Senior ML Engineer

About This Opportunity

Our talent team is representing a confidential enterprise SaaS organization seeking a Senior ML Engineer to join their predictive intelligence engineering team in Manchester. You will build backend services powering machine learning infrastructure and forecasting solutions used by enterprise customers globally.

This role reports to the Director of Engineering for Predictive Intelligence and requires close collaboration with data scientists, ML engineers, and platform partners to deliver scalable, production-ready ML systems.

Responsibilities

• Design and implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine backend
• Lead the technical implementation of MLOps capabilities, including model training pipelines, deployment workflows, and runtime infrastructure for production ML
• Partner with data scientists to productionize models and graduate experimental work into stable, observable production services
• Drive the evolution of forecasting, scoring, and data processing services with a focus on performance, scalability, and cost efficiency
• Take part in on-call rotations and own the operational health of high-availability production services, including incident response and post-incident improvements
• Lead design reviews and code reviews, raising the quality bar across the team and mentoring mid-level and junior engineers
• Identify and drive cross-cutting platform improvements that benefit multiple services and teams

What We're Looking For

Required Qualifications:

• 6+ years of professional software engineering experience building production backend services
• Strong proficiency in Python, with a track record of writing performant, well-tested production code
• Hands-on experience operating containerized services on Kubernetes in at least one major cloud (AWS, GCP, or Azure)
• Experience with data warehousing or analytics technologies such as Snowflake, Iceberg, Trino, or Postgres
• Experience designing, deploying, and operating ML models in production, including familiarity with MLOps tooling such as MLflow
• Demonstrated ability to work autonomously, take ownership of meaningful systems, and deliver against ambiguous requirements
• Track record of being on-call for production services and contributing to operational excellence
• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

Preferred Skills:

• Experience with gradient-boosted tree models, neural networks, and optimization solvers in production
• Familiarity with data orchestration tools (e.g., Prefect, Airflow, dbt) and modern data lake architectures
• Experience working closely with data scientists to operationalize research code
• Multi-cloud experience across AWS, GCP, and Azure
• Background in forecasting, demand planning, or retail/supply chain domains

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your profile and conduct an initial screening. If there's a strong match, we'll submit your candidacy to our client for consideration and guide you through their interview process. Please do not contact the client directly—all communication should go through our team to ensure the best outcome for your application.

Pay

Compensation details will be discussed during the screening process based on your experience and the client's budget.

Equal Employment Opportunity

Get A Job.ai is committed to creating an inclusive recruiting experience. We welcome candidates of all backgrounds and provide reasonable accommodation throughout our process. All qualified applicants will receive consideration without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, disability, age, or veteran status.