The Role
We're hiring a Senior AI/ML Engineer with deep expertise in computer vision, generative AI, and production-grade ML systems. This is a 100% hands-on individual contributor role where you will build the AI engines behind the platform automated image processing, generative content creation, intelligent workflows, and large-scale ML pipelines.
You will work across computer vision, generative models, automation, and ML infrastructure to deliver production-ready AI systems.
What You'll Build
- Computer Vision & Image Understanding
- Product image analysis, object detection, and segmentation
- Automated background removal, image enhancement, and 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
- Generative AI & Content Creation
- Fine-tune generative models for visual and marketing asset creation
- Build text-to-image and image-to-image model pipelines
- Generate AI-based product descriptions, tags, and metadata
- Work with diffusion models, GANs, and transformer architectures
- Develop texture generation, style transfer, and image editing tools
- Build synthetic data generation pipelines
- Experiment with the latest foundation models and diffusion techniques
- Intelligent Automation & ML Systems
- Build end-to-end automation pipelines for large-scale product catalog processing
- Develop recommendation and personalization models
- Implement automated workflows for quality control, moderation, and validation
- Build predictive models for engagement and conversion
- Implement anomaly detection and platform monitoring
- Design continuous learning and self-improving systems
- Production ML Infrastructure
- Deploy and optimize ML models on AWS
- Build scalable inference pipelines with low latency and high throughput
- Implement model versioning, A/B testing, and CI/CD for ML
- Create data pipelines for annotation, augmentation, and quality control
- Optimize models for speed, efficiency, and cost
- Build monitoring systems for model drift, quality, and performance
- Develop APIs and microservices for ML model serving
- Research & Innovation
- Explore the latest AI/ML trends and emerging models
- Prototype rapidly using state-of-the-art models such as GPT-4V, Diffusion, and SAM
- Integrate open-source tools into the production stack
- Run feasibility experiments and influence model architecture decisions
- Document learnings and share insights internally
Technical Stack
AI / ML Frameworks
- PyTorch, TensorFlow, Hugging Face
- OpenCV, YOLO, Detectron2
- Stable Diffusion, ControlNet, Diffusers
- scikit-learn, XGBoost
Deployment & Infrastructure
- FastAPI, ONNX, TorchScript, TensorRT
- AWS services including SageMaker, Lambda, EC2, and S3
- Docker and Kubernetes
- PostgreSQL, Redis, MongoDB, Pinecone
Languages & APIs
- Python (primary)
- JavaScript / Node.js (working knowledge)
- REST, GraphQL, WebSocket APIs
Nice to Have (3D / Graphics)
- Understanding of rendering pipelines
- Familiarity with glTF or USDZ formats
- Experience with Three.js or Unity / Unreal
What We're Looking For
Must-Haves
- 58+ years of experience in AI/ML with a strong computer vision background
- Deep expertise in PyTorch or TensorFlow
- Experience deploying production ML systems
- Strong understanding of CNNs, transformers, detection, and segmentation models
- Hands-on experience with diffusion models or GANs
- Strong Python skills and ML system design experience
- Cloud experience with AWS, GCP, or Azure
- Proven track record of shipping ML-powered products
- Passion for experimenting with emerging AI models
Highly Desirable
- Experience in e-commerce, retail imaging, or content pipelines
- Background in automation and intelligent workflow systems
- Experience with recommendation or personalization systems
- Familiarity with multimodal models combining vision and language
- Experience with neural rendering or 3D generation
- Open-source contributions or research publications
- Experience optimizing real-time inference
- Strong understanding of MLOps practices
- Ability to build end-to-end ML-driven product 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 through intelligent automation
- Optimizing inference speed and infrastructure cost
- Personalizing user experiences using ML
- Monitoring and evaluating ML models reliably in production
Why Ctruh
- Work across computer vision, generative AI, automation, and NLP
- Use cutting-edge models and a modern AI stack
- High-impact role influencing millions of shoppers
- Culture focused on experimentation and rapid iteration
- Strong learning environment with research exposure
- Small engineering team with high ownership and visibility
- Supported by Microsoft, NVIDIA, Google, and AWS
Location & Culture
- Location: Bengaluru
- Schedule: 6 days a week (5 days in office, Saturdays work-from-home)
- Culture: Fast-paced, experimentation-driven, and execution-focused
- Team: Highly skilled engineers focused on impact
- Resources: GPU compute, modern tooling, and research access
The Ideal Candidate
You are an AI builder who enjoys experimenting and shipping real systems. You have worked with diffusion models, vision transformers, SAM, GPT-4 Vision, and similar technologies. You are comfortable switching between computer vision, generative models, automation systems, and production ML pipelines.
You care about impact building models that improve real product experiences. You move quickly, choose the right tools for the problem, prototype rapidly, and optimize systems for production reliability.
You thrive in environments where you can innovate continuously and own AI systems end-to-end.
Skills:- Computer Vision, Generative AI, PyTorch, TensorFlow and Huggingface
