About the Company
Qodea is a global technology group focused on innovation at the intersection of technology, design, and human behaviour. The company delivers high-impact solutions for leading global clients, including Google, Snap, Diageo, PayPal, and Jaguar Land Rover, solving complex challenges with AI, data, and cutting-edge engineering.
Qodea provides an environment where professionals can work at the frontier of innovation, AI, and data engineering, with opportunities to develop advanced machine learning systems and deliver transformative results.
About the Role
The Principal Machine Learning Engineer will lead the architecture and evolution of large-scale, high-performance data and ML systems. The role focuses on data ingestion, transformation, quality checks, enrichment, and the intelligent linking of products and information.
This position includes technical leadership, mentorship, and cross-functional collaboration to ensure alignment with architectural standards, operational excellence, and the integration of modern AI/ML technologies, including semantic understanding, NLP, and large language models.
The role operates in a flexible model, with time spent on-site for collaboration sessions, customer meetings, and workshops.
Responsibilities
- Lead architecture and development of scalable data pipelines and ML systems
- Provide technical leadership and mentorship to ML Engineers, Data Scientists, and Infrastructure Engineers
- Integrate AI and ML technologies to automate data quality, link canonical products, and enhance data enrichment
- Define strategies to improve performance, reliability, and observability of data and ML services
- Design frameworks to evaluate data quality and ML model effectiveness through offline metrics and online validation
- Champion engineering best practices across teams, raising standards for code quality, data governance, and ML system design
- Influence long-term technical direction by staying ahead of trends in AI, ML, data engineering, and distributed systems
Requirements
- Extensive experience designing and leading large-scale distributed data or ML backend systems
- Hands-on experience with ETL pipeline design and optimization
- Familiarity with technologies such as Apache Beam, Pub/Sub, Redis, and large-scale data processing frameworks
- Expertise in backend development with Python and Scala; knowledge of Node.js or Golang is a plus
- Proficient with SQL and NoSQL databases, including data warehousing solutions
- Experience building robust APIs (REST, GraphQL)
- Familiarity with modern cloud environments (GCP preferred), Kubernetes, Docker, CI/CD, and observability tools
- Proven ability to lead and influence engineering direction across teams
- Strong communication skills and ability to align diverse stakeholders around data and ML strategies
Benefits
- Competitive base salary with discretionary bonus
- Employee referral scheme
- Meal vouchers
- Health care package and life insurance
- 28 days of annual leave plus floating holidays and birthday off
- Ten paid learning days per year
- Flexible working hours and work-from-anywhere policy (up to 3 weeks/year)
- Sabbatical leave after 5 years
- Industry-recognised training and certifications
- Bonusly employee recognition and rewards platform
- Clear career development opportunities and length-of-service awards
- Regular company events
- Inclusive and diverse work environment