We are looking for an experienced Machine Learning Engineer with deep expertise in Computer Vision and Generative AI to join our team and own the end-to-end development and improvement of various innovative problem statements. You will take full ownership of projects, from ideation to delivery, ensuring successful deployment as well as ML monitoring post-launch.
What You Will Be Doing
- Own the entire lifecycle of the Vision and GenAI problem statement, from initial concept throughout deployment.
- Research, design, develop, and deploy robust and scalable ML systems for various Vision use-cases.
- Optimize model training and inference pipelines to maximize GPU utilization and minimize costs.
- Collaborate with Product, Backend, and Platform teams to define project timelines, ensure alignment of business goals, and drive strong execution.
What We're Looking For
- Solid foundation in Deep Learning, Computer Vision, and Generative AI, with a proven experience of 3-5 years, preferably in a fast-paced startup environment.
- In-depth and practical knowledge of CNNs, GANs, VAEs, Diffusion models, and Inpainting methods, image processing techniques, text-to-image and image-to-image generation architectures, etc.
- Strong programming skills in Python and proficiency with ML frameworks (e., Tensorflow, Pytorch, JAX) - create code that is understandable, simple, clean, and easily shared with others.
- Experience in deploying Vision models on edge devices, optimizing for resource constraints.
- Knack for staying up to date with the latest research and trying out unconventional, out-of-the- box ideas.
- Passion for problem-solving and creative thinking, with the ability to break down complex and abstract problems into actionable items.
- Self-motivated to build, with an ability to thrive with minimal oversight and process.
Bonus Points:
- Experienced with 3D computer vision, video processing, and text-to-video, image-to-video generation.
- Knowledge of the Rust programming language for implementing the inference pipelines.
- Experienced working with highly skewed and imbalanced data.
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
