What You'll Build :

1. Computer Vision & Image Understanding :

- Product image analysis, object detection, segmentation

- Automated background removal, image enhancement, preprocessing

- Classification, attribute extraction, and visual search systems

- Quality assessment and edge-case detection models

- Depth estimation and scene understanding from 2D images

- Real-time object detection for AR try-on

- Multi-view image analysis and camera pose estimation

2. Generative AI & Content Creation :

- Fine-tune generative models for visual and marketing asset creation

- Text-to-image and image-to-image model pipelines

- AI-generated product descriptions, tags, and metadata

- Work with diffusion models, GANs, transformers

- Texture generation, style transfer, image editing tools

- Synthetic data generation pipelines

- Experiment with the latest foundation models and diffusion techniques

3. Intelligent Automation & ML Systems :

- End-to-end automation for large-scale product catalog processing

- Recommendation and personalization models

- Automated workflows for QC, moderation, and validation

- Predictive models for engagement and conversion

- Anomaly detection and platform monitoring

- Continuous learning and self-improving systems

4. Production ML Infrastructure :

- Deploy/optimize ML models on AWS

- Build scalable inference pipelines (low latency, high throughput)

- Implement model versioning, A/B testing, CI/CD for ML

- Data pipelines for annotation, augmentation, and quality control

- Optimize models for speed, efficiency, and cost

- Monitoring systems for drift, quality, and performance

- APIs/microservices for ML model serving

5. Research & Innovation :

- Explore latest AI/ML trends and cutting-edge models

- Prototype quickly with state-of-the-art models (GPT-4V, Diffusion, SAM, etc.)

- Integrate open-source tools into our production stack

- Run feasibility experiments and contribute to model architecture decisions

- Document learnings and share insights internally

What We're Looking For :

Must-Haves :

- 5-8+ years experience in AI/ML, strong computer vision background

- Deep expertise in PyTorch/TensorFlow

- Production ML deployment experience

- Strong understanding of CNNs, transformers, detection, segmentation

- Hands-on experience with diffusion models or GANs

- Strong Python skills and ML system design

- Cloud experience (AWS/GCP/Azure)

- Proven record of shipping ML products

- Passion for experimenting with new AI models

Highly Desirable :

- Experience in e-commerce/retail imaging or content pipelines

- Background in automation and intelligent workflow systems

- Recommendation/personalization experience

- Familiarity with multimodal models (vision + language)

- Experience with neural rendering or 3D generation

- Open-source contributions or research publications

- Real-time inference optimization

- Strong MLOps understanding

- Ability to build end-to-end ML-driven features

Problems You'll Solve :

- Automating large-scale product image processing

- Generating high-quality product visuals at scale

- Extracting structured attributes from image datasets

- Reducing manual processes with intelligent automation

- Optimizing inference speed and cost

- Personalizing user experiences with ML

- Monitoring and evaluating models reliably in production