Senior Human Factors Research Engineer

Intuitive•Sunnyvale, CA

2d•Onsite

About The Position

The Human Factors Research Engineer (HFRE) is part of the Human Factors (HF) organization that aims to maximize usability and desirability of Intuitive products while minimizing risk through scientific research and usability engineering. HFRE is focused on end-to-end experimental and real-world behavioral research aligned with business demands that (a) de-risk product design strategies for future development, (b) translate evidence to define user requirements, (c) establish product claims. This role works closely with executive leadership, product managers, mechanical engineers, computer scientists, clinical engineers, clinical scientists, health economists, and data scientists. HFRE conducts research that is focused on the psychology, biomechanics, and physiology of end users’ underlying performance associated with robotic teleoperations. Evidence generated from these studies provide strategic insight into “what”, “why”, and “how much” end users differ in learning and performance across a range of products. This role functions in ambiguous and strategic stages of product development that involve the ability to position and conduct experimental research within a business. This role demands extensive follow-through to translate, communicate, ideate, prototype, and build novel evidence-based strategies, tools, and concepts that operationalize and inform the “intuitiveness” of commercialized and future products. This role demands quick changes in direction with capacity to define and implement strategies that have visibility across business units while maintaining focus on tactical details. This role is a unique engineering and scientific opportunity with the expectation that knowledge and skills can be applied to experimental behavioral research that actionably informs product design strategies for future development, inform product development, and establish product claims with state-of-the-art human-robot interfaces.

Requirements

Minimum 6 years relevant research and engineering experience in product development industry.
Minimum 6 years leading human subjects research.
Ability to process and analyze large quantitative datasets from human subjects and robotic systems.
Ability to analyze large volumes of data from mixed methods research into usable communications.
Ability to develop experimental conditions and stimuli in virtual and physical environments.
Ability to translate findings from studies into product requirements for complex, software-controlled electro-mechanical medical device.
Experience with authoring and reviewing scientific manuscripts.
Excellent verbal communication and presentation skills.
Ability to work with and across various groups and levels of management within the organization, including other engineering groups, commercial, clinical engineering, and regulatory.
Excellent collaboration skills.
Ability to apply user-centered design and human factors engineering principles to product research, development, and design.
Minimum MS in Mechanical Engineering, Computer Science, Psychology, Biomechanics with emphasis on Human-Computer Interaction, Robotics, or a related field.
Python or C++ required for ML performance modeling
Develop Snowflake pipeline, Databricks pipeline
Experience in testing BI systems and data analysis processes, including ETL processes
Data testing such as pre-screening raw data, vital check on completeness, integrity of data, field tests on Aggregation, Reconciliation tests, Report and App testing associated with data collection from lab-based experiments
Execute end-to-end testing of ETL processes, including data extraction, transformation, loading, and reporting, to ensure accuracy, completeness, and data integrity from lab-based and field-based experiments
Create and analyze requirements and deliver required project documents test strategy, testing scope and test cases
Manage data management governance associated with data sharing internally and externally
Manage updates on systems configurations for reliable data capture pipeline from lab-based and field-based experiments
Development and maintenance of data infrastructure required to synchronize, capture, process and analyze multiple data sources from research and evaluations to inform product design strategies, product development, and product claims
Build and validate experimental conditions within virtual and physical environments
Develop and validate novel and OTS bioinstrumentation and psychometrics that can be implemented in experiments to reliably measure individual differences related to human performance

Nice To Haves

Experience in research on Neuromotor/ Sensorimotor Control and Learning
Experience in research on Neuroscience, a plus
Experience in Computational Psychology or Data Science, a plus.
Experience in Differential Psychology, a plus.
Experience with bioinstrumentation, a plus.
Experience in medical device, or similar regulated industry, a plus.

Responsibilities

Experimental research design, execution, and enablement
Propose and position research plans across a range of products and a myriad of internal and/or external stakeholders
AI/ Machine learning a must
Conduct literature reviews that justify research strategy and study design
Design studies, author protocols, train support staff on products and protocols
Manage ethics reviews
Guide sampling, legal, logistical, and operational tactics with study preparation
Conduct experiments end-to-end ranging in scale and complexity
Manage customer relationships associated with human subjects
Lead data processing and analysis
Lead authorship and submissions of abstracts, white papers, manuscripts
Translate and convert scientific evidence to a range of internal and external stakeholders into actional recommendations for product design strategies, product requirements, or product claims
Identify behavioral markers associated with individual differences underlying customer learning and performance
Characterize inferential and predictive relationship between individual differences and standard and new product metrics
Develop and maintain relationships with behavioral scientists as prospective partners to Intuitive either in direct collaboration on sponsored research or indirect collaboration on independently funded research with surgical scientists
Instrumentation and test box development
Align business goals, experimental research objectives, and development of experimental requirements and instrumentation
Define experimental requirements based on evidence from psychological, biomechanical, and physiological research
Build and validate experimental conditions within virtual and physical environments
Develop and validate novel and OTS bioinstrumentation and psychometrics that can be implemented in experiments to reliably measure individual differences related to human performance
Data science
Data extraction, transformation, processes, analysis and visualization with multiple data sources from biometrics, psychometrics, and system data logs from lab-based experiments and field-based experiments
Prototype and iterate on designs, develop tests, and deliver high-quality software in Python or C++ required for ML performance modeling
Develop Snowflake pipeline, Databricks pipeline
Experience in testing BI systems and data analysis processes, including ETL processes
Data testing such as pre-screening raw data, vital check on completeness, integrity of data, field tests on Aggregation, Reconciliation tests, Report and App testing associated with data collection from lab-based experiments
Execute end-to-end testing of ETL processes, including data extraction, transformation, loading, and reporting, to ensure accuracy, completeness, and data integrity from lab-based and field-based experiments
Create and analyze requirements and deliver required project documents test strategy, testing scope and test cases
Manage data management governance associated with data sharing internally and externally
Manage updates on systems configurations for reliable data capture pipeline from lab-based and field-based experiments
Development and maintenance of data infrastructure required to synchronize, capture, process and analyze multiple data sources from research and evaluations to inform product design strategies, product development, and product claims
Build and validate experimental conditions within virtual and physical environments
Develop and validate novel and OTS bioinstrumentation and psychometrics that can be implemented in experiments to reliably measure individual differences related to human performance