Join Fingerprint as a Senior Machine Learning Engineer

Fingerprint empowers developers to stop online fraud at the source by transforming radical new ideas in the fraud detection space into reality. Our developer-focused products serve clients ranging from solo developers to publicly traded companies. As a globally dispersed, 100% remote company with a strong open-source focus, our flagship open-source project, FingerprintJS, boasts 20K stars on GitHub.

About Us

We have raised $77M in funding, backed by reputable investors such as Craft Ventures (Tesla, Facebook, Airbnb), Nexus Venture Partners (Postman, Apollo.io, MinIO, Druva), and Uncorrelated Ventures (Redis, Rollbar, Gradle).

Position: Senior Machine Learning Engineer

We are seeking a highly skilled and innovative Machine Learning Engineer to join our team. In this role, you will work on groundbreaking projects that involve applying data science and machine learning techniques to process raw, unlabeled data and extract valuable insights about browsers and devices. Your contributions will be pivotal in enhancing our smart signals product and fostering a data-driven culture within our team.

Types of Projects and Impact

• Collaborate with the Smart Signals Product team to enhance the quality of existing smart signals, including Browser bot and VM detection, VPN detection, Incognito detection, and Tampering/Spoofing detection using data science and machine learning algorithms.
• Develop new smart signals by creating real-time ML-based services that analyze large volumes of raw data to gain insights about devices.
• Foster a data-driven culture within the Fingerprint team by sharing tools and knowledge on effective data science approaches.

Position Overview

Responsible for the end-to-end software engineering of products that leverage data science and machine learning techniques to process raw, unlabeled data and extract insights about browsers and devices.

Required Skills

• Proficient in English for clear verbal communication within an international remote team.
• BS/MS in Computer Science or related field, or equivalent work experience.
• 3+ years of demonstrated experience in Machine Learning Engineering, Data Science, and Backend Development.

Machine Learning and Data Science Skills

• Strong foundation in Machine Learning and Mathematical Statistics for performing offline and online experiments.
• Proficient in Supervised Learning for column-based data.
• Experience with Semi- and Unsupervised Learning for problems lacking reference labeling.
• Skilled in Exploratory Data Analysis to investigate ad-hoc questions and explain anomalous data.
• Creative in collecting datasets and estimating ML algorithm performance without reference labeling.
• Excellent SQL and coding skills.
• T-shaped backend engineering skills for independent end-to-end ML service development.
• Expertise in ML-related engineering challenges, such as real-time model inference, creating services from models, and training pipeline automation.
• Broad backend engineering expertise to develop MVP real-time web services from ML models.
• Proficiency with general software engineering tools: git, IDE, shell, CI/CD.

Nice to Have

• Experience with GoLang for backend development.
• Practical experience with analytical storages like Clickhouse, Snowflake, BigQuery, Redshift, Databricks.
• Familiarity with engineering practices for maintaining numerous data transformations, such as data transformation frameworks (dbt, materialized views, data pipeline workflow tools).
• Experience with data visualization tools (Apache Superset, Tableau, Metabase, Looker).
• Proficiency in the Python data analytics stack: Numpy, pandas, Jupyter, etc.

Main Technologies

• ML stack is open-ended, with CatBoost used in production.
• GoLand for backend development.
• AWS.
• Databases: AWS DynamoDB, Redis, ElasticSearch.
• Data analytics/processing: Clickhouse, dbt, Apache Superset (Preset), Prefect.

Offers vary depending on relevant experience, education, certifications/licenses, skills, training, and market conditions. Due to regulatory and security reasons,