AI/ML Engineer (Synthetic Data)

Remote from: Czechia
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Full Time,
Job posted: 2 Jun 2026
Apply before: 2 Jul 2026
Views / Applies: 16 / 5

About company

About Cint

The World's Largest Global Research Marketplace connecting your research questions to the right people.

Market Research
1998

Actively Hiring

AI Summary

Cint is hiring AI/ML Engineers for a new Synthetic Data Platform team, focusing on building production models for survey augmentation, audience profiling, and agentic insights. The role involves designing, training, and deploying models using LLMs and traditional ML, working closely with data science and product teams. Candidates should have strong Python skills, experience with ML and LLMs, and familiarity with cloud technologies. The position offers high autonomy and the chance to work on cutting-edge AI tooling.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires advanced skills in AI/ML, including LLM fine-tuning and production deployment, which is challenging, but the company provides strong support and modern tooling, balancing difficulty.

Salary Analysis

AI Insight The offered salary is not specified. Based on the US market for AI/ML Engineers with synthetic data focus, the estimated median is $175,000. This is competitive for senior roles with deep technical expertise.

Key Skills

Python Machine Learning LLM Fine-Tuning Synthetic Data AWS SQL Deep Learning Statistics FastAPI Kubernetes

Cover Letter Sample

Dear Hiring Manager,

I am excited to apply for the AI/ML Engineer (Synthetic Data) position at Cint. With a strong background in machine learning and deep learning, particularly in building production models for data augmentation and predictive profiling, I am eager to contribute to your greenfield project. My experience includes fine-tuning large language models and deploying scalable ML pipelines on cloud platforms like AWS.

I am particularly drawn to the high autonomy and AI-native engineering culture at Cint, and I thrive in fast-paced, collaborative environments. I look forward to the opportunity to discuss how my skills align with your team's goals.

Sincerely,
[Your Name]

Possible Interview Questions

Can you describe your experience with fine-tuning large language models? What techniques have you used (e.g., LoRA, distillation)?

I have fine-tuned LLMs using LoRA for efficient adaptation to domain-specific tasks. For example, I fine-tuned a GPT-2 model on customer support data to improve response accuracy, achieving a 15% increase in relevant answers. I also used distillation to create smaller, faster models for deployment.

How would you approach building a model to predict respondent characteristics from limited signals?

I would start by exploring the data to understand signal patterns and missingness. Then, I'd use feature engineering to extract meaningful features, and try ensemble methods like gradient boosting or a neural network with embeddings. Cross-validation and ablation studies would help select the best model.

Explain a time you owned a project end-to-end from experiment to production.

At my previous job, I led the development of a real-time recommendation system. I designed the model architecture, trained it on historical data, deployed it using Docker and Kubernetes on AWS, and set up monitoring for performance. The system handled 10k requests per second with 95% accuracy.

How do you ensure the integrity of statistical testing in your experiments?

I use A/B testing with proper randomization and sample size calculation. I also apply techniques like bootstrapping for confidence intervals and control for multiple comparisons using Bonferroni correction. Regular peer reviews of experimental design help catch errors.

Describe your experience with cloud technologies like AWS and Databricks.

I have extensive experience with AWS, including EC2, S3, Lambda, and SageMaker for model training and deployment. I also used Databricks for large-scale data processing and collaborative notebook development, leveraging Spark for ETL pipelines.

Company Description

Who We Are

Cint is a pioneer in research technology (ResTech). Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more. The Cint platform is built on a programmatic marketplace, which is the world’s largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.

We are feeding the world’s curiosity!

Job Description

The Role

We’re hiring several AI/ML Engineers for the Synthetic Data Platform team. This is a greenfield project, an exciting new market and a key part of Cint’s 2026 product strategy. You will build models with a deep understanding of how respondents answer surveys. These will underpin new products which will be best-in-class for the industry, including:

Survey Augmentation: filling missing responses to surveys
Audience Profiling: predicting respondent characteristics from signals we have
Agentic Insights: answering a client’s research questions using insights from existing data

The Team

You’ll join our AI/ML team in Prague, working alongside engineers on augmentation and profile modelling, the data science team, and a product manager who owns the Synthetic Data roadmap. Customer pilots are already running, and feedback from those pilots shapes the roadmap.

Qualifications

What You’ll Do:

Build production augmentation and profile models: Design, train, evaluate, and deploy models against real survey data, owning the full path from experiment to production.
Innovate on solutions: We aim to build the best simulation of survey responses in the industry. You’ll design the experiments, baselines, and models to get us there.
Use the latest technology: Build on the best open-weights LLMs with fine-tuning, build new ones from scratch with custom architectures or use third party models through an API; whatever gets us the best result.
Partner with Data Science: Work with the data science team to ensure integrity of our statistical testing and experiment framework.
Leverage AI tooling: Use Claude Code and agentic programming tools where appropriate.

What You Bring:

Excellent programming skills and be proficient in Python. Knowledge of Java is a plus.
Knowledge of traditional machine learning tools and techniques (support vector machines, gradient boosting)
An understanding of LLMs and their architecture, ideally with experience in fine-tuning, e.g. LoRA, distillation
Proficient in SQL, knowledge of Databricks is a plus
Familiarity with cloud technologies, e.g. AWS
Outstanding problem-solving and analytical skills
Knowledge of maths, probability, statistics and algorithms
You like to push the limits of your knowledge every day
You own your conclusions and are comfortable presenting them and shaping outcomes

Additional Information

Working at Cint

Prague-First, Europe-Friendly: Our preferred base is Prague, alongside our existing AI/ML team. Remote work from Spain or the UK is also possible, as these are the markets where we have entities.
AI-Native Engineering: We’re rolling out Claude Code and modern agentic tooling across engineering. You’ll use it daily, not as a novelty, but as a force multiplier for the complex problems that matter.
High Autonomy: We trust our engineers to make sound decisions and own their work end-to-end.
Global Impact: Your work powers a marketplace used by millions of people worldwide.
Modern Tech Stack: We usually build our services using the latest Python tooling and FastAPI, dockerize them and deploy with CI/CD to K8s in AWS. We keep the code on GitHub.
Company Hardware: Cint provides a laptop (Win/Linux/Mac) and accessories, and a height adjustable desk at the Pankrác office
Benefits Include:
- Office in Prague (Pankrác) but full remote possible
- 25 days of vacation, unlimited sick days
- Pension fund contribution, Edenred meal vouchers

Our Values

Collaboration is our superpower

We uncover rich perspectives across the world
Success happens together
We deliver across borders.

Innovation is in our blood

We’re pioneers in our industry
Our curiosity is insatiable
We bring the best ideas to life.

We do what we say

We’re accountable for our work and actions
Excellence comes as standard
We’re open, honest and kind, always.

We are caring

We learn from each other’s experiences
Stop and listen; every opinion matters
We embrace diversity, equity and inclusion.

More About Cint

We’re proud to be recognised in Newsweek’s 2025 Global Top 100 Most Loved Workplaces®, reflecting our commitment to a culture of trust, respect, and employee growth.

In June 2021, Cint acquired Berlin-based GapFish – the world’s largest ISO certified online panel community in the DACH region – and in January 2022, completed the acquisition of US-based Lucid – a programmatic research technology platform that provides access to first-party survey data in over 110 countries.

Cint Group AB (publ), listed on Nasdaq Stockholm, this growth has made Cint a strong global platform with teams across its many global offices, including Stockholm, London, New York, New Orleans, Singapore, Tokyo and Sydney. (www.cint.com)

Additionally, in a world of AI, we want our candidates to understand our approach to the use of AI during the interview and hiring process, so we’d appreciate you reading our AI usage guide.

Apply now >