Machine Learning Engineer
2 days ago
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
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