Lead Data Scientist (Computer Vision)

Lead Data Scientist – Computer Vision (Contract)

India (Remote) | Contract | 6-month contract | Fashion Tech / AI

Placed by Hotsourced – connecting top global talent with world-class companies

We’re partnering with an innovative fashion technology startup that is transforming how people discover and shop for clothing online. By combining advanced artificial intelligence with a user-first approach, the company is building a powerful visual search platform that helps users find styles tailored to their preferences, size, and budget.

This is a unique opportunity to join at a pivotal stage of growth and take ownership of the core intelligence layer powering the product. You’ll work on cutting-edge AI systems that directly impact real users, shaping the future of fashion discovery through scalable, high-performance machine learning solutions.

Company Overview / About Us

Our client is a fast-growing AI-driven fashion platform focused on redefining online discovery through visual intelligence. Their mission is to make fashion search intuitive, personalized, and empowering by leveraging computer vision and multimodal AI technologies.

With a strong product vision and a highly technical team, they are building solutions that bridge the gap between inspiration and purchase—delivering meaningful, real-time recommendations at scale.

Job Summary / Role Overview

As Lead Data Scientist (Computer Vision), you will lead the design, development, and deployment of advanced machine learning systems that power a next-generation visual search platform.

This is a hands-on leadership role where you will own the full ML lifecycle—from experimentation and model design to production deployment and optimisation. You’ll work closely with product and engineering teams to translate user needs into intelligent, scalable solutions.

Job Summary

We are looking for a Lead Data Scientist specializing in Computer Vision to play a pivotal role in designing and building the intelligence engine behind a cutting-edge visual search platform.

This is a hands-on technical leadership role where you will architect, develop, and deploy state-of-the-art computer vision and multimodal AI systems. From research and experimentation to production deployment, you will take ownership of the full machine learning lifecycle and ensure that models translate directly into high-impact product experiences.

The ideal candidate thrives on solving complex technical challenges, enjoys building scalable ML systems, and is excited by the opportunity to shape a product used by real customers in real time.

Responsibilities

• Own the computer vision pipeline end-to-end, including image ingestion, preprocessing, embeddings, object detection, similarity search, and large-scale retrieval.
• Design and implement transformer-based vision models for fashion understanding, including classification, detection, and feature extraction.
• Build multimodal search systems that combine image and text signals to deliver highly relevant search results.
• Architect and deploy real-time inference infrastructure using AWS services such as SageMaker, Lambda, and S3.
• Develop and optimize vector database pipelines (e.g., Pinecone, Weaviate, Qdrant) to support large-scale image retrieval and nearest-neighbor search.
• Manage ML infrastructure using Infrastructure as Code (Terraform) to ensure scalable and reproducible deployments.
• Conduct structured experiments to evaluate model performance and continuously improve system accuracy.
• Translate user needs into machine learning solutions in collaboration with product and engineering teams.
• Monitor and optimize production systems to ensure low-latency, high-reliability performance at scale.

Requirements

We believe the right candidate will have most of the following:

• 6+ years of hands-on machine learning experience, with deep expertise in computer vision.
• Proven experience deploying computer vision models into production systems at scale.
• Strong expertise with transformer-based vision architectures such as ViT, CLIP, or similar models.
• Hands-on experience building multimodal search or retrieval systems combining text and visual signals.
• Advanced knowledge of embedding-based search, re-ranking strategies, and relevance evaluation.
• Experience implementing and scaling vector databases such as Pinecone, Weaviate, or Qdrant.
• Strong experience with AWS SageMaker, including model training, deployment, and endpoint management.
• Familiarity with AWS services such as S3 and Lambda for supporting ML infrastructure.
• Expertise in PyTorch or TensorFlow and modern object detection frameworks.
• Experience managing inf