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Senior Deep Learning Engineer - San Antonio, TX

Robotic Research
San Antonio, TX, United States
Full-time

Company Overview :

Robotic Research has provided vehicle autonomy solutions for over 20 years and is a global leader in self-driving technology.

Our AutoDrive® autonomy kit is designed to tackle the industry’s greatest challenges from GPS-denied environments to mixed-traffic and unpaved roads.

The commercial division, RR.AI, works with trusted OEM partners to deliver these autonomous solutions across the United States, Canada, Australia, Europe, and Saudi Arabia.

The defense division of Robotic Research designs and implements solutions that improve the efficiency and effectiveness of logistics, enhance situational awareness, and save lives by extending the warfighter’s reach through transformable robots, automated vehicles, and GPS-denied localization devices.

We offer a fast-paced environment where innovation comes first, and a breadth and depth of skills, knowledge, and interests are highly valued.

We are leading this dynamic revolution in technology with team members throughout the U.S including our main offices in Clarksburg, MD and San Antonio, TX.

Position Responsibilities :

The Senior Deep Learning Engineer will be responsible for

  • Develop novel and efficient real time solutions for a wide variety of perception tasks.
  • Research and apply deep learning to detection and perception challenges
  • Understand new perception challenges by analyzing the real world data collected on our vehicle fleet.
  • Creatively and collaboratively build deep learning models that can predict the future behavior of other road users in real-time

Required Skills & Abilities :

  • Software development experience in C++ and python
  • Experience with at least one existing deep learning frameworks like Pytorch, Tensorflow, Caffe or other relevant machine learning libraries.
  • Knowledge of deep learning topics such as detection, segmentation, pose estimation, and spatio- temporal analysis.
  • Relevant publications in conferences is a bonus.

Education & Experience :

  • Degree in computer science, robotics, or related field, or with equivalent industrial experience
  • 5+ years of similar academic and / or professional working experience

Preferred Qualifications :

  • Experience in applying deep learning on autonomous vehicles.
  • Experience in traditional ML methods (eg, regression, decision trees, and kernel methods) and strong knowledge of optimization.

Tele-work : Hybrid

Travel : Domestic & International (10%)

Benefits :

Robotic Research is excited to offer the following benefits :

  • Company holidays
  • Flexible work schedules
  • Paid time off
  • Competitive medical, dental & vision plans
  • 401k contribution plan with up to 4% match
  • Employer paid short-term & long-term disability insurance
  • Employer paid life insurance
  • Voluntary life insurance
  • Relocation reimbursement for qualifying situations
  • Dog Friendly Office!
  • Tuition reimbursement
  • Discretional annual bonus and profit sharing
  • Employee assistance program

All benefits are subject to change. Please discuss with a member of the Robotic Research HR team for details.

Employment is conditioned upon successful completion of a thorough background screening and drug test.

Diversity and Equal Opportunity Statement : At Robotic Research, we don’t just accept differences, we celebrate them! We strive to attract, develop and retain curious & highly qualified individuals representing a variety of backgrounds, cultures, skills & perspectives.

Robotic Research is committed to building a diverse team and is proud to be and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, marital status, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

19 days ago
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