Requirements
• MS or PhD (preferred) in Computer Science, Engineering, or a related field, or equivalent work experience,
• 5+ years of hands-on experience in machine learning and computer vision, with a strong track record of deploying models into production,
• Proficiency in Python and ML frameworks (PyTorch/TensorFlow/ONNX/TensorRT). Experience with C++ is a plus,
• Strong experience with model optimization (e.g., quantization, pruning) and deployment on various platforms (cloud, edge, or mobile),
• Familiarity with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration (ECS, Kubernetes),
• Proven experience in building and maintaining data pipelines (e.g., Airflow),
• Strong understanding of the agile development process and CI/CD pipelines and tools (e.g., Github Actions, Jenkins),
• Excellent communication skills, capable of presenting complex technical information clearly,
• Experience in high-growth, innovative environments is a plus,
• Publications in top-tier conferences (e.g., CVPR, ICCV, NeurIPS) are a strong plus
What the job involves
• We are seeking a Senior Machine Learning Engineer to play a key role to join our growing team,
• As a key member of the Advanced Technologies team, you will play a critical role in designing, developing, and deploying state-of-the-art computer vision and recommendation models that power our core products and solutions,
• Your work will involve tackling challenging problems in object detection, tracking, OCR, video analytics, and multi-modal systems,
• This role involves a unique blend of technical expertise in data and machine learning, innovative thinking, and a passion for data-driven solutions,
• Design, develop, and deploy advanced computer vision models for real-world applications, including object detection, itracking, OCR, image search, and scene understanding,
• Build and optimize deep learning models, ensuring high accuracy, performance, and scalability for deployment in production environments,
• Explore and integrate multi-modal approaches, leveraging visual, textual, and other data modalities for robust solutions,
• Collaborate with cross-functional teams, including data engineers and software engineers to deliver end-to-end solutions,
• Lead the design and implementation of scalable pipelines for data processing, model training, and model deployment,
• Optimize models for performance on various hardware platforms, including CPUs, GPUs, and edge devices,
• Conduct thorough experimentation and A/B testing to validate model effectiveness and ensure alignment with business objectives,
• Mentor junior team members, providing technical guidance and fostering professional growth,
• Write clean, efficient, and maintainable code while adhering to best practices in software engineering and machine learning
