Location : Remote / Bangalore / Chennai
Type : Full-Time
Team : Founding Tech Team
Level : Mid–Senior / Lead
Role Overview
We are looking for an experienced AI / ML Engineer (Computer Vision) to architect and build an advanced AI Scoring Engine for inputs. The role involves model selection, training, fine-tuning, evaluation, deployment (cloud / on-device) and seamless integration with mobile applications.
You will work closely with the founding team, product and mobile engineering teams.
This is a 0→1 ownership role with significant influence on the core technology direction.
Key Responsibilities
AI / ML Responsibilities
- Build and optimize the AI Scoring Engine.
- Implement computer vision models for multiple scoring dimensions, such as :
- Face quality
- Overall aesthetic score
- Subject–environment alignment
- Lighting & composition
- Expression & mood
- Uniqueness & style attributes
- Evaluate and select the best-suited models (CLIP, Vision Transformers, aesthetic models, YOLO / BlazeFace, MediaPipe, SAM, etc.).
- Fine-tune models to match defined scoring categories.
- Build weighted scoring logic and inference APIs.
- Focus on performance optimization, bias reduction and accuracy improvements.
- Deploy and scale models on AWS / GCP, leveraging GPU / TPU infrastructure.
- Stay updated with the latest developments in computer vision and deep learning.
Engineering Responsibilities
Design and implement backend architecture for real-time scoring pipelines.Build high-performance inference APIs (sub-700ms preferred).Integrate AI engine with Android / iOS mobile applications.Optimize pipelines using caching, batching, and rate limiting.Ensure strong data privacy, security and ethical AI compliance.Create internal tools, dashboards, and analytics for scoring visibility and evaluation.Requirements
Must-Have
Experience in Computer Vision / Deep LearningStrong proficiency in Python, PyTorch, TensorFlowHands-on experience with image / video classification, detection, or aesthetic modelsFamiliarity with Vision Transformers, CLIP, YOLO, MediaPipeStrong understanding of model deployment, GPU inference, ONNX, TensorRTExperience working with AWS / GCP cloud infrastructureAbility to build end-to-end AI pipelines from prototype to productionStrong analytical and problem-solving skills, especially in startup or fast-paced environmentsGood-to-Have
Experience with CoreML / TensorFlow Lite / MediaPipe for mobile inferenceExposure to building scoring, ranking, or recommendation systemsKnowledge of aesthetic / quality scoring datasetsExperience in MVP-grade rapid prototypingBackground in user-facing or high-frequency inference systemsPersonality Fit
Enjoys building systems from the ground upExecutes quickly and iterates fastComfortable with ambiguity and early-stage decision-makingOwnership-driven and self-directedPassionate about AI, computer vision and scalable engineeringFirst 90 Days Deliverables
Release Version 1 of the AI EngineBuild and deploy the backend inference APIImplement and validate the weighted scoring logicDeliver performance, accuracy and bias evaluation reportsIntegrate the AI engine into the mobile applicationSet up internal tools for monitoring, benchmarking and model evaluation