Machine Learning Engineer
Core
Design, train, and evaluate machine learning models for production use cases in the recruitment technology space, owning the full ML lifecycle from problem definition to monitoring.
Role type
Mid-level Machine Learning Engineer
Builds
Production ML models and end-to-end ML pipelines for recruitment technology products
Domain
Recruitment technology / AI
Deliverable
production ML models
Required skills
Python, TensorFlow/PyTorch/scikit-learn, end-to-end ML pipelines, model selection and evaluation, feature engineering, MLOps tools, cloud platforms (AWS SageMaker/GCP Vertex AI), Kubernetes, Docker, A/B testing frameworks
Preferred skills
Startup environment experience, rapid iteration cycles
Technologies
TensorFlow, PyTorch, scikit-learn, AWS SageMaker, GCP Vertex AI, Kubernetes, Docker
Responsibilities
Design and implement end-to-end ML pipelines covering data preprocessing, model serving, and monitoring; Debug and optimize model performance in production based on real-world feedback; Collaborate with product and engineering to translate business requirements into ML solutions; Write clean, maintainable code and contribute to ML infrastructure and tooling
Seniority
Mid-level, hands-on IC
