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Machine Learning Engineer
Исключительная вакансия в компании-единороге с мировым именем. Работа над социально значимым продуктом, использование передового стека технологий и возможность влиять на индустрию биометрии делают это предложение очень привлекательным для опытных инженеров.
Сложность вакансии
Высокая сложность обусловлена требованием более 5 лет индустриального опыта, наличием публикаций и глубокой экспертизы в узких нишах (биометрия, анти-спуфинг). Роль предполагает полный цикл разработки: от исследований до деплоя на edge-устройства.
Анализ зарплаты
Зарплата в объявлении не указана, но для Senior ML ролей в Испании рыночный диапазон составляет от 60,000 до 90,000 евро в год. В компаниях уровня 'Unicorn' (как Incode) компенсация часто выше рынка и включает опционы.
Сопроводительное письмо
I am writing to express my strong interest in the Machine Learning Engineer position at Incode. With over five years of industrial experience in deep learning and computer vision, I have a proven track record of developing and deploying production-ready models that solve complex real-world challenges. My background in facial recognition and liveness detection aligns perfectly with Incode’s mission to reinvent digital identity and trust.
In my previous roles, I have successfully architected scalable ML pipelines and optimized models for both performance and cost efficiency, including edge AI deployments. I am particularly drawn to Incode’s status as a Series B unicorn and its commitment to innovation in biometric technology. I am eager to bring my expertise in PyTorch and document processing to your specialized engineering team and contribute to the development of world-class identity solutions.
I am a builder at heart who thrives in environments that balance long-term research with rapid iteration. I look forward to the possibility of discussing how my technical skills and passion for AI can help Incode continue to lead the Gartner® Magic Quadrant™ for Identity Verification.
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Описание вакансии
POWER A WORLD OF TRUST
Incode is the leading provider of world-class identity solutions that is reinventing the way humans authenticate and verify their identities online to power a world of digital trust.
Through our revolutionary identity solutions, we are unleashing the business potential of universal industries including finance, government, retail, hospitality, gaming, and more, by reducing fraud and transforming human interactions with data, products, and services.
We’re in the process of rapidly scaling our diverse global team and we’re looking for entrepreneurial individuals and leaders who are curious, driven, and excited by ownership to join a Unicorn-status scale-up!
About Incode
Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security.
Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we’re scaling fast - and we’re looking for world-class Machine Learning Engineers to help us keep pushing the boundaries of biometric technology.
The Impact You’ll Make
As a Machine Learning Engineer at Incode, you’ll design, build, and deploy the deep learning models that power our most advanced technologies — from facial recognition and liveness detection to document processing and ID validation.
You’ll join a highly specialized engineering team working on solving complex, real-world challenges with cutting-edge ML architectures. Your work will directly influence how people verify their identity safely, seamlessly, and securely around the world.
What You’ll Own & Drive
- Innovate & Optimize - Develop and refine state-of-the-art deep learning models for computer vision applications such as facial recognition, liveness detection, and document processing and validation.
- Production-Ready Solutions - Architect and maintain scalable, efficient ML pipelines and ensure production-readiness and cost efficiency of deployed models.
- Research & Discovery - Stay at the forefront of academic and industry breakthroughs, experiment with emerging architectures and algorithms, and translate research into production-grade solutions.
- Data Mastery - Drive improvements in model performance through robust data preprocessing, cleaning, and analysis workflows.
- Collaborate & Communicate - Partner closely with research, product, and engineering teams to integrate ML solutions seamlessly into Incode’s production environment.
- Mentorship & Leadership - Provide technical guidance, share best practices, and contribute to building a culture of innovation and continuous learning.
Your Background
- 5+ years of industrial experience in Machine Learning, Deep Learning, or Computer Vision.
- Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Demonstrated experience developing, deploying, and optimizing models for both performance and cost efficiency in production environments (including edge AI).
- Specialized expertise in at least one of the following areas:
+ Facial Recognition – face recognition, age estimation, facial attributes analysis.
+ Liveness Detection – facial authentication, anti-spoofing, and anti-deepfake defense.
+ Document Processing – OCR-based extraction, document analysis, and quality assurance.
+ ID Verification – biometric data authentication and document integrity validation.
- Proven ability to design and maintain end-to-end ML pipelines.
- Track record of research contributions or publications in deep learning and computer vision.
- Excellent communication and collaboration skills across cross-functional teams.
- Passion for mentoring talent and thriving in both long-term research and rapid iteration cycles.
The Qualities That Set You Apart
- Deep curiosity and technical excellence in AI and computer vision.
- Builder mindset with a drive to deliver real-world impact through applied research.
- Strong analytical thinking balanced by practical execution.
- Collaborative spirit and ability to simplify complex ideas for diverse audiences.
- Commitment to innovation, scalability, and continuous improvement.
Why Incode?
- Mission with Meaning - Shape how billions of people prove identity - safely, simply, and ethically.
- Rocket-Ship Growth - Join at a defining moment where your work compounds in global impact.
- Elite Team & Technology - Collaborate with top-tier engineers, researchers, and scientists at the forefront of AI.
- Ownership & Autonomy - Operate with the freedom to innovate, test, and deploy your ideas end-to-end.
- Global Impact - Your models will power secure, frictionless identity verification experiences across continents.
Aspects of our Culture:
- High performance
- Freedom & responsibility
- Context, not control
- Highly aligned, loosely coupled
- Continuous Feedback
- Promotions & Development
- Learn more about Life at Incode!
Benefits & Perks:
- Flexible Working Hours & Workplace
- Open Vacation Policy
Equal Opportunities:
Incode is an equal opportunity employer, committed to creating a diverse and inclusive work environment. We take great pride in having an inclusive, diverse, and global team, and we are always looking for talented and passionate individuals from all backgrounds and walks of life. As part of our commitment to inclusion, we ensure that reasonable accommodations are available throughout the hiring process. If you require any accommodation due to a disability or specific need, please let our Talent Acquisition team know—we’ll do our best to support you.
Applicant Data Privacy:
We will only use your personal information concerning Incode’s application, recruitment, and hiring processes.
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Навыки
- Python
- PyTorch
- TensorFlow
- Computer Vision
- Deep Learning
- OCR
- Facial Recognition
- Edge AI
- Machine Learning Pipelines
Возможные вопросы на собеседовании
Проверка глубины знаний в основной специализации компании.
Какие архитектуры нейросетей вы бы использовали для реализации liveness detection и как бы вы боролись с современными deepfake-атаками?
Оценка навыков оптимизации для реальных условий.
Опишите ваш опыт оптимизации моделей для работы на edge-устройствах (мобильные телефоны). Какие техники квантования или прунинга вы применяли?
Проверка инженерных навыков и понимания MLOps.
Как вы организуете процесс мониторинга качества модели после её деплоя в продакшн, чтобы вовремя заметить data drift?
Оценка исследовательского потенциала.
Расскажите о вашей самой значимой публикации или исследовательском проекте в области Computer Vision. Какую практическую проблему он решал?
Проверка навыков работы с данными.
Как вы подходите к очистке и разметке данных для задач OCR при работе с документами низкого качества или в условиях плохой освещенности?
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