Staff Machine Learning Engineer, Robotics

Santa Clara County, CA - USA

Monthly Salary: $ 141000 - 227700

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

At Johnson & Johnsonwe believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented treated and curedwhere treatments are smarter and less invasive andsolutions are our expertise in Innovative Medicine and MedTech we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow and profoundly impact health for more at

Job Function:

R&D Product Development

Job Sub Function:

Robotics

Job Category:

Scientific/Technology

All Job Posting Locations:

Santa Clara California United States of America

Job Description:

About MedTech

Fueled by innovation at the intersection of biology and technology were developing the next generation of smarter less invasive more personalized treatments.

Your unique talents will help patients on their journey to wellness.

Learn more at are searching for the best talent for Staff Machine Learning Engineer Robotics to be located in Santa Clara CA.

Johnson & Johnson MedTech is inventing the future of robotic surgery with OTTAVA. This next-generation soft-tissue surgical robot will leverage advancements inAI/ML connect health data inside and beyond the operating room and deliver clinical innovations for patients and care teams.

Purpose:

We are looking for a highly skilled and innovative Staff Machine Learning Engineer to apply the latest advances in learning-based manipulation to improve the performance and safety of surgical this hands-on role you will rapidly design models implement algorithms and bring ML-trained manipulation behaviors from research to real-world robotic hardware in unstructured environments. As a senior member of the team you will be responsible for mentoring engineers and elevating the teams overall technical capabilities.

You will be responsible for:

Develop and implement ML algorithms for surgical robotic manipulation
Build pipelines for data collection training testing and deployment of ML models
Leverage simulation for prototyping training and transfer to robot hardware
Define and evaluate performance metrics for surgical tasks and implement rigorous testing protocols
Collaborate with software and controls teams to deploy learned policies and ensure safe and reliable execution
Optimize models for onboard real-time performance on robotic hardware
Stay current with the latest robotics and AI research mentor team members and drive innovation

Qualifications / Requirements:

PhD/MS in Machine Learning Computer Science Robotics or related field and 3/6years of work experience
3 years of hands-on experience implementing and deploying ML models for robotic manipulation and experience with large multimodal ML models
Proven ability to take ML models from research prototype to production deployment
Mastery of Python for prototyping and C for performant deployable code
Strong proficiency in deep learning frameworks (e.g. PyTorch TensorFlow)
Strong experience with simulation platforms (e.g. MuJoCo Isaac Sim PyBullet) and sim-to-real transfer
Understanding of robot kinematics dynamics sensing and control
Ability to travel up to 5% domestic and international
Ability to work in a regulated environment in compliance with ISO 13485 and 21 CFR 820

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity age national origin disability protected veteran status or other characteristics protected by federal state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants needs. If you are an individual with a disability and would like to request an accommodation external applicants please contact us via internal employees contact AskGS to be directed to your accommodation resource.

#JNJMedTech-DS #JNJDataScience#LI-Hybrid

Required Skills:

Machine Learning Algorithms Robotic Control

Preferred Skills:

Computer Programming Cost-Benefit Analysis (CBA) Critical Thinking Data Science Industry Analysis Innovation Manufacturing Technologies Organizing Problem Solving Process Improvements Prototyping Quality Assurance (QA) Quality Control (QC) Research and Development Robotic Automation SAP Product Lifecycle Management Technical Credibility

The anticipated base pay range for this position is :

The anticipated base pay range for this position is $141000 to $227700 USD.

Additional Description for Pay Transparency:

Subject to the terms of their respective plans employees and/or eligible dependents are eligible to participate in the following Company sponsored employee benefit programs: medical dental vision life insurance short- and long-term disability business accident insurance and group legal insurance. Subject to the terms of their respective plans employees are eligible to participate in the Companys consolidated retirement plan (pension) and savings plan (401(k)). This position is eligible to participate in the Companys long-term incentive program. Subject to the terms of their respective policies and date of hire Employees are eligible for the following time off benefits: Vacation 120 hours per calendar year Sick time - 40 hours per calendar year; for employees who reside in the State of Washington 56 hours per calendar year Holiday pay including Floating Holidays 13 days per calendar year Work Personal and Family Time - up to 40 hours per calendar year Parental Leave 480 hours within one year of the birth/adoption/foster care of a child Condolence Leave 30 days for an immediate family member: 5 days for an extended family member Caregiver Leave 10 days Volunteer Leave 4 days Military Spouse Time-Off 80 hours Additional information can be found through the link below. Experience:

Staff IC