Senior/Lead Machine Learning Engineer

MimicaAI process intelligence

Only considering candidates based in the UK or Europe, UTC-1 to UTC+3Full-TimeLead

Salary not disclosed

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Job Details

Languages: Communicate clearly in spoken and written English
Required Skills: PythonMachine LearningData scienceDeep LearningPrompt Engineering

Have a solid machine learning or data science background.
Understand experimental design, data splits, metrics, bias, and statistical significance.
Have hands-on experience applying LLMs in production or near-production settings, especially evaluating them.
Have experience building evaluation sets, LLM judges, and benchmarks and iterating on prompts and pipelines against them.
Be comfortable exploring messy data, troubleshooting issues, and turning insights into measurable improvements.
Have strong Python skills and write clear, readable, tested code that can be taken into production.
Be able to work independently on ambiguous problems, frame questions, choose approaches, and define acceptance criteria.
Use AI coding tools effectively and understand, explain, and defend shipped work.
Communicate clearly in spoken and written English with technical and non-technical audiences.
Experience with classical machine learning or deep learning model development is a plus.
Experience with image/OCR pipelines or face-related anonymization is a plus.
Experience shipping end-to-end ML features in a startup or scale-up environment is a plus.

Own, debug, and improve production pipelines for accuracy and efficiency.
Design and iterate on LLM evaluations and LLM-as-a-judge systems, including datasets, metrics, and benchmarks.
Run experiments on prompts, pipeline design, model choice, and inputs, and turn results into recommendations.
Improve LLM efficiency by comparing models, restructuring pipeline steps, and replacing LLM calls with smaller task-specific models where appropriate.
Expand the anonymization pipeline by evaluating and adapting existing models.
Work with Python and quality engineers to take experiments into production.
Document findings in experiment reports and design documents.

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