About Incode

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!

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 data professionals passionate about investigating data quality problems and building the systems that keep world-class ML models reliable.

The Impact You'll Make

As a Data Analyst on the ID Document Intelligence team, you'll investigate data quality issues, perform root cause analysis, and build the pipelines and automated checks that keep Incode's machine learning ecosystem reliable. You'll ensure that data flows efficiently and accurately through every stage of model training, labeling, and performance tracking.

Your work will be essential to maintaining the scalability, quality, and precision of Incode's document intelligence systems used by millions worldwide.

What You'll Own & Drive

• Root Cause Investigation — Independently investigate data quality issues end-to-end. When a model metric drops or data looks wrong, you own the investigation: forming hypotheses, querying across data sources, and delivering a clear, evidence-backed answer.
• Automated Data Pipelines — Design, build, and maintain pipelines for collection, labeling, validation, and metric computation that support ML training and evaluation.
• Data & Labeling Quality Standards — Establish and monitor consistency checks, accuracy audits, and root-cause analysis when issues impact model outcomes.
• Model Evaluation Metrics — Define, implement, and automate evaluation metrics and reporting that reflect real-world product use cases and business goals.
• Performance Tracking Systems — Build scalable dashboards and monitoring to enable fast, data-driven decisions across teams.
• Workflow Orchestration — Develop and operate reliable orchestration (Airflow, Prefect, or similar) to schedule, observe, and troubleshoot end-to-end pipelines.
• Clean, Maintainable Code — Write SQL and Python to efficiently investigate problems — querying databases, calling internal APIs, and processing data across multiple sources.
• Cross-Functional Partnership — Partner closely with ML engineers, analysts, and product stakeholders to prioritize work by impact, unblock execution, and continuously improve internal tooling for analysis and evaluation.

The Qualities That Set You Apart

• Investigative mindset — You don't stop at the symptom. You chase data anomalies until you find the root cause, and you bring receipts.
• Statistical intuition — You can tell the difference between a meaningful metric shift and noise, and you know how to prove it.
• Builder's bias — You'd rather automate a check than run it manually for the third time.
• Proactive ownership — You spot problems before anyone flags them, and you drive them to resolution without waiting for permission.
• Clear communicator — You translate messy data into crisp answers that ML engineers, PMs, and leadership can act on.

Your Background

• 3+ years of experience as a Data Analyst or in a similar data infrastructure role.
• Strong SQL and Python skills for data investigation and root cause analysis.
• Hands-on experience with AWS Redshift or a similar columnar/cloud database (BigQuery, Snowflake, etc.).
• Solid statistical foundation — you can reason about rates, distributions, significance, and sampling bias.
• Hands-on experience with workflow orchestration tools (Airflow, Prefect, Dagster, etc.).
• Proven experience in data quality management, data preparation, or ML data pipelines.
• A proactive mindset toward identifying problems.
• Strong collaboration and problem-solving skills.
• Background in mathematics, physics, or engineering.

Preferred Experience

• Familiarity with big data technologies or data infrastructure optimization.
• Experience with labeling workflows or ML data preparation pipelines.
• Exposure to AWS or other cloud-based data solutions.
• Interest in machine learning operations (MLOps) and scalable ML systems.

Why Incode?

• Mission with Meaning — Build systems that enable ethical, seamless identity verification for millions.
• Rocket-Ship Growth — Join a company scaling globally with AI at its core.
• Elite Team & Technology — Collaborate with top engineers and data scientists redefining document intelligence.
• Ownership & Autonomy — Operate with end-to-end responsibility for impactful data pipelines.
• Global Impact — Your work will power real-world AI experiences trusted by major enterprises.

Power a world of trust.

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?

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?