Computer Vision Engineer (The Visual Intelligence Architect)
Unreal Gigs
San Francisco, california
Job Details
Full-time
Full Job Description
Are you excited by the challenge of developing algorithms that enable machines to interpret and make sense of visual data? Do you excel at creating computer vision systems that recognize, analyze, and respond to real-world environments? If you’re ready to apply advanced vision technology in robotics, autonomous systems, or industrial applications, our client has the ideal role for you. We’re looking for a Computer Vision Engineer (aka The Visual Intelligence Architect) to design and implement vision systems that empower machines to see and interact intelligently.
As a Computer Vision Engineer at our client, you’ll work with multidisciplinary teams to build solutions that process visual information, detect objects, and make real-time decisions. Your expertise in image processing, machine learning, and algorithm development will be essential in delivering reliable and scalable vision systems that can perform in various dynamic environments.
Key Responsibilities:
- Develop and Optimize Computer Vision Algorithms:
- Design, develop, and optimize algorithms for object detection, tracking, recognition, and segmentation. You’ll leverage deep learning and traditional vision techniques to build efficient solutions for real-world applications.
- Implement and Train Machine Learning Models:
- Create and train machine learning models to interpret and classify visual data. You’ll use frameworks like TensorFlow and PyTorch to build models that generalize well and perform accurately.
- Integrate Vision Systems into Robotics and Automation Platforms:
- Collaborate with robotics, automation, and software teams to integrate vision systems into operational workflows. You’ll ensure that vision data flows seamlessly to other system components for responsive, real-time performance.
- Perform Calibration and Testing for Vision Hardware:
- Calibrate and test cameras, sensors, and optics to ensure precise data capture and interpretation. You’ll work with LIDAR, RGB-D, stereo cameras, or other sensors, ensuring compatibility with system requirements.
- Optimize for Real-Time Processing and Embedded Applications:
- Adapt algorithms to run efficiently on edge devices, embedded systems, or specialized hardware like GPUs. You’ll focus on achieving high-speed, low-latency performance for real-time applications.
- Collaborate on Data Collection and Annotation Processes:
- Work with data scientists and annotation teams to collect and prepare labeled datasets for training models. You’ll refine datasets to improve accuracy and robustness in various conditions.
- Stay Updated on Computer Vision Advancements:
- Continuously research new techniques, tools, and methodologies in computer vision and machine learning. You’ll incorporate the latest advancements to enhance system capabilities and stay at the cutting edge of technology.
Requirements
Required Skills:
- Expertise in Computer Vision and Image Processing: Strong understanding of computer vision concepts, including object detection, segmentation, and pattern recognition, with experience using libraries like OpenCV and scikit-image.
- Proficiency in Deep Learning and Machine Learning Frameworks: Experience with TensorFlow, PyTorch, or Keras for developing and training vision models.
- Programming Skills in Python and C++: Proficiency in programming languages for developing algorithms, with experience in ROS (Robot Operating System) as a plus.
- Experience with Sensors and Hardware Calibration: Familiarity with camera calibration, stereo vision, and other vision hardware, such as LIDAR and depth sensors.
- Analytical and Problem-Solving Skills: Strong troubleshooting skills for refining algorithms, improving accuracy, and optimizing performance in real-world conditions.
Educational Requirements:
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field. Equivalent experience in computer vision engineering may be considered.
- Certifications or specialized courses in machine learning, computer vision, or image processing are advantageous.
Experience Requirements:
- 3+ years of experience in computer vision engineering, with a focus on robotics, autonomous systems, or similar applications.
- Experience with embedded or edge computing for vision applications (e.g., NVIDIA Jetson, OpenCV on ARM platforms) is beneficial.
- Familiarity with 3D computer vision, SLAM, or multi-view geometry is a plus.
Benefits
- Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
- Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
- Work-Life Balance: Flexible work schedules and telecommuting options.
- Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
- Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
- Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
- Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
- Tuition Reimbursement: Financial assistance for continuing education and professional development.
- Community Engagement: Opportunities to participate in community service and volunteer activities.
- Recognition Programs: Employee recognition programs to celebrate achievements and milestones.