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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading and developing ML engineering teams while maintaining hands-on experience in building and deploying ML systems. Proficient in mentoring, performance management, and implementing engineering standards across projects.
Highest-signal resume keywords
Line Management ExperienceHands-On ML EngineeringStrong Python SkillsExperience with LLMsKnowledge of CI/CD
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
ML System DevelopmentModel EvaluationPerformance ArchitectureCode ReviewReproducibilityAutomated EvaluationSoftware Engineering PracticesTraining ML ModelsDeploying ML SystemsBuilding Reproducible Pipelines
Soft Skills
Strong Communication SkillsMentoring SkillsInfluencing SkillsDifficult Conversation Skills
Tools & Technologies
DatabricksAWSGCPGitHubDockerKubernetesMLflowJiraNvidia JetsonRaspberry Pi
Certifications & Qualifications
MSc or Equivalent ExperienceEligibility for Developed Vetting (DV) Clearance
Industry Keywords
ML Engineering StandardsAgile DeliveryEmbedded AcceleratorsLarge-Scale TrainingAgentic Systems
Tech Stack
Tools & technologiesAWSDockerGoogle Cloud PlatformKubernetesPython
About the role
Key responsibilities & impact- Lead and develop a team of ML engineers
- Line manage engineers, set objectives, support progression and be accountable for team performance
- Work with technical and delivery leads to define and uphold ML engineering standards
- Develop and improve team ways of working, processes and systems
- Raise team skills through mentoring, reviews and knowledge sharing
- Resource engineers across concurrent projects and customers
- Lead hiring for the growing ML team
- Spend approximately 70% of time on hands-on ML engineering and 30% leading the team
- Work closely with technical and delivery leads and report to the Head of ML
- Deploy and assure ML systems for demanding operational environments
Requirements
What you’ll need- Experience line managing and developing engineers
- Experience hiring during a period of growth
- Experience balancing people across several concurrent projects or customers
- Current, hands-on experience building, training, evaluating or deploying ML systems for real-world use
- Strong Python and good software engineering habits
- Understanding of ML and software engineering practices including performance, architecture, testing, code review, reproducibility and evaluation
- Strong communication, mentoring, influencing and difficult-conversation skills
- MSc or equivalent experience required
- Experience with LLMs and agentic systems, edge deployment or large-scale training (desirable)
- Experience with reproducible pipelines, model versioning, CI/CD, observability and automated evaluation (desirable)
- Knowledge of Agile delivery and engineering career frameworks (beneficial)
- Knowledge of Databricks, AWS, GCP, GitHub, Docker/Kubernetes, MLflow and Jira (beneficial)
- Knowledge of Nvidia Jetson, Raspberry Pi or other embedded accelerators (beneficial)
- Must be eligible for Developed Vetting (DV) clearance
Benefits
Comp & perks- Flexible working and hybrid-working model
- Average 3 days in the office each week (dependent on the role)
- Flexibility and part-time working requirements welcomed
- Workplace adjustments available
- Disability Confident Committed company
- Inclusive and diverse working environment