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Computer Vision Engineer

About us:

Protex AI is a VC-backed technology company building a privacy-preserving computer vision platform to enable proactive Health and Safety (EHS) workflows. We leverage the domain knowledge of EHS teams to help our computer vision system understand the concept of danger, preventing accidents before they occur. Every worker has the right to go home safe and healthy every day and every employer has the responsibility to provide a safe work environment. Our mission at Protex AI is to ensure that this is the case in every facility around the world by empowering EHS teams to adopt proactive safety cultures and in doing so realise an injury-free workplace.

About the Role

We are seeking a Computer Vision Engineer that will lead the development and optimization of our cutting-edge computer vision systems that transform safety standards in factories and warehouses worldwide. The ideal candidate excels in computer vision technology, thrives under pressure, and expertly manages multiple projects while maintaining high standards. If you're passionate about pushing the boundaries of AI-driven safety solutions and have a track record of delivering exceptional results, we want to talk to you. Join us in building systems that revolutionize workplace safety and impact the well-being of thousands of workers.

About the Team

You'll be joining our Computer Vision Operations (CV Ops) team, a dedicated group of engineers committed to developing and deploying state of the art CV technologies to the real world. We maintain a fast-paced, collaborative environment where team members are empowered to make significant technical decisions while supporting each other's growth and development.

What You’ll Do

  • Model Development & Enhancement: Build, train, and optimize computer vision models for object detection, classification, and pose estimation, ensuring robust, real-time performance.

  • Data Pipeline Management: Curate, refine, and maintain specialized datasets. Oversee annotation projects and ensure data integrity for model training and validation.

  • Production Integration: Work with cross-functional teams to integrate computer vision solutions into our production pipeline, ensuring scalability, efficiency, and alignment with client needs.

  • Continuous Improvement: Experiment with new technologies, methodologies, and frameworks to enhance model accuracy, reduce inference time, and improve overall system performance.

  • Drive projects with a sense of urgency, maintaining high standards for model quality and deployment readiness

  • Effectively manage multiple concurrent projects while ensuring consistent delivery

  • Set and maintain high expectations for team output and model performance

  • Implement and maintain robust testing frameworks to ensure reliability across different environments

  • Proactively identify bottlenecks and propose solutions to improve team efficiency

What You’ll Need

  • Bachelor's degree in Computer Science, Engineering, or related field

  • 5+ years of experience in computer vision or related field

  • Strong background in deep learning frameworks (PyTorch, TensorFlow)

  • Expertise in Python and experience with C++

  • Experience with AWS cloud services (S3, EC2, Lambda) and orchestrating compute intensive workloads (Batch, Apache Airflow)

  • Proven track record of deploying computer vision models in production

  • Deep understanding of computer vision fundamentals and current state-of-the-art techniques

  • Experience with object detection, classification, and pose estimation models

  • Proficiency in managing and defining data annotation projects

  • Familiarity with MLOps tools (Voxel 51, AWS Batch, Weights & Biases)

  • Knowledge of privacy-preserving ML techniques is a plus

What You’ll Bring

  • Strong sense of urgency and ability to drive projects to completion

  • Exceptional organizational skills with proven ability to manage multiple projects simultaneously

  • High standards for quality and attention to detail

  • Strategic thinking with ability to anticipate and prevent potential issues

  • Excellent communication skills for collaborating with technical and non-technical stakeholders

  • Track record of setting and maintaining high expectations for team performance

  • Adaptability and eagerness to learn new technologies

Protex AI is an inclusive and equal opportunities employer. We are committed to creating an equitable workplace for everyone regardless of gender, civil status, family status, sexual orientation, religion, age, disability, education level, or race.

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Average salary estimate

$140000 / YEARLY (est.)
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$120000K
$160000K

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What You Should Know About Computer Vision Engineer, Protex AI

Are you ready to take your career to the next level? Protex AI is on the lookout for a talented Computer Vision Engineer to join our innovative team. At Protex AI, we are revolutionizing workplace safety through a privacy-preserving computer vision platform dedicated to proactive Health and Safety (EHS) workflows. As part of our mission, we empower EHS teams around the world to foster safety cultures that ensure every worker goes home safe and sound. In this role, you'll lead the development and optimization of cutting-edge computer vision systems that have real-world implications for safety standards in factories and warehouses. We are looking for an expert who is passionate about AI-driven safety solutions and possesses a knack for managing multiple high-stakes projects with ease. Your duties will include model development, data pipeline management, and integration of computer vision solutions into our production processes, maintaining a high standard for quality in each model deployed. You will be a key player in setting the tone for your team's output while collaborating across functions to push the boundaries of what's possible in workplace safety. If you have a robust background in computer vision, experience with deep learning frameworks like PyTorch and TensorFlow, and a desire to drive change in the industry, we want to hear from you! Join Protex AI and help us transform the future of workforce safety for thousands of workers across the globe.

Frequently Asked Questions (FAQs) for Computer Vision Engineer Role at Protex AI
What are the primary responsibilities of a Computer Vision Engineer at Protex AI?

As a Computer Vision Engineer at Protex AI, your main responsibilities include developing and optimizing computer vision models for tasks such as object detection, classification, and pose estimation. You'll manage specialized data pipelines, oversee data integrity, and ensure seamless integration of these solutions into production environments while maintaining high performance standards.

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What qualifications do I need to be a Computer Vision Engineer at Protex AI?

To qualify for the Computer Vision Engineer position at Protex AI, you need a Bachelor's degree in Computer Science or a related field, along with at least 5 years of experience in computer vision. A strong background in deep learning frameworks such as PyTorch or TensorFlow and proficiency in languages like Python and C++ are also essential.

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What technologies and tools will a Computer Vision Engineer at Protex AI work with?

At Protex AI, Computer Vision Engineers work with a range of technologies and tools, including deep learning frameworks (PyTorch, TensorFlow), AWS cloud services (S3, EC2, Lambda), and MLOps tools such as Voxel 51 and Weights & Biases. You will utilize these tools for model training, data annotation, and production deployment.

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How does Protex AI ensure the quality and reliability of the computer vision models?

Protex AI emphasizes quality and reliability by implementing robust testing frameworks across various environments to validate the computer vision models. Continuous improvement through experimentation with new methodologies and proactive identification of bottlenecks are key practices in our development process.

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What type of work environment can I expect as a Computer Vision Engineer at Protex AI?

Working as a Computer Vision Engineer at Protex AI means joining a collaborative and fast-paced environment within the Computer Vision Operations team. You'll be encouraged to make significant technical decisions, support your colleagues' growth, and consistently contribute to a proactive safety culture while developing cutting-edge technology.

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Common Interview Questions for Computer Vision Engineer
Can you describe your experience with computer vision frameworks like PyTorch and TensorFlow?

When answering this question, highlight specific projects where you utilized PyTorch or TensorFlow to build or deploy computer vision models. Discuss the challenges encountered, how you overcame them, and any quantifiable results that demonstrate your expertise.

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How do you manage data pipelines for computer vision projects?

Talk about your approach to curating and maintaining high-quality datasets. Discuss your experience with data annotation and how you ensure data integrity for model training and validation. Mention tools or frameworks you've used to streamline these processes.

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What strategies do you use for model optimization and improving performance?

Discuss various techniques you've employed for optimizing computer vision models, such as hyperparameter tuning, model compression, and comparing different architectures. Be sure to include examples of how these strategies led to tangible improvements in model accuracy or inference times.

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Can you explain a complex computer vision project you worked on and your role in it?

Share detailed insights about a challenging project where your contributions were pivotal. Focus on your responsibilities, the technologies used, any collaboration with cross-functional teams, and the outcomes achieved. This showcases your problem-solving abilities and teamwork.

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How do you ensure your models are reliable and produce consistent results?

Emphasize how you implement testing frameworks and continuous validation processes to verify model reliability. Mention specific metrics you use to measure model performance and any practices you have for ongoing evaluations once the model is deployed.

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What is your experience with MLOps tools, and how have you utilized them?

Explain your familiarity with MLOps tools like AWS Batch or Voxel 51, detailing how you have used them to manage workflow, automate processes, or track model performance. Strong examples of efficiency improvements will greatly strengthen your answer.

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How do you handle tight deadlines and multiple projects?

Discuss your organizational skills and strategies for prioritizing tasks. Provide examples of how you successfully managed competing demands in previous roles, highlighting your ability to work under pressure while maintaining high-quality standards.

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What are the latest trends in computer vision that interest you?

This is an opportunity to showcase your knowledge of the field. Discuss emerging technologies or techniques that excite you and explain how they could potentially align with Protex AI’s mission or your vision for future innovations in safety solutions.

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Can you talk about a failure you experienced in a computer vision project and what you learned?

Be honest and share a genuine experience where a project didn’t go as planned. Focus on the lessons learned and how you adapted your approach in subsequent projects. Employers appreciate self-awareness and the ability to learn from challenges.

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Why do you want to work for Protex AI as a Computer Vision Engineer?

Express genuine enthusiasm for Protex AI’s mission of promoting safety and well-being through technology. Relate your values to the company’s culture and describe how your skills align with the goals of the Computer Vision Engineering team.

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Full-time, remote
DATE POSTED
December 18, 2024

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