Junior Computer Vision Engineer | AI & Machine Learning
Our organization is at the forefront of applied artificial intelligence, pioneering solutions that redefine entire sectors. We operate as a distributed team of innovators and problem-solvers, committed to a culture of continuous learning and impactful creation. By joining us, you become part of a collective dedicated to pushing the boundaries of technology and delivering tangible value through intelligent systems. Your professional growth is our priority; we provide the mentorship and resources necessary to transform your ambitious ideas into reality.
Your Impact and Responsibilities
- Design and implement novel computer vision algorithms for tasks like object detection, segmentation, and image classification.
- Author clean, efficient, and well-documented Python code for image and video processing pipelines using libraries like OpenCV and Scikit-image.
- Train, validate, and rigorously test deep learning models (leveraging TensorFlow or PyTorch) to ensure exceptional accuracy and robustness.
- Meticulously debug and resolve complex issues within our AI systems, ensuring seamless performance in production environments.
- Collaborate on the integration of computer vision modules into larger application ecosystems and hardware platforms.
- Curate, augment, and maintain the large-scale datasets that are the lifeblood of our sophisticated machine learning models.
- Analyze and optimize model performance for speed and efficiency, especially for deployment on edge devices or in real-time scenarios.
- Work closely with cross-functional teams—including software developers and project managers—to translate ambitious project requirements into elegant technical solutions.
Core Qualifications
- A Bachelor's or Master's degree in Computer Science, Engineering, or a related field with a demonstrated focus on AI or Computer Vision.
- Solid programming proficiency in Python and hands-on experience with its scientific computing stack (e.g., NumPy, Pandas).
- Foundational knowledge of computer vision principles and practical experience with core libraries such as OpenCV.
- Demonstrable experience with at least one major deep learning framework, such as TensorFlow or PyTorch, through academic projects or internships.
- A systematic approach to problem-solving and debugging complex software systems.
- Excellent communication skills, with the ability to articulate technical concepts clearly to diverse team members.
Preferred Skills
- Familiarity with C++ for performance-critical code.
- Experience with cloud platforms (AWS, GCP, Azure) and their associated AI/ML services.
- Knowledge of containerization technologies like Docker for creating reproducible research environments.
- A strong understanding of modern version control systems, particularly Git.
- Exposure to MLOps principles and tools for model deployment and monitoring.