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Senior Perception Engineer, Facial Recognition

Who We Are

Sauron protects your family and home, bringing the innovations of autonomous robots and self-driving cars to residential security. Our team is led by veteran entrepreneurs and roboticists, alumni of Zipline, Tesla, and Cloud Kitchens. Sauron has raised an $18M seed round led by A* and Atomic with participation from other leading venture capital firms and angel investors, including 8VC and Flock Safety CEO Garret Langley. 

The Role | Perception Engineer, Facial Recognition

We Value

  • Collaboration, pair programming, and teamwork.

  • Making small improvements and shipping code to production continuously.

  • Taking ownership across the stack.

  • Test-driven development, and refactoring regularly to keep our codebases healthy.

You Will Contribute By

  • Leading development efforts on facial recognition systems.

  • Extracting the maximum value from our sensors, fusing all observations available while being robust to occlusions, poor lighting and disguises

  • Leading the collection, labeling, and management of datasets to train and evaluate ML models for facial recognition.

  • Leveraging state of the art models for facial recognition and pushing them to the limits of their performance in this problem domain.

  • Performing trade studies to understand the value of new sensors or processing approaches to system reliability.

  • Analyzing the performance of systems both in simulation and using data from deployments in the field to find headroom and devise solutions to reduce it.

  • Probing the inner workings of neural networks to uncover and mitigate edge case failures.

  • Designing systems that can understand and communicate when they are not working well.

  • Contributing to machine learning infrastructure (e.g. distributed training, continuous model integration, data management, and evaluation of production systems).

Your Background Includes

  • 5+ years of professional experience with machine learning for hardware products in a safety-critical field, e.g. aerospace, robotics, medical devices, autonomous vehicles.

  • Passionate about ML, both robust engineering and research challenges.

  • A deep understanding of the theory and practice of modern machine learning techniques.

  • A clear grasp of basic linear algebra, optimization, statistics, and algorithms.

  • Experienced at all facets of training and using deep-learning models, including writing custom layers/operations, optimizing networks for inference on edge compute, reproducibility and evaluation.

  • Extensive experience working with Pytorch, Tensorflow or other modern deep learning frameworks.

  • Familiar with the use of VLMs and other multi-modal models for semantic scene understanding and description.

  • Able to solve complex problems with little supervision.

  • Excellent communicator, both written and verbal.

  • A generalist mindset and can dive in wherever the bottlenecks are, whether that be spooling up cloud compute services to optimizing for embedded systems.

Average salary estimate

$135000 / YEARLY (est.)
min
max
$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Perception Engineer, Facial Recognition, Sauron

At Sauron, we're on a mission to revolutionize residential security with cutting-edge technology. As a Senior Perception Engineer focusing on Facial Recognition, you'll be at the forefront of developing systems that protect families and homes using state-of-the-art autonomous robots and self-driving cars. With a team packed with seasoned entrepreneurs and roboticists from top companies like Zipline and Tesla, your role will entail leading the charge on facial recognition systems, pushing technological boundaries to ensure they can operate under challenging conditions like poor lighting and disguises. If you're passionate about machine learning, enjoy collaborative pair programming, and take pride in making continuous improvements to production code, this is the ideal opportunity for you. You'll be responsible for collecting and managing datasets to train and evaluate machine learning models, designing robust systems that can self-diagnose, and conducting analyses that drive innovations in both software and hardware solutions. If you have a strong background in machine learning within safety-critical fields—such as aerospace or robotics—and are a great communicator with a knack for problem-solving, we would love to have you join our enthusiastic team in San Francisco. This position offers not just challenges but also the chance to make a meaningful impact in the world of security technology. Come be a part of our exciting journey at Sauron!

Frequently Asked Questions (FAQs) for Senior Perception Engineer, Facial Recognition Role at Sauron
What are the key responsibilities of a Senior Perception Engineer at Sauron?

At Sauron, a Senior Perception Engineer will lead the development of facial recognition systems, enhancing the performance of these systems by analyzing and managing datasets to facilitate machine learning models. They will focus on maximizing sensor value while addressing common challenges like poor lighting and occlusions. This role also involves rigorous testing, trade studies for new sensor implementation, and ensuring the systems can communicate their operational status.

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What qualifications are needed for the Senior Perception Engineer position at Sauron?

Candidates must have at least 5 years of professional experience with machine learning for hardware products, particularly in safety-critical sectors such as autonomous vehicles or robotics. A strong understanding of machine learning theories and practical applications, alongside proficiency in frameworks like Pytorch and Tensorflow, is essential. Additionally, a solid grasp of linear algebra, optimization, and algorithms will greatly benefit applicants.

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How does Sauron approach teamwork for the Senior Perception Engineer role?

Teamwork is a cornerstone at Sauron. As a Senior Perception Engineer, you'll engage in collaborative efforts that prioritize pair programming and knowledge sharing. The environment encourages ongoing code improvements and leveraging collective expertise to tackle complex machine learning challenges effectively.

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What kind of machine learning techniques will the Senior Perception Engineer utilize at Sauron?

In this role at Sauron, you'll work with advanced machine learning techniques tailored for facial recognition systems. This includes training deep-learning models, writing custom layers, optimized network inference, and employing various multi-modal models for enhanced scene understanding.

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What makes the Senior Perception Engineer role at Sauron unique?

What truly sets the Senior Perception Engineer position at Sauron apart is the blend of cutting-edge technology in autonomous systems with a focus on safety and reliability. You'll have the opportunity to lead pioneering projects that have real-world applications, all while being part of a motivated team that values innovation and continuous improvement.

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Common Interview Questions for Senior Perception Engineer, Facial Recognition
Can you describe your experience with deep learning frameworks specific to facial recognition?

During your interview, emphasize your hands-on experience with frameworks like Pytorch and Tensorflow. Describe specific projects where you trained models, the challenges faced, and how you optimized performance for facial recognition tasks. Mention any unique techniques you developed to improve model accuracy and speed.

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What strategies do you use to handle occlusions and poor lighting in facial recognition systems?

Discuss techniques such as data augmentation, which can help simulate diverse conditions, and using advanced algorithms that can effectively recognize faces despite occlusions or poor lighting. You might also share experiences related to model training or sensor enhancement to achieve better results.

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How do you ensure the reliability of facial recognition systems?

Detail your approach to testing and validating models, including performance metrics you employ and your experience with field testing. Talk about how you use continuous integration for model evaluation and improvement and how you perform trade studies to assess new sensor technologies.

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Can you explain a challenging machine learning problem you solved in your previous role?

Select a problem relevant to facial recognition or safety-critical applications and provide context. Walk through your methodology for troubleshooting, the solution you implemented, and the results achieved, emphasizing what you learned from the experience.

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How do you stay current with advancing machine learning technologies?

Discuss your methods for ongoing learning such as attending conferences, participating in online courses, or engaging with professional communities. Mention any publications you follow or contributions you've made that reflect your commitment to staying ahead in the field.

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What is your experience with dataset management for training machine learning models?

Explain how you have collected, cleaned, and labeled data in your previous projects. Outline procedures you’ve implemented to ensure data quality and integrity, and discuss the tools used for managing large datasets effectively.

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Describe a time when you had to communicate technical information to a non-technical team member.

Provide an example where clear communication was crucial. Explain your approach to breaking down complex concepts into easily understandable terms and how it helped ensure successful collaboration.

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How do you approach performance analysis for deployed systems?

Share your systematic approach to evaluating system performance post-deployment. Discuss the tools and metrics you use to gather data and how you leverage this information to inform iterative improvements.

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What do you consider when selecting sensors for facial recognition systems?

Mention critical factors like sensor specifications, compatibility with existing systems, environmental resilience, and cost-effectiveness. Discuss any experience you have with analyzing sensor performance data to inform decisions.

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How do you manage project priorities in a fast-paced environment like Sauron?

Explain your strategies for prioritizing tasks, such as aligning with team goals, assessing impact, and using project management tools. Highlight your flexibility and willingness to adapt based on ongoing project needs and deadlines.

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Full-time, on-site
DATE POSTED
December 13, 2024

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