If you enjoy taking ML beyond experiments, this is your chance to 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 (eg. experiment reports, design docs)

What we’re looking for

Primarily, we’re looking for an individual with an experiment- and data-driven researcher mindset with good coding habits. This includes:

• 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

Bonus / Nice to have

• 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.

Location

This is a fully remote position. To make sure we work well together, we’re only considering candidates based in the UK or Europe, in time zones compatible with London (typically UTC-1 to UTC+3).

Hiring Process

• Stage 1. Talent Partner (30-45 min)
• Stage 2. Take-home challenge (flexible) + Technical Discussion with the team (1h)
• Stage 3. Technical design exercise and situational questions in session w/ two ML Engineers (1h)
• Stage 4. Behavioral interview w/ Engineering leadership (1h)
• Offer
• Identity Verification

What we offer

💰 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

Note: Some benefits may vary depending on location and role

<code>⚠️ Mimica will only contact candidates from an @mimica.ai email address. We do not request banking or sensitive personal information during the recruiting process.</code>