Machine Learning Engineer - Computer Vision

About Vionlabs

At Vionlabs, we’re shaping the future of content discovery through the power of AI. Our groundbreaking metadata enrichment platform helps the world’s leading streaming services, broadcasters, and media companies deliver hyper-personalized user experiences — from smarter recommendations to intuitive content search.

We combine deep tech, computer vision, and machine learning to understand content on a whole new level — analyzing emotions, pacing, and narrative structure to unlock what truly resonates with audiences.

As a fast-growing, product-driven company with global clients and a highly collaborative culture, we offer the opportunity to work at the forefront of AI innovation in media — where your ideas and engineering skills directly shape the viewing experiences of millions.

Your Role

We are looking for an experienced and hands-on Machine Learning Engineer specializing in Computer Vision to join our AI engineering team. You will design, build, and optimize deep learning models that power our content intelligence platform — including video understanding, scene segmentation, and multimodal embedding models.

Working closely with our ML researchers and platform engineers, you’ll turn research prototypes into scalable production models and help shape the future of AI-powered video analysis.

Your Responsibilities

• Develop and deploy state-of-the-art deep learning models for image and video understanding
• Work with large-scale datasets and build robust preprocessing and augmentation pipelines
• Design and implement training, validation, and inference workflows using TensorFlow/Keras and/or PyTorch
• Apply and adapt modern neural architectures, including CNNs, RNNs, and transformer-based models (e.g., ViT, CLIP)
• Collaborate on multimodal AI systems combining vision, audio, and text signals
• Optimize models for performance, including quantization, pruning, and accelerated inference on GPU/TPU
• Support model deployment in both cloud and edge environments using GCP Vertex AI and Kubernetes
• Work with MLOps engineers to ensure robust monitoring, versioning, and governance of models in production
• Contribute to cross-functional initiatives with product managers, data scientists, and backend developers

Your Skills

Required Skills & Experience

• 3+ years of experience developing and deploying deep learning models in the field of Computer Vision
• Strong expertise in neural network architectures, especially CNNs, RNNs, and transformer-based models (e.g., ViT, Swin, CLIP)
• Highly proficient in Python and frameworks like TensorFlow/Keras; experience with PyTorch is a plus
• Solid understanding of the machine learning lifecycle, including training, evaluation, deployment, and monitoring
• Experience in data preparation and maintaining image/video processing pipelines
• Familiarity with cloud-based ML environments, especially GCP Vertex AI, Cloud Storage, and BigQuery
• Strong knowledge of model performance optimization techniques (e.g., quantization, pruning, distillation)
• Understanding of evaluation metrics used in Computer Vision

Nice to Have

• Experience with video understanding tasks like scene detection, action recognition, or temporal modeling
• Familiarity with multimodal models and embeddings (e.g., CLIP, BLIP, VideoBERT)
• Exposure to MLOps tools and model versioning workflows
• Experience with edge deployments and GPU optimization for inference at scale
• Background in media, video processing, or streaming applications

Why Join Us?

• Work on cutting-edge AI that transforms how millions discover and engage with content
• Contribute to real-world systems with immediate product impact in a fast-moving industry
• Join a highly collaborative team at the intersection of machine learning and media
• Competitive salary and benefits
• Flexible, remote-friendly work environment
• Opportunities for continuous learning and growth in a deep tech company