Recruitment Room Team
MLOps Engineer (Python & SQL) (CPT)
Job Description
ENVIRONMENT:
DELIVER Data-Science value – discover, build, train and deploy ML solutions that drive measurable value and impact as the next MLOps Engineer wanted by a reputable Independent Asset Management Firm. You will design the MLOps infrastructure that lets models move from notebook to production safely, quickly and cost-effectively. Providing thought leadership & radical innovation – you will also challenge conventional approaches, champion out of the box thinking and push the team to explore bold, future focused ideas that keep the firm ahead of the curve. The successful incumbent will require 5+ years delivering commercially driven ML projects from concept to production, expert Python and solid SQL; modern development practices (Git, tests, code review, CI/CD) with hands-on experience designing and operating MLOps pipelines: containerisation (Docker/K8s), automated deployment, drift monitoring & retraining triggers.
DUTIES:
MLOps & Engineering –
- Architect and automate end-to-end ML pipelines (CI/CD, testing, monitoring, retraining) in Azure, DataBricks or Mosaic.
- Build feature stores, model registries and scalable batch/streaming data pipelines (BigQuery/Spark/Kafka/dbt).
Model Development –
- Lead full-lifecycle ML projects – ideation, experimentation, production and post-deployment monitoring.
- Apply regression, classification, clustering, time-series forecasting and recommender systems to real-world retail problems.
Innovation –
- Track emerging research (LLMs, ensemble methods, vector search) and run PoCs to keep the stack ahead of the curve.
- Demonstrate thought leadership by challenging the status quo, encouraging radical, out-of-the-box thinking and inspiring the team to step outside their comfort zone.
- Drive a culture of continuous experimentation and learning to unlock innovative solutions.
Stakeholder Engagement –
- Translate fuzzy business questions into data-science roadmaps, articulate complex concepts to non-technical partners.
- Coach and mentor Analysts/Engineers, promoting best-practice coding and MLOps approaches.
Governance & Efficiency –
- Embed security, cost-optimisation and observability into everything you build.
- Define operating procedures, documentation and design patterns that future-proof the platform.
REQUIREMENTS:
- 5+ Years delivering commercially driven ML projects from concept to production.
- Expert Python and solid SQL; modern development practices (Git, tests, code review, CI/CD).
- Hands-on design and operation of MLOps pipelines: containerisation (Docker/K8s), automated deployment, drift monitoring, retraining triggers.
- Strong grasp of data-warehousing and modelling concepts; comfortable collaborating with Data Engineering on ETL and architecture.
- Familiarity with Deep-Learning frameworks (TensorFlow/PyTorch) and vector databases.
ATTRIBUTES:
- Passion for upskilling others and shaping Data-Science culture.
- Excellent communication and collaboration skills to work effectively in cross-functional teams.
- The ability to build and maintain meaningful relationships.
- A strong belief in doing the right thing.
- Driven by results.
- Ability to recognise and embrace change.
- Intellectual curiosity.
- Able to analyse, interpret and assimilate information.
