Summary: The Senior MLOps Engineer role focuses on building robust pipelines for model deployment within a major FinTech company's digital transformation initiative. The position requires expertise in machine learning operations, including experience with tools like MLflow and containerization technologies. The contract is for 9 months and offers a competitive daily rate while being classified as outside IR35. The role is hybrid, requiring some presence in London.

Key Responsibilities:

• Build robust pipelines for model deployment that are repeatable, scalable, and observable.
• Utilize MLflow, Kubeflow, or SageMaker for machine learning operations.
• Implement CI/CD processes for machine learning using tools like GitHub Actions, Argo, or Airflow.
• Work with containerization technologies such as Docker and Kubernetes, preferably on AWS.
• Monitor, version, and ensure reproducibility of machine learning models.
• Collaborate with data scientists to productionize machine learning models.

Key Skills:

• Experience with high-scale data environments.
• Proficiency in relational and NoSQL databases.
• Ability to write production-grade code in Python, SQL, or similar languages.
• Prior experience in FinTech, SaaS, or consulting preferred.
• Familiarity with machine learning tools and frameworks.

Salary (Rate): 800

City: London

Country: United Kingdom

Working Arrangements: hybrid

IR35 Status: outside IR35

Seniority Level: Senior

Industry: IT