remote
Staff AI/ML Engineer - Burq
ML Engineer
Lead the design and deployment of large‑scale AI/ML solutions, building robust pipelines and models that power next‑generation logistics automation using Python, cloud services, and container orchestration.
About the role
Key Responsibilities
- Architect, develop, and productionize end‑to‑end machine learning pipelines for real‑time logistics optimization.
- Design and train deep learning models using frameworks such as TensorFlow or PyTorch, ensuring high accuracy and scalability.
- Collaborate with data engineering and product teams to define data requirements, feature engineering strategies, and model evaluation metrics.
- Deploy and manage AI services on cloud platforms (AWS) using container orchestration tools like Kubernetes.
- Mentor junior engineers, establish best practices, and drive continuous improvement of the ML development lifecycle.
Requirements
- 5+ years of hands‑on experience building and scaling machine learning systems in production.
- Strong proficiency in Python and deep learning frameworks (TensorFlow, PyTorch).
- Extensive experience with cloud services (AWS) and containerization (Docker, Kubernetes).
- Solid understanding of data pipelines, feature engineering, and model monitoring.
- Proven ability to lead technical initiatives and mentor engineering teams.
Skills
pythontensorflowpytorchawskubernetesmachine learningdeep learning