Lead Machine Learning Engineer Computer Vision

Posted 21d ago

Lead Machine Learning Engineer Computer Vision - Veracity Group | Career Page

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Job Openings Lead Machine Learning Engineer Computer Vision

Lead the design and development of end-to-end computer vision systems, from data acquisition and preprocessing to model deployment and monitoring.
Architect scalable ML pipelines for vision domain including detection, segmentation, and multimodal learning, ensuring reliability in both batch and real-time environments.
Drive research and adoption of state-of-the-art CV and ML techniques (e.g., Transformers, Vision-Language Models, diffusion models) to solve complex image understanding problems.
Oversee the collection, annotation, and augmentation of training datasets, ensuring diversity and quality for robust model performance.
Build frameworks for model experimentation, reproducibility, and lifecycle management (MLflow, Weights & Biases, or similar).
Collaborate with data engineers to integrate ML workflows into scalable data pipelines and ensure smooth deployment on cloud platforms (AWS, Azure, GCP).
Partner with product and business teams to translate business needs into ML solutions, balancing research depth with delivery timelines.
Establish and enforce best practices for ML code quality, testing, version control, and CI/CD pipelines.
Mentor and lead a team of ML/CV engineers, conducting code reviews, guiding experiments, and fostering a culture of technical excellence.
Represent the ML team in cross-functional discussions, contributing to long-term AI/ML strategy and roadmap.

Bachelors or master's degree in computer science, Machine Learning, Computer Vision, or related field.
5+ years of professional experience in computer vision and machine learning engineering, with at least 2+ years in a technical leadership role.
Strong expertise in Python and ML/CV frameworks: PyTorch, TensorFlow, OpenCV.
Proven experience with deep learning architectures (CNNs, RNNs, Transformers, Vision-Language Models).
Hands-on experience with segmentation, object detection, image similarity, and multimodal approaches.
Experience in designing scalable ML pipelines with tools such as Apache Airflow, Docker, and Kubernetes.
Familiarity with cloud-based ML platforms (AWS Sagemaker, GCP Vertex AI, Azure ML).
Solid background in model monitoring, explainability, and performance optimization.
Strong leadership and communication skills, with a track record of mentoring engineers and managing cross-team initiatives.

Research experience or publications in computer vision, multimodal AI, or generative models.
Exposure to 3D vision, AR/VR, CAD/BIM, or graphics pipelines.
Knowledge of synthetic data generation, simulation environments, or reinforcement learning.
Experience with federated learning, edge AI, or on-device ML optimization.

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