Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Leading the design, build, deployment, and monitoring of production machine learning models on a Lakehouse platform with an accent on MLOps best practices and model governance. Focus on translating business problems into effective ML solutions and diagnosing/resolving production ML issues at scale.

Location: Manchester, United Kingdom (Hybrid working)

Salary: Up to £90,000 per annum

Company

hirify.global specializes in enabling enterprise machine learning delivery at scale within modern data environments, utilizing platforms like Databricks.

What you will do

• Lead the design, build, deployment, and monitoring of production machine learning models using Databricks.
• Define and embed MLOps best practices, including model versioning, governance, and monitoring strategies.
• Develop automated model validation tests covering unit, integration, regression, and bias checks.
• Translate business problems into effective ML solutions, managing ethical, privacy, and data governance.
• Establish model performance KPIs, reliability measures, and production monitoring frameworks.
• Diagnose and resolve production ML issues, leading root cause analysis and system improvements.

Requirements

• Proven experience delivering machine learning models into production environments.
• Strong Python, SQL, and PySpark skills for scalable, production-grade development.
• Hands-on experience establishing MLOps processes within Databricks.
• Experience building data pipelines for structured and unstructured data.
• Degree in a STEM subject or equivalent experience with strong statistical understanding.
• Strong stakeholder communication skills, able to explain technical concepts to non-technical audiences.

Culture & Benefits

• Hybrid working model.
• Discretionary bonus and non-contributory pension.
• Private medical and dental cover (including family options).
• Life insurance and wellbeing-focused benefits.
• Supportive, collaborative data and technology environment.
• Opportunity to work on modern ML, MLOps, and Lakehouse technologies at scale.