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Machine Learning Engineering Manager - Compare The Market
ML Engineer
Lead a high‑performing ML team to build scalable AI solutions for financial decision‑making, leveraging Python, AWS, and MLOps practices to deliver rapid, data‑driven outcomes.
About the role
Key Responsibilities
- Lead and mentor a cross‑functional ML engineering team, setting technical direction and ensuring delivery of production‑ready models.
- Design and implement end‑to‑end ML pipelines on AWS, integrating data ingestion, feature engineering, training, and deployment.
- Collaborate with data scientists, product managers, and infrastructure teams to translate business problems into scalable AI solutions.
- Champion best practices in model monitoring, versioning, and continuous improvement using MLOps tools.
- Drive innovation in deep learning and advanced analytics to enhance financial decision‑making products.
Requirements
- 5+ years of experience in ML engineering, with a proven track record of leading teams.
- Strong proficiency in Python, AWS services (SageMaker, Lambda, S3), and containerization (Docker, Kubernetes).
- Hands‑on experience with MLOps frameworks (MLflow, Kubeflow) and model monitoring.
- Excellent communication skills and a collaborative mindset.
- Passion for building customer‑centric AI solutions in a fast‑paced environment.
Skills
machine learningpythonawsdeep learningmlops