Senior ML Engineer: Productionize Forecasting & Pipelines

Anaplan; Manchester; On-site; GBP 90,000 - 125,000; Full time

Job summary

Anaplan is hiring a Machine Learning Engineer in Manchester to move forecasting, optimization and clustering models from research into production. You will partner with data scientists to ship models, while consolidating forecasting systems into a shared backend and ensuring reliability.

You’ll lead end-to-end projects, from design to deployment, focusing on scalable pipelines, observability, and model governance.

Qualifications

• Strong professional experience building, hardening and operating ML systems in production.
• High proficiency in Python with rigorous testing, code review and CI/CD practices.
• Strong SQL and hands-on experience with a cloud data warehouse and dbt or a similar framework.
• Experience building reliable, idempotent batch pipelines with an orchestrator such as Prefect, Airflow or Dagster.
• Practical experience training and deploying PyTorch and gradient-boosted models (LightGBM or XGBoost), including GPU training.
• Experience with AWS, GCP or Azure hyperscalers.
• Experience with observability for data and ML systems (metrics, logging, drift detection, alerting) and participating in on-call.
• Ability to balance research support, platform work and operational priorities.
• Experience with feature stores, data contracts or data quality frameworks (e.g., Great Expectations, dbt tests).
• Familiarity with shadow, canary and champion/challenger deployment patterns.
• Experience with multi-tenant data platforms with strict per-customer data isolation.
• Background in forecasting, supply chain, planning or analytics applications.

Responsibilities

• Partner with Data Science R&D to turn prototypes into production-grade code.
• Refactor and consolidate forecasting pipelines into a shared backend with output parity validation.
• Extend and optimize internal ML libraries for rapid model development and deployment.
• Build automated training, retraining and batch inference pipelines with backtesting and hyperparameter tuning.
• Design idempotent, retry-safe orchestration with data validation gates and clear SLOs.
• Profile and optimize memory, compute and GPU usage; tune warehouse queries and compute for cost.
• Own experiment tracking, model registry, and data/features/model versioning with promotion gates.
• Build reusable feature pipelines with correct timing and lineage.

Skills

ML systems in production

Python

SQL

PyTorch

LightGBM / XGBoost

Cloud platforms (AWS/GCP/Azure)

Observability

Data pipelines (Prefect/Airflow/Dagit)

Tools

dbt

Dagster

Airflow

Prefect

Git / CI/CD

Job description

Anaplan is hiring a Machine Learning Engineer in Manchester to move forecasting, optimization and clustering models from research into production. You will partner with data scientists to ship models, while consolidating forecasting systems into a shared backend and ensuring reliability.

You’ll lead end-to-end projects, from design to deployment, focusing on scalable pipelines, observability, and model governance.