Senior Machine Learning Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Take full ownership of the entire lifecycle for Vision and GenAI problem statements, from the initial concept to deployment.

• Conduct research, design, develop, and implement robust and scalable machine learning systems tailored for Vision use cases.

• Enhance model training and inference pipelines to optimize GPU utilization while reducing costs.

• Work collaboratively with Product, Backend, and Platform teams to establish timelines, align business objectives, and drive project execution.

• Ensure successful deployment and perform ML monitoring post-launch.

• Manage projects from ideation through to delivery, maintaining end-to-end accountability.

⛳️ Requirements

• 5–8 years of relevant experience, ideally within a fast-paced startup environment.

• Strong foundation in Deep Learning, Computer Vision, and Generative AI.

• Extensive hands-on knowledge of CNNs, GANs, VAEs, Diffusion models, Inpainting methods, image processing techniques, and architectures for text-to-image and image-to-image generation.

• Proficient programming skills in Python.

• Expertise in machine learning frameworks such as TensorFlow, PyTorch, and JAX.

• Experience in deploying Vision models on edge devices with a focus on resource optimization.

• Capable of staying up-to-date with the latest research and exploring unconventional ideas.

• Skilled in breaking down complex and abstract problems into actionable tasks.

• Self-motivated and capable of working with minimal supervision and established processes.

• Bonus: Experience in 3D computer vision, video processing, and text-to-video and image-to-video generation.

• Bonus: Knowledge of Rust.

• Bonus: Familiarity with handling highly skewed and imbalanced data.

• Bonus: Experience with cloud platforms such as AWS, GCP, Azure, as well as Docker and Kubernetes.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for professional development and training.

• Flexible working hours and remote work options.

• Collaborative and innovative team environment.