Machine Learning Engineer
The Machine Learning Engineer designs, builds, and deploys machine learning models into production systems. This role bridges data science and software engineering, ensuring models are scalable, reliable, and maintainable.
What Does a Machine Learning Engineer Do?
Deploy ML models that meet latency and accuracy requirements, build robust data pipelines, and maintain model monitoring and retraining systems.
Key Responsibilities & Tasks
ML Pipeline Engineering
- Build and maintain data pipelines for model training
- Deploy ML models to production environments
- Implement model monitoring and automated retraining
Infrastructure and Scaling
- Optimise model inference for latency and throughput
- Design scalable ML infrastructure and tooling
Do You Have the Skills for This Role?
A Machine Learning Engineer needs 4 core competencies. Here's what's required and at what level.
Must-Have Skills (Advanced)
Digital Fluency
AdvancedStaying Relevant
Problem Solving
AdvancedThinking Critically
Supporting Skills
Learning Agility
IntermediateStaying Relevant
Transdisciplinary Thinking
IntermediateThinking Critically
SkillsFuture Skill Levels
3 levelsBasic
Recognise and understand fundamental concepts. Apply skills in routine situations with guidance.
Intermediate
Apply skills in varied situations independently. Analyse problems and adapt approaches as needed.
Advanced
Lead and innovate in complex situations. Evaluate strategies, guide teams, and drive improvements.
Technical Skills & Competencies (TSC) Levels
6 levelsFollow
Carry out routine tasks under close supervision. Follow established procedures and guidelines.
Assist
Perform tasks with some independence. Assist in non-routine situations and apply established techniques.
Apply
Apply skills and knowledge independently in varied situations. Analyse problems and adapt approaches.
Analyse
Analyse complex situations and develop solutions. Guide and mentor junior colleagues.
Strategise
Set strategic direction and drive innovation. Evaluate trade-offs and make high-impact decisions.
Transform
Lead industry transformation. Establish standards, shape policy, and provide expert advisory.
Technical Skills & Competencies
A Machine Learning Engineer requires 10 technical skills at specific proficiency levels.
Data Governance
Level 6Governance and Compliance
Establish policies for data security and usage, facilitate industry consensus around data ethics, and provide expert advice on data transfer across geographies
Data Strategy
Level 6Strategy Planning and Implementation
Define a coherent data strategy and spearhead new approaches to enrich, synthesise and apply data, to maximise the value of data as a critical business asset and driver
Business Innovation
Level 5Business and Project Management
Prioritise business innovation opportunities and design digital architectures and processes to facilitate the creation of an innovative business environment
Business Needs Analysis
Level 5Business and Project Management
Lead comprehensive analysis to understand underlying drivers and present a compelling business case for proposed IT solutions
Data Design
Level 5Design and Architecture
Establish a strategy for the creation of large-scale data models and structures and spearhead the implementation of database technology, architectures, software and facilities
Data Engineering
Level 5Development and Implementation
Lead the creation of data management procedures and oversee the integration of data, ensuring optimisation of the organisation's data pipeline
Data Visualisation
Level 5Development and Implementation
Establish an effective data visualisation architecture and design intelligent and adaptable displays employing optimal delivery modes, mechanisms and timings
Emerging Technology Synthesis
Level 5Business and Project Management
Establish internal structures and processes to guide the exploration, integration and evaluation of new technologies
Performance Management
Level 5Operations and User Support
Evaluate and integrate new mechanisms and technology, and leverage analytics to optimise performance data, and determine implications of performance levels reported
Stakeholder Management
Level 5Stakeholder and Contract Management
Define a strategic stakeholder management roadmap, and lead critical discussions and negotiations, addressing escalated issues or problems encountered
European Skills Framework
ESCOSkills and knowledge areas required for this occupation based on European classification.
Essential
Optional
Career Paths from Machine Learning Engineer
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Quick Facts
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