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- Tasks: Lead the development of cutting-edge computer vision algorithms for autonomous systems.
- Company: Join a dynamic defence-focused start-up in Austin, TX, pushing technological boundaries.
- Benefits: Enjoy a competitive salary, equity package, health insurance, and generous paid time off.
- Why this job: Be part of a mission-driven team creating impactful technology in a collaborative environment.
- Qualifications: Master’s or PhD in relevant fields with 6+ years of experience in machine learning and computer vision.
- Other info: Relocation to Austin, TX is required; mentorship opportunities available.
The predicted salary is between 72000 - 144000 £ per year.
Computer Vision Engineer / Machine Learning Engineer required to join an exciting defense-focused start-up manufacturer based in Austin, TX.
The successful Computer Vision Engineer / Machine Learning Engineer will ideally have a Master’s or PhD in a relevant discipline such as Computer Science or a related field.
Package
$110,000 – $220,000
Equity Package
Health, Dental, Vision Insurance
Paid Time Off
Computer Vision Engineer / Machine Learning Engineer Responsibilities:
- Spearhead the creation and refinement of computer vision algorithms for autonomous gun turret systems, with a primary focus on real-time drone detection, tracking, and classification.
- Develop and implement machine learning models optimized for performance in resource-constrained environments, delivering high levels of accuracy and reliability.
- Work closely with electrical engineers to seamlessly integrate computer vision systems into the turret’s hardware architecture.
- Perform comprehensive testing and validation of algorithms across diverse environmental conditions to ensure their robustness and reliability.
- Provide mentorship and leadership to junior engineers, fostering expertise in machine learning and computer vision throughout the team.
- Facilitate the progression from prototype designs to military-grade autonomous turrets, contributing to the development of system variants tailored for different weapon systems and engagement distances.
- Ensure that all algorithms align with the stringent performance and reliability standards expected of defense-grade systems, adhering to best practices for safety-critical applications.
Computer Vision Engineer / Machine Learning Engineer Requirements:
- Master’s Degree or PhD in Computer Science, Electrical Engineering, or a related field, with a strong academic and professional focus on machine learning and computer vision.
- A minimum of 6 years of experience developing machine-learning-driven computer vision systems, ideally within robotics or real-time operational contexts.
- Demonstrated expertise in designing and deploying real-time computer vision systems in environments with resource constraints or within safety-critical industries.
- Advanced proficiency in Python and C++ programming languages.
- Hands-on experience with leading machine learning frameworks like TensorFlow, PyTorch, or similar tools.
- Strong background in embedded systems and experience integrating computer vision algorithms into hardware platforms.
- In-depth knowledge of various sensors, including cameras, LIDAR, and RADAR, and their application in autonomous systems.
- A collaborative team player with a proven ability to mentor junior engineers and tackle challenging technical problems.
- Must be commutable or willing to relocate to Austin, TX.
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Machine Learning Engineer employer: Verto People, Ltd.
Contact Detail:
Verto People, Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network with professionals in the defence and machine learning sectors. Attend industry conferences, workshops, or meetups in Austin to connect with potential colleagues and learn about the latest trends in computer vision technology.
✨Tip Number 2
Showcase your hands-on experience by working on personal projects or contributing to open-source initiatives related to computer vision and machine learning. This will not only enhance your skills but also provide tangible examples of your work during interviews.
✨Tip Number 3
Familiarise yourself with the specific technologies and frameworks mentioned in the job description, such as TensorFlow and PyTorch. Consider taking online courses or tutorials to deepen your understanding and demonstrate your commitment to continuous learning.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm problems, especially those related to real-time systems and resource-constrained environments. Use platforms like LeetCode or HackerRank to sharpen your problem-solving skills.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in machine learning and computer vision. Emphasise any projects or roles where you've developed algorithms or worked with real-time systems, especially in defence or robotics.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the job description. Mention your academic qualifications, relevant experience, and how you can contribute to the company's goals, particularly in developing autonomous systems.
Showcase Technical Skills: In your application, clearly list your technical skills, especially your proficiency in Python, C++, and any machine learning frameworks like TensorFlow or PyTorch. Provide examples of how you've applied these skills in past projects.
Highlight Leadership Experience: If you have experience mentoring junior engineers or leading projects, make sure to include this in your application. This role requires collaboration and leadership, so demonstrating these qualities will strengthen your application.
How to prepare for a job interview at Verto People, Ltd.
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with machine learning frameworks like TensorFlow and PyTorch. Highlight specific projects where you've developed computer vision systems, especially in resource-constrained environments.
✨Demonstrate Problem-Solving Skills
Expect technical questions that assess your ability to tackle complex challenges. Prepare examples of how you've approached difficult problems in past projects, particularly those related to real-time operational contexts.
✨Emphasise Collaboration and Mentorship
Since the role involves mentoring junior engineers, be ready to share your experiences in team settings. Discuss how you've fostered collaboration and helped others grow in their technical skills.
✨Understand the Defence Industry Standards
Familiarise yourself with the performance and reliability standards expected in defence-grade systems. Be prepared to discuss how you ensure safety and robustness in your algorithms, especially in high-stakes environments.
