Machine Learning Engineer

What You’ll Do

• Research & Experimentation: Explore and implement state-of-the-art ML techniques in computer vision and generative AI to improve our culling, editing, and face-matching models.
• Model Development: Train, fine-tune, and deploy models for blur detection, blink detection, duplicate detection, aesthetics scoring, and personalized editing.
• Benchmarking: Analyze current FilterPixel ML models against competitor offerings and identify opportunities for improvement in speed, accuracy, and reliability.
• Data Pipelines: Work with large-scale photo datasets to prepare, label, augment, and optimize data for training.
• Production Readiness: Build models that are not only accurate but also efficient and production-friendly (low latency, lightweight).
• Collaboration: Work closely with the product and engineering teams to convert research into real features photographers love.

What We’re Looking For

• Experience: 1–3 years of experience in machine learning research projects (internships, academic research, or applied industry work all count).
• Strong Fundamentals: Solid understanding of deep learning, computer vision, and ML research techniques.
• Hands-On Skills: Proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX).
• Project Work: Prior research projects, papers, or contributions to ML/AI projects (academic or industry).
• Problem-Solving: Ability to take ambiguous problems, run experiments, and arrive at practical solutions.
• Nice-to-Have: Experience with CLIP, diffusion models, photo aesthetics models, or GANs.

Job Types: Full-time, Permanent

Pay: Up to ₹600,000.00 per year

Application Question(s):

• How many years of experience do you have in machine learning research projects?(internships, academic research, or applied industry work all counts).

Work Location: In person