Senior Anti-Fraud Engineer (Full-Time)

Toloka; Portugal; Remote; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Base salary + bonus + ESOP

Remote or hybrid from Portugal

Home office allowance

Paid time off and benefits by location

Career development support

Job summary

Toloka AI is seeking a data/ML professional to help detect and stop fraud on the Toloka platform. You will work at the intersection of analytics and applied ML, digging into data, identifying patterns, formulating hypotheses, and turning them into defenses—models and automated pipelines running in production.

You will design metrics and dashboards to track protection performance, build scalable data pipelines, and think like an attacker to ensure defenses hold up from day one.

Qualifications

• Work at the intersection of analytics and applied ML, turning data into defenses.
• Build metrics, dashboards, and charts to visualize protection performance.
• Design and test hypotheses using data to guide production solutions.

Responsibilities

• Explore data to detect fraud patterns, anomalies, and insights.
• Design metrics and dashboards to show protection effectiveness.
• Generate hypotheses from data and rigorously test them.
• Turn validated hypotheses into production rules, models, and LLM-based approaches.
• Build and maintain data pipelines (SQL, Python, Airflow) for defenses.
• Anticipate bypass methods and design robust defenses from day one.
• Own end-to-end delivery from insight to deployed solution and monitoring.
• Help shape anti-fraud rules and policy definitions.

Skills

SQL

Python

Machine learning

Airflow

ClickHouse

LLMs

Data analysis

Product sense

Tools

Databricks

Job description

At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains - from doctors and lawyers to physicists and engineers - and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft, and Shopify.

Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA, UK, the Netherlands, Serbia, and more.

What this role is about (& Project details)

Our team builds the systems that detect and stop fraud on the Toloka platform. Fraud here is a moving target: bad actors adapt quickly, test our defenses, and increasingly use automation and LLMs to get around them. The same technologies give us a lot of room for new ideas, and we’re looking for someone to help us stay ahead.

You’ll sit at the intersection of analytics and applied ML. You’ll dig into data, find patterns nobody has noticed yet, turn them into hypotheses, and then into working defenses: models and automated pipelines running in production.

What you'll actually do

• Explore data to find new fraud patterns, anomalies, and insights, and to understand how fraudsters operate.
• Design metrics that show how our protection works, and build dashboards and charts that make them visible.
• Generate hypotheses from data and test them rigorously.
• Turn validated hypotheses into production solutions: rules and heuristics, ML models, and LLM-based approaches.
• Build and maintain data pipelines (SQL, Python, Airflow) that keep our defenses running and up to date.
• Think like an attacker. Anticipate how a new defense could be bypassed, and design it to hold up from day one.
• Own your area end to end: from the first insight to a deployed solution and its ongoing monitoring.
• Help shape anti-fraud rules and policies, including how we define and classify fraud.

What we evaluate

• Analytical thinking. You can frame a vague problem, choose the right metrics, and draw sound conclusions from messy data.
• Hypothesis-driven approach. You generate ideas from data and know how to test them properly.
• SQL. You write confident, efficient queries on large datasets (ClickHouse experience is a plus).
• Python & ML. You can build features, train and evaluate models, and ship them to production. Practical experience with LLMs is a plus.
• Data pipelines. You have working experience with Airflow or similar orchestration tools.
• Product sense. You understand the trade-offs of protection: false positives, impact on honest users, and cost.

Nice to have, none required

• Hands-on experience in anti-fraud, trust & safety, risk, or abuse prevention (a big plus).
• Experience with anomaly detection, graph analysis, or behavioral modeling.
• Experience applying LLMs to analytical or classification tasks.
• Experience with Databricks.
• Experience with crowdsourcing or data annotation platforms.

What we can offer

• You will be part of an international, dynamic environment that drives innovation and sets new standards in the AI and technology sector.
• Competitive compensation package including base salary, bonus, and ESOP.
• Flexibility: We offer remote or hybrid employment from Portugal, with a flexible work schedule that you can design together with your manager to best suit your needs.
• Paid PTO and benefits will vary depending on location.
• IT setup and home office allowances.
• Personal and career development: we support employee’s ambition for professional development and encourage them to implement their ideas in their projects;

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