Senior/Lead Machine Learning Engineer
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Job Description
Machine Learning Engineer building LLM-heavy data intelligence pipelines for Mimica’s AI process intelligence platform. Improving evaluation, anonymization, efficiency, and production ML systems.
Responsibilities:
- Transform raw recorded data into clean, structured, anonymized data for downstream teams
- Own key parts of ML pipelines end to end
- Improve pipeline accuracy, cost efficiency, and trustworthiness
- Build evaluations and LLM judges
- Run experiments and turn promising results into validated production improvements
- Evaluate and fine-tune open-source models
- Build smaller task-specific models
- Own, debug, and improve production pipelines
- Design and iterate on LLM evaluations and LLM-as-a-judge systems, including datasets, metrics, and benchmarks
- Experiment with prompts, pipeline design, model choice, and inputs such as OCR text versus image plus OCR
- Drive LLM efficiency improvements by comparing models, restructuring steps, and replacing LLM calls with smaller purpose-built models
- Expand the anonymization pipeline by evaluating and adapting existing models
- Work with Python and quality engineers to productionize experiments
- Share responsibility for shipped production code
- Document findings in experiment reports and design documents
Requirements:
- Solid machine learning/data science background, including experimental design, data splits, metrics, bias, and statistical significance
- Hands-on experience applying LLMs in production or near-production settings, especially evaluating them
- Experience building eval sets, LLM judges, benchmarks, and iterating on prompts and pipelines
- Comfortable exploring, troubleshooting, and transforming messy data into measurable improvements
- Strong Python and good engineering skills
- Clear, readable, tested code suitable for production
- Ability to work independently on ambiguous problems
- Effective use of AI coding tools with accountability for shipped output
- Clear spoken and written English
- Ability to explain technical trade-offs to technical and non-technical audiences
- Experience with classical ML or deep learning model development (nice to have)
- Experience with image/OCR pipelines or face-related anonymization (nice to have)
- Experience shipping end-to-end ML features in a startup or scale-up environment (nice to have)
Benefits:
- Generous compensation + stock options
- Distributed work: Work from anywhere - fully remote, in our hubs, or a mix
- Company-issued laptop
- Remote setup stipend
- Co-working budget
- Flexible schedules and location
- Ample paid time off, in addition to local public holidays
- Enhanced parental leave
- Health & retirement benefits
- Annual learning & development budget
- Annual workaways
- Regular virtual & in-person socials
- Opportunity to contribute to groundbreaking projects that shape the future of work
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