At Aftershoot, we’re building a global community of photographers who spend less time behind their screens and more time behind the lens. Every feature we create, every update we ship, is designed to make post-processing easier, faster, and smarter for photographers around the world.

From culling to editing to retouching. Our AI tools do all the heavy lifting, so photographers can focus on what they do best: capturing moments, telling stories, and creating magic.

We’re a fast-growing, passionate team backed over 100K+ active users globally. Double digit ARR in less than 4 years, amazing investors and team who truly believe in our mission.

Our mission is clear: Become the default companion for every photographer in the world.

If you care deeply about building meaningful products, working with curious and driven teammates, and being part of a team that genuinely loves what they do, we’d love to meet you.

Let’s create the future of AI in photography, together.

🚀Your Mission

We are looking for an experienced Machine Learning Engineer with deep expertise in Computer Vision and Generative AI to join our team in New Delhi, India, 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 full lifecycle of vision and generative AI systems, from problem definition and research through deployment and monitoring.

• Design, train, evaluate, and deploy state-of-the-art deep learning models for image and video understanding, enhancement, generation, and editing.

• Build scalable training and inference pipelines optimized for quality, latency, and cost.

• Work on challenging problems involving image quality assessment, image restoration, segmentation, aesthetic scoring, image enhancement, object understanding, and generative image manipulation.

• Experiment with and productionize modern architectures across computer vision and generative AI, including diffusion-based approaches and multimodal systems.

• Collaborate closely with Product, Platform, and Engineering teams to translate ambiguous problems into measurable outcomes.

💪 What We're Looking For

• Solid foundation in Deep Learning, Computer Vision, and Generative AI, with 5-8 years of experience building and shipping ML systems.

• Strong understanding of modern vision architectures, image processing, image enhancement, segmentation, diffusion models, and generative image editing.

• Hands-on experience with PyTorch and building scalable, production-grade ML systems.

• Experience in one or more of the following areas: computational photography, image restoration, image quality assessment, video understanding, 3D vision, or multimodal AI.

• Strong understanding of model optimization, deployment, and inference efficiency.

• Ability to stay current with cutting-edge research and translate new ideas into production-ready solutions.

• Passion for solving complex problems, strong ownership, and the ability to thrive in a fast-moving environment.

⭐ Bonus Points

• Experience with Gaussian Splatting, NeRFs, video generation, or advanced generative AI systems.

• Familiarity with computational photography techniques such as HDR, denoising, deblurring, or image enhancement.

• Publications, research contributions, or experience reproducing state-of-the-art papers.

• Knowledge of Rust for high-performance inference pipelines.

• Experience working with highly skewed datasets.

• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

What happens after you apply?

Step 1: If your profile aligns with our vibe and requirements for the role, our people team will reach out to you for a brief phone call.
Step 2: If everything aligns, your next chat will be with one of your future team members to better understand the role and your experience.
Step 3: You will then be given a task - this helps us evaluate your thought process and help you showcase your expertise.
Step 4: If everything goes well, you will meet the leadership for a quick bar-raiser round.
Step 5: If you do manage to clear all rounds, this is the point we make an offer, shake hands, and welcome you to the team.

You will work with:

Team: Nikhil, Abinash, Abhishek, Karan