Animall - Computer Vision Engineer - Machine Learning

Role Overview :

We are looking for a hands-on Computer Vision / Applied ML Engineer to own and scale the ML systems powering our B2B and Classifieds modules.

This role focuses on image intelligence, moderation, quality scoring, duplicate detection, and data-driven automation not core generative AI or chatbot systems.

You will work closely with product and backend teams to design, deploy, and optimize production-grade ML systems that directly impact marketplace quality and trust.

Key Responsibilities :

1. Computer Vision & Image Intelligence :

- Build and optimize image processing pipelines using OpenCV

- Develop duplicate/near-duplicate image detection systems

- Improve listing quality via automated image scoring and validation

- Optimize model inference for low-latency production use

2. ML Model Development & Deployment :

- Train, fine-tune, and deploy deep learning models (PyTorch preferred)

- Work with detection architectures (YOLO, Faster R-CNN, etc.)

- Implement evaluation pipelines and model monitoring

- Improve precision/recall for moderation and classification systems

3. Data & Infrastructure :

- Design clean ML pipelines integrated with backend systems

- Work with SQL databases (PostgreSQL/MySQL)

- Build automated workflows (batch + scheduled jobs)

- Containerize and deploy models using Docker

- Work with AWS services (S3, ECR, compute services)

4. Quality & Moderation Systems :

- Build ML-based listing moderation systems

- Detect fraud/spam listings using image + metadata signals

- Improve marketplace trust and content quality through ML

Required Skills :

Must-Have :

- Strong expertise in Computer Vision & Image Processing

- Hands-on experience with OpenCV

- Deep Learning experience using PyTorch or TensorFlow

- Experience with Object Detection models

- Strong understanding of model training, evaluation, and optimization

- Experience deploying ML models in production

- SQL database proficiency

- Docker-based deployment experience

- AWS experience (S3, ECR, compute services)

Good to Have :

- Feature matching & similarity search

- Basic MLOps practices

- Workflow orchestration tools (Airflow)

- Experience working in marketplace / classifieds / content platforms

Experience :

- 2 - 5 years of relevant experience in Computer Vision / Applied ML

- Proven track record of shipping ML models into production

Ideal Candidate :

- Strong ownership mindset

- Can independently design train deploy monitor ML systems

- Practical problem solver (not research-only)

- Comfortable working in fast-paced product environments