Senior/Lead Machine Learning Engineer

Mimica Automation; Greater London; Remote; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Stock options

Remote work options

Laptop provided

Remote setup stipend

Co-working budget

Job summary

Mimica Automation is hiring a Machine Learning Engineer/Data Scientist for its Data Intelligence team. You will transform raw data into clean, structured, anonymized data powering other teams.

You’ll own ML pipelines end to end, improving accuracy, cost-efficiency, and trust, while building evaluations, LLM judges, experiments, and production-inference improvements. Your work will be ML-heavy, with opportunities to fine-tune open-source models and develop small task-specific models, shaping

Qualifications

• Solid machine learning/data science background: understands experimental design, data splits, metrics, bias, and statistical significance.
• Hands-on experience applying LLMs in production or near-production settings, especially evaluating them with eval sets and benchmarks.
• Comfortable handling messy data and turning insights into measurable improvements.
• Strong Python and engineering skills; write clear, tested code for production use.
• Independent work on ambiguous problems, framing the question and acceptance criteria.
• Use AI coding tools effectively and defend shipped outputs.
• Clear English communication to technical and non-technical audiences.

Responsibilities

• Own, debug, and improve production pipelines for accuracy and efficiency.
• Design, build, and iterate on LLM evals and LLM-as-a-judge systems with datasets, metrics, and benchmarks.
• Run rigorous experiments on prompts, pipeline design, model choice, and inputs; translate results into recommendations.
• Drive LLM efficiency improvements across pipelines by comparing models and replacing calls with smaller, purpose-built models.
• Expand anonymization pipeline and adapt existing models.
• Collaborate with Python and quality engineers to take experiments into production and share responsibility for the code.
• Document findings in experiment reports and design docs.

Skills

Machine learning

Data science

Python

LLM evaluation

Experimental design

Production ML

English communication

Job description

What we are building

Mimica is an AI-powered process intelligence platform enabling enterprises and individuals to reclaim their most precious resource: time. We've all seen repetitive tasks and redundant processes quietly drain productivity and creativity. Not because companies don’t want to become more efficient, but because they don’t know where to start.

Mimica automatically analyzes your team’s work, then generates the AI agents to execute it. Our software turns everyday work into data-backed decisions, helping companies remove process bottlenecks, automate the right tasks, and upskill teams with precision and confidence.

We’ve raised $26 million in Series B financing and are scaling fast. Backed by investors including Khosla Ventures and Paladin Capital, our proprietary AI technology is trusted by Fortune 500 companies to accelerate transformation. Mimica is recognized as a Top 100 AI Start-up by Accel and an industry Leader by the Everest Group.
Our team

Our approach to engineering

• We prioritize customer needs first

• We work in small, project-based teams

• We have flexibility in terms of the problems we work on

• We own the full lifecycle of our projects

• We avoid silos and encourage taking up tasks in new areas

• We balance quality and velocity

• We have a shared responsibility for our production code

• We each set our own routine to maximize our productivity

Your mission

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.

You’ll own key parts of our ML pipelines end to end, making them more accurate, cost-efficient, and trustworthy. Along the way, you’ll 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.

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