onsite
Senior Machine Learning Engineer - PitchBook Data
ML Engineer
Lead the design, development, and deployment of advanced machine learning models and pipelines, leveraging Python, deep‑learning frameworks, and cloud services to deliver data‑driven insights for a fast‑growing financial data platform.
About the role
Key Responsibilities
- Architect, build, and productionize scalable machine learning models for large‑scale financial datasets.
- Collaborate with data engineers and product teams to design end‑to‑end data pipelines and feature stores.
- Implement and optimize deep‑learning solutions using TensorFlow or PyTorch, including NLP and time‑series models.
- Deploy models on AWS (SageMaker, EC2, Lambda) and monitor performance, reliability, and cost.
- Conduct experiments, perform rigorous A/B testing, and translate results into actionable product improvements.
Requirements
- 5+ years of professional experience building production ML systems, preferably in fintech or data‑intensive domains.
- Strong proficiency in Python and deep‑learning libraries (TensorFlow, PyTorch) with solid software engineering practices.
- Hands‑on experience with AWS services for ML (SageMaker, ECS, S3) and containerization (Docker, Kubernetes).
- Expertise in SQL and data‑engineering concepts, including ETL pipelines and feature engineering.
- Demonstrated ability to solve complex problems, communicate insights clearly, and mentor junior engineers.
Skills
pythontensorflowpytorchawssqlmachine learningnlp