics solutions.*
* ** You will lead teams building production-ready robotics capabilities across perception, sensor fusion, multimodal AI, embodied AI, robot planning, mission execution, telemetry, digital twins, device management, and cloud services. This role requires strong judgment across hardware and software boundaries, the ability to balance scientific innovation with operational rigor, and accountability for delivering scalable robotics platforms that create measurable customer and business value.*
* ** Responsibilities*
* Responsibilities

+ Strategic Leadership:
Set the scientific and technical direction for robotics, perception, and embodied AI initiatives. Collaborate with executive leadership to align product vision, applied research priorities, resource allocation, and delivery roadmaps.

+ Applied Research and

Innovation: Lead teams of scientists, data engineers, machine learning engineers, and developers in applied research programs spanning multi-sensor fusion, real-time signals, perception systems, multimodal reasoning, reinforcement learning, planning, and decision-making.

+ Robotics Technology Development:
Drive development and deployment of AI capabilities for robotic systems and related cloud services, including data collection, model architecture, training, evaluation, inference design, API integration, observability, and production monitoring.

+ Solution Identification and Prioritization:
Partner with science, engineering, product, and hardware leaders to identify product needs where robotics and embodied AI can create measurable customer and business impact. Prioritize opportunities using feasibility, scientific rigor, customer impact, and risk/reward tradeoffs.

+ Cross-Disciplinary

Collaboration:

Foster productive collaboration between applied science, software engineering, machine learning engineering, product management, hardware teams, operations, and go-to-market stakeholders. Encourage knowledge sharing and joint problem-solving across disciplines.

+ Product

Innovation: Translate scientific advances into practical, scalable, and marketable capabilities. Ensure delivered solutions are competitive, reliable, and aligned with customer needs and cloud service requirements.

+ Data, Evaluation, and Insights:
Define dataset strategy, data quality standards, labeling approaches, synthetic or simulation data opportunities, evaluation protocols, product metrics, and operational feedback loops that guide technical decisions and future strategy.

+ Production Readiness and Quality Assurance:
Establish standards for reliability, latency, robustness, safety, security, testing, documentation, code review, and deployment readiness. Serve as an escalation point for complex robotics, AI, perception, and systems integration issues.

+ Technical Leadership and Talent Development:
Recruit, lead, mentor, and develop senior scientists and engineers. Raise the bar for applied research rigor, engineering quality, full-stack delivery, and executive-level communication.

+ Intellectual Property, Ecosystem Awareness, and Portfolio Management:
Identify opportunities for patents, publications, white papers, demos, and reusable patterns. Stay current on robotics platforms, commercial robot APIs and SDKs, benchmarks, customer feedback, and competitive offerings while managing budgets and portfolio priorities.

Minimum Qualifications

+ 15+ years of experience in robotics, machine learning, artificial intelligence, computer vision, perception, signal processing, statistical modeling, data mining, software engineering, or a related field; or equivalent degree-based experience in a relevant technical discipline.

+ Demonstrated experience leading applied science, research, machine learning, or engineering teams through complex technical programs from ambiguous problem framing through production delivery.

+ Proven ability to guide high-complexity technical decisions, evaluate tradeoffs, and communicate robotics and AI strategy to executive, technical, product, and cross-functional audiences.

+ Experience delivering AI, robotics, perception, embodied AI, or multimodal systems into production, customer-facing, or operational environments.

Preferred Skills and Experience

+ Ph.D. in Computer Science, Robotics, Machine Learning, Deep Learning, Electrical Engineering,…