Lead Data Scientist

Lead Data Scientist, Computer Vision (Contract)

Location: Remote

Employment Type: Contract (6 months)

Company Description:

Our client is an innovative fashion technology startup redefining the way people discover fashion online. Their mission is to create a smarter and more empowering fashion discovery experience that helps users find clothing that truly fits their style, size, and budget.

By combining cutting-edge artificial intelligence with a user-first design philosophy, they are building a platform that transforms visual search into an intuitive and powerful discovery tool. The company is currently at an exciting stage of growth and is building a product that aims to reshape how millions of users interact with fashion online.

With a passionate and mission-driven team, the company is focused on creating technology that empowers users, improves confidence, and delivers highly personalized fashion recommendations.

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 infrastructure with Terraform and treating infrastructure as code.
• Strong understanding of MLOps best practices, including CI/CD pipelines, automated deployments, and monitoring.
• Excellent software engineering skills with clean, maintainable, and scalable code practices.
• Strong communication skills and the ability to collaborate with cross-functional teams.
• Ability to thrive in fast-moving startup environments where priorities may evolve quickly.

Nice-to-haves

• Experience deploying large-scale AI/ML systems supporting high user volumes.
• Familiarity with ensemble or multi-model inference strategies.
• Experience in fashion, e-commerce, search, recommendation systems, or consumer products.
• Exposure to agentic AI systems or multimodal retrieval-augmented generation (RAG).
• Experience designing machine learning systems with limited data or constrained resources.
• Prior work in early-stage startups or high-growth product environments.

Work Schedule

• Monday to Friday - 09:00 – 17:30 GMT
• Indian Standard Time (IST): 2:30 PM – 11:00 PM

Pay & Benefits - What we offer

• 2,35,000 INR - 2,65,000 INR Monthly.
• Remote-first collaboration across distributed teams.