[Hiring] Senior/Lead Machine Learning Engineer @Mimica

Role Description

You’ll join us as a Machine Learning Engineer/ Data Scientist for Mimica’s Data Intelligence team, whose goal is to transform raw recorded data into clean, structured, anonymized data that powers the work of other teams.

• Own key parts of our ML pipelines end to end, making them more accurate, cost-efficient, and trustworthy.
• Build evaluations and LLM judges, run experiments, and transform promising results into validated production improvements.
• Your work will be applied and LLM-heavy, with opportunities to evaluate and fine-tune open-source models and build smaller, task-specific models.
• Shape the systems at the heart of Mimica’s products and see your work deliver value to real users at scale.

Part of your day-to-day:

• Own, debug, and improve production pipelines for accuracy and efficiency.
• Design, build, and iterate on LLM evals and LLM-as-a-judge systems, including the datasets, metrics, and benchmarks to monitor quality.
• Run rigorous experiments on prompts, pipeline design, model choice, and inputs (e.g., OCR text vs. image + OCR), and turn the results into clear recommendations.
• Drive LLM efficiency improvements across our pipelines by comparing models, restructuring steps, and replacing LLM calls with smaller, purpose-built models where it makes sense.
• Expand our anonymization pipeline, including evaluating and adapting existing models.
• Work with Python and quality engineers to take experiments into production, and share responsibility for the code you ship.
• Document findings in writing (e.g., experiment reports, design docs).

Qualifications

• Solid machine learning/data science background: you understand experimental design, data splits, metrics, bias, and statistical significance, and you know when a result is real.
• Hands-on experience applying LLMs in production or near-production settings, especially evaluating them: building eval sets, LLM judges and benchmarks, and iterating on prompts and pipelines against them.
• Comfortable getting deep into messy data: exploring it, troubleshooting issues, and transforming insights into measurable improvements.
• Strong Python and good engineering skills: you write clear, readable, tested code that others can take to production, even if you’re not the one owning the infrastructure.
• Able to work independently on ambiguous problems: framing the question, choosing the approach, and deciding on the acceptance criteria to ship.
• Use AI coding tools effectively and stay accountable for the output: understand, explain, and defend everything you ship.
• Communicate clearly in spoken and written English, including explaining technical trade-offs to both technical and non-technical audiences.

Requirements

• Experience with classical ML or deep learning model development.
• Experience with image/OCR pipelines or face-related anonymization.
• Experience shipping end-to-end ML features in a startup or scale-up environment.

Benefits

• Generous compensation + stock options - aligned with our internal framework, market data, and individual skills.
• Distributed work: Work from anywhere - fully remote, in our hubs, or a mix.
• Company-issued laptop, remote setup stipend, and 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 and regular virtual & in-person socials.
• Opportunity to contribute to groundbreaking projects that shape the future of work.