Senior MLOps Engineer
As our Senior MLOps Engineer, you'll build the infrastructure that takes our ML models from research to production — including ONNX export for client-side inference, GPU worker orchestration for OCR, and model versioning across 5 age classifiers and face recognition.
About Xident
Xident is building the future of digital identity verification. Our platform enables businesses to verify users' ages and identities in seconds, while respecting privacy through our unique "Verify Once, Access Everywhere" model.
Founded in 2023, we've already processed over 10M+ verifications processed and serve 500+ businesses. We're a remote-first company with team members across 12 countries.
Our mission is simple: To make identity verification seamless, private, and accessible for everyone. We believe privacy and convenience shouldn't be mutually exclusive, and we're proving it every day.
25+
Team members
500+ businesses
Customers
12
Countries
What You'll Do
- Design and implement ML training pipelines for age classifiers and face recognition models
- Build model versioning, ONNX export automation, and deployment to CDN for client-side inference
- Manage GPU infrastructure for OCR workers (docling VLM) and face matching (InsightFace)
- Implement A/B testing infrastructure for model evaluation in production
- Monitor model performance, detect drift across demographic groups, and automate retraining triggers
- Optimize model serving latency and cost — GPU allocation, batching, and queue management via River
What We're Looking For
- 5+ years of experience in MLOps, ML infrastructure, or ML engineering
- Strong Python skills with expertise in PyTorch and ONNX model export pipelines
- Experience with GPU infrastructure management and optimization
- Proficiency with containerized model serving and orchestration
- Understanding of data pipelines for training data management and labeling
- Experience with experiment tracking (W&B, MLflow, or similar)
Nice to Have
- Experience with ONNX Runtime deployment across web (WASM), iOS (Core ML), and Android (TFLite)
- Background in computer vision model deployment at scale
- Familiarity with River or PostgreSQL-backed job queues for ML workloads
Our Hiring Process
We respect your time and aim to complete the entire process within 2-3 weeks. Here's what to expect:
Application Review
3-5 daysOur team reviews your application within 5 business days. We look for relevant experience, passion for our mission, and alignment with our values.
Initial Call
30 minutesA 30-minute video call with our recruiting team to learn about your background, discuss the role, and answer your questions about Xident.
Technical Assessment
1-2 hoursRole-specific evaluation—this might be a coding challenge, portfolio review, case study, or technical discussion depending on the position.
Team Interviews
2-3 hoursMeet with 3-4 team members including your potential manager and cross-functional partners. We assess technical skills, collaboration, and culture fit.
Final Interview
45 minutesA conversation with a company leader to discuss your career goals, our vision, and ensure mutual fit. This is also your chance to ask strategic questions.
Offer
24-48 hoursIf it's a match, we move quickly. Expect a competitive offer within 48 hours of your final interview, with clear details on compensation and equity.
Our Values
Privacy by Design
We build systems that protect user data by default, not as an afterthought.
Ship Fast, Learn Faster
We iterate quickly, gather feedback, and improve continuously.
Ownership Mentality
Everyone owns their domain end-to-end. No finger-pointing, just solutions.
Transparent by Default
Open salaries, open metrics, open communication. Information empowers.
Join our talent pool
Apply now to be first in line when this position opens.
Apply nowOr email careers@xident.io
Benefits & Perks
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Meaningful Equity
Substantial stock options so you benefit directly from the company's success.
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Remote-First
Work from anywhere. We have team members across 12 time zones.
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Premium Healthcare
Comprehensive medical, dental, and vision coverage for you and your family.
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Learning Budget
$3,000 annual budget for courses, conferences, and professional development.
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Top Equipment
MacBook Pro, 4K monitor, ergonomic setup—whatever you need to do your best work.
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Flexible Time Off
Unlimited PTO with a 3-week minimum. We mean it—rest is productive.
Role Details
- Department
- Machine Learning
- Location
- Remote (US/EU)
- Employment Type
- Full-time
- Compensation
- $160,000 - $210,000
Other Machine Learning Positions
Senior Machine Learning Engineer
We're looking for a Senior ML Engineer to advance our age bracket classifiers and face recognition models. We run 5 binary classifiers (+12/+15/+18/+21/+25) deployed as ONNX models for client-side inference via WebAssembly — you'll improve accuracy, reduce bias, and tackle anti-spoofing.
ML Research Engineer
Join our ML team as a Research Engineer to push the boundaries of identity verification. You'll explore novel approaches to age bracket classification, document verification, and anti-spoofing — turning research ideas into production-ready ONNX models deployed on millions of devices.
Have questions about this role?
We're happy to answer any questions before you apply. Reach out to our team anytime.