Job Description

We are seeking an enthusiastic Associate Machine Learning (ML) Scientist with a specialization in computer vision applications to join our AI development team. The ideal candidate will have experience designing, developing, and deploying computer vision solutions to tackle real-world problems. This role involves working on high-impact AI applications and collaborating closely with data scientists, engineers, and domain experts to deliver reliable, scalable AI solutions.
Key Responsibilities
? Develop robust, scalable machine learning models addressing complex computer vision challenges.
? Assist in the design and implementation of image and video analysis models, including object detection, face recognition, and image classification.
? Translate real-world challenges into well-defined AI/ML problem statements.
? Build and evaluate AI solutions through rigorous experimentation and performance benchmarking.
? Optimize and deploy computer vision models on various platforms, including edge and mobile devices.
? Curate, preprocess, and manage image and video datasets for model development and validation.
? Define and apply appropriate evaluation metrics for computer vision tasks, including accuracy, precision, recall, F1-score, and real-time inference benchmarks.
? Collaborate with cross-functional teams, including software engineers, product managers, and domain specialists, to deliver end-to-end AI solutions.
? Stay current with emerging research and best practices in computer vision, deep learning, and related fields.
Requirements
? Educational Background: Bachelor's, Master's, or equivalent degree in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, Physics, or a related quantitative discipline.
? Experience: 1-3 years of professional experience in developing and deploying machine learning solutions, with a strong focus on computer vision applications.
? Technical Skills:
? Proficiency in Python and ML libraries such as TensorFlow, PyTorch, OpenCV, and scikit-learn.
? Solid understanding of deep learning architectures for image and video processing (e.g., CNNs, ResNet, MobileNet, EfficientNet).
? Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker) is preferred.
? Strong communication skills with the ability to translate technical concepts into actionable insights for cross-functional teams.
? Passion for applied machine learning and a willingness to adapt to diverse problem domains and real-world constraints.
Preferred Qualifications
? Prior experience deploying computer vision models on mobile or edge devices.
? Experience working with face detection and recognition models.
? Familiarity with MLOps practices for model deployment, monitoring, and lifecycle management.
? Demonstrated ability to work independently and collaboratively in fast-paced, solution-driven environments.
? Exposure to ethical and responsible AI practices in computer vision applications.

Skills Required