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Machine Learning Engineer - X4 Engineering
ML Engineer
Build and scale production‑grade machine learning systems for a high‑frequency trading platform, integrating data pipelines, model serving, and cloud infrastructure using Python, TensorFlow/PyTorch, and AWS services.
About the role
Key Responsibilities
- Design, develop, and maintain end‑to‑end machine learning pipelines that ingest, process, and serve data for trading, analytics, and research workloads.
- Implement robust model training, validation, and deployment workflows using Python, TensorFlow or PyTorch, and container orchestration (Docker, Kubernetes).
- Collaborate with traders, quantitative researchers, and platform engineers to translate research prototypes into production‑ready services.
- Optimize data storage, retrieval, and feature engineering pipelines on AWS (S3, Redshift, SageMaker) to ensure low‑latency, high‑throughput performance.
- Monitor, troubleshoot, and continuously improve the reliability, scalability, and security of ML infrastructure.
Requirements
- 5+ years of software engineering experience with a strong focus on production machine‑learning systems.
- Proficiency in Python and deep‑learning frameworks such as TensorFlow or PyTorch.
- Hands‑on experience with cloud platforms (AWS) and container orchestration (Docker, Kubernetes).
- Solid understanding of data engineering concepts, including ETL pipelines, feature stores, and real‑time streaming.
- Ability to work cross‑functionally with domain experts, translating research ideas into scalable code.
Skills
pythontensorflowpytorchawsdockerkubernetes