VAYUZ Technologies - Machine Learning Engineer - Python

Responsibilities :

- Optimize model inference for real-time recommendations.

- Containerize ML models using Docker/Kubernetes.

- Build REST APIs for the recommendation engine.

- Monitor model drift and retraining pipelines.

- Productionize machine learning models for fashion and fit recommendations, ensuring low-latency inference and high scalability.

- Deploy recommendation models using REST/gRPC APIs for real-time and batch inference.

- Optimize models for performance, memory usage, and response time in high-traffic environments

- Implement hybrid recommendation pipelines combining collaborative filtering, content-based filtering, and contextual signals (season, region, trends).

- Integrate stylist-curated rules and human-in-the-loop feedback into ML-driven recommendations.

- Support personalization based on body type, height, skin tone, ethnicity, and user style profiles.

- Build and maintain end-to-end MLOps pipelines including training, validation, deployment, monitoring, and retraining.

- Containerize ML services using Docker and orchestrate deployments with Kubernetes.

- Implement CI/CD pipelines for ML models and inference services.

- Monitor model performance, drift, bias, and recommendation quality in production.

- Design automated retraining workflows based on data freshness and performance metrics.

- Collaborate with Data Scientists to tune ranking, diversity, and relevance metrics.

Qualifications :

- Solid understanding of MLOps practices, including MLflow, model registries, and feature stores.

- TensorFlow Serving, FastAPI / REST API.

- MLOps and CI/CD pipelines.

- Experience with scalable deployment architectures.

- Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

- Hands-on experience with recommendation systems (collaborative filtering, embeddings, ranking models).

- Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).

- Knowledge of data storage systems (SQL/NoSQL) and caching mechanisms (Redis, Memcached).