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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 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 5-8 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). 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
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
