Machine Learning Engineer, Fraud & Abuse Detection
Job description
Machine Learning Engineer on the Messaging team responsible for building and operating real-time fraud and abuse detection for a messaging platform, deciding which outbound messages reach real people.
At a glance
- Work mode
- Remote
What you'll do
- Design, train, evaluate, and operate text classifiers end-to-end: data curation, labeling, offline evaluation, deployment, and production drift monitoring.
- Run shadow-mode evaluations against labeled fraud corpora and human-reviewed legitimate controls before any model earns enforcement authority; report precision, recall, and calibration per abuse archetype.
- Build detection that holds up against adversarial content: obfuscated and confusable brand text, URL and domain evasion, and cross-account template fingerprinting.
- Serve detection models inline on the message send path under strict latency budgets, with deliberate fail-open/fail-closed behavior per dependency.
- Power human-in-the-loop fraud review: reviewer tooling, label quality, and turning fraud dispositions into replay and training signals.
- Collaborate with fraud operations, trust & safety, and cross-functional engineering teams.
- Participate in code reviews and help raise code quality and standards.
What we're looking for
- 3+ years of software development and/or machine learning experience.
- Strong proficiency in async Python webservice frameworks (e.g. FastAPI).
- Production experience building and operating text classification systems in fraud, spam, abuse, or trust & safety.
- Rigorous evaluation methodology: labeled corpora, holdout sets, precision/recall tradeoffs, and calibration.
- Experience using LLMs as classifiers or judges within a larger decision pipeline.
- Experience deploying and maintaining ML models in production.
- Excellent communication skills and the ability to work effectively with cross-functional teams.
Nice to have
- Familiarity with A2P messaging abuse: artificially inflated traffic, smishing, brand impersonation, and 10DLC / toll-free verification regimes.
- Adversarial ML experience: evasion-resilient detection, obfuscation handling, or attack-surface hardening.
- High-scale data experience with ClickHouse, PostgreSQL, Redis, and streaming systems such as Kafka.
- Experience with a cloud-native stack (e.g. Docker, Kubernetes, Prometheus).
- Experience with distributed batch scoring (e.g. Ray).
Your team
Messaging team
Team building fraud and abuse detection for the messaging platform, including phishing and smishing, brand impersonation, artificially inflated traffic (AIT), and social-engineering scams.
Apply
About Telnyx
Telnyx is an industry leader building the future of global connectivity, from a private, global, multi-cloud IP network to hyperlocal edge technology delivered through intuitive APIs. The company is financially stable and profitable, investing in pioneering technologies and fostering continuous learning and growth for its team.
Mission
Our collective vision is a world where borderless connectivity fuels limitless innovation.
Key facts
- global connectivity
- Financially stable and profitable company
- Operates a private, global, multi-cloud IP network
- Provides hyperlocal edge technology through intuitive APIs
What they value
- Continuous learning and growth