AI development & evaluation
AI development & evaluation
Evaluate AI capabilities against a defined problem.
A clear scope of work
AI development & evaluation: where does it help?
Evaluate AI capabilities against a defined problem.
Start with the desired outcome. Depending on scope, the right solution may be a specialist, a project team or a defined work package.
Tasks and outcomes
Prototype models and integration
Review failure cases and human oversight
Possible outcome: Evaluated prototype with usage limits.
Select by assignment
Which roles are relevant?
15 roles with this professional connection. These describe capabilities, not currently available people.
Data scientist
Explore data and develop suitable statistical models for a specific question..
Possible outcomeAnalysis with a baseline, validation and clear interpretation of limitations.
Explore tasks & qualifications ↗Machine learning engineer
Turn a validated model into a maintainable technical workflow..
Possible outcomeVersioned model deployment with monitoring, tests and a documented fallback.
Explore tasks & qualifications ↗MLOps engineer
Connect model versions, data dependencies, deployment and monitoring in a reproducible workflow..
Possible outcomeVersioned model pipeline with checks, operational metrics and documented rollback.
Explore tasks & qualifications ↗AI engineer
Connect models, data access and application interfaces for a defined AI use case..
Possible outcomeIntegrated AI feature with evaluation cases, error handling and documented limits.
Explore tasks & qualifications ↗Generative AI consultant
Identify suitable tasks, establish data access and structure a pilot with business evaluation cases..
Possible outcomePrioritised pilot scope with evaluation criteria, human approvals and a decision brief.
Explore tasks & qualifications ↗NLP Engineer
Structure text data and analysis objectives.
Possible outcomeA tested text-processing solution with documented error categories.
Explore tasks & qualifications ↗Computer Vision Engineer
Review image data and annotations for the use case.
Possible outcomeAn evaluated vision solution with a documented operating scope.
Explore tasks & qualifications ↗Prompt Engineer
Define tasks, output formats and test examples.
Possible outcomeA versioned prompt and evaluation baseline.
Explore tasks & qualifications ↗The task in practice
How to recognise the value
Evaluate AI capabilities against a defined problem.
Starting point
Capacity is missing for this task: Explore data and develop suitable statistical models for a specific question
If this situation persists, it consumes capacity and makes decisions harder. The brief should therefore specify which workflow needs to change.
Intended value
Evaluated prototype with usage limits
Define a real acceptance case before starting. A broad capability requirement becomes a task whose result your team can assess and use.
Which capabilities matter for your assignment?
Select the professional priorities that belong in your brief.
No priorities selected yet.
Discuss the task ↗Three possible ways to scope the task
Explore data and develop suitable statistical models for a specific question.
Your team can make decisions using traceable data.
What makes the result tangible
Understand this role’s responsibilities ↗Analysis with a baseline, validation and clear interpretation of limitations.
Turn a validated model into a maintainable technical workflow.
Your team can make decisions using traceable data.
What makes the result tangible
Understand this role’s responsibilities ↗Versioned model deployment with monitoring, tests and a documented fallback.
Connect model versions, data dependencies, deployment and monitoring in a reproducible workflow.
Models can be deployed, monitored and rolled back in a traceable way.
What makes the result tangible
Understand this role’s responsibilities ↗Versioned model pipeline with checks, operational metrics and documented rollback.
Capability compass
Which combination moves your project forward?
Connect your task to relevant capabilities. A tool selection narrows the working environment; the results explain each professional connection.
Starting pointAI development & evaluationSearch the full catalogue ↗
03Reasoned role selectionTask · capabilities · outcome
The professional connection becomes clear through tasks and possible outputs.
Data scientist
Explore data and develop suitable statistical models for a specific question.
Your possible outcome
Analysis with a baseline, validation and clear interpretation of limitations.
Machine learning engineer
Turn a validated model into a maintainable technical workflow.
Your possible outcome
Versioned model deployment with monitoring, tests and a documented fallback.
MLOps engineer
Connect model versions, data dependencies, deployment and monitoring in a reproducible workflow.
Your possible outcome
Versioned model pipeline with checks, operational metrics and documented rollback.
Capability profiles for orientation. An individual’s suitability is assessed against the search brief.
Refine the selection ↗Your assignment with VB Analyst
Choose expertise. Define the engagement.
A capacity gap does not always require a permanent role. Choose a model by responsibility, duration and desired outcome.
Useful information for your enquiry
AI development & evaluation
Which errors are unacceptable, which data may be used and who evaluates responses?
Possible work objective
Evaluated prototype with usage limits
- Task, existing systems and scope
- Essential criteria, internal contact and approval
- Preferred start, duration, capacity and budget range
You can leave undecided details open. Non-confidential information is enough for initial contact.
Selected model: Project support
Discuss these requirements ↗View this model and its responsibilities ↗What happens next
From enquiry to a well-prepared start
- Define the requirement
We clarify the task, priority and outstanding requirements with you.
- Assess specialist fit
Relevant experience is assessed against the assignment. Open questions and working parameters remain visible.
- Agree selection and scope
You decide through specialist discussions. Capacity, terms and responsibilities are agreed.
- Prepare onboarding
Access, the first milestone, contacts and handover are established.
How soon can work start?
Timing depends on suitable availability, selection, agreement and access. For urgent needs, separate essential initial work from later tasks. A binding start date is confirmed for the specific assignment.
A useful starting point
Anything still unclear?
Short answers for your next step. We can work through your specific situation together.
Discuss my question ↗What belongs to this area?
Evaluated prototype with usage limits
Can I hand over one specific task?
Yes, if inputs, outputs and ownership can be defined. We agree which parts stay with your team and how acceptance is assessed.
Are the specialists available now?
The profiles describe capabilities and typical assignments. Actual people, availability, terms and engagement are assessed for your specific need.