At SentiLink, we stop identity fraud at scale. Our products protect banks, fintechs, marketplaces, and leading financial institutions from synthetic identity fraud, identity theft, and emerging threats — analyzing millions of applications while keeping real users moving fast.
We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.
SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.
We’re a small, high-impact team solving one of the most interesting and adversarial problems in fintech: how do you build systems that reliably determine whether a real human is on the other side of a financial transaction?
We’re hiring across Engineering (Full-stack and Infra) and Data Science / ML roles. Hiring at Manager/Director level as well as mid-level/Senior levels.
We’re language-agnostic and hire for fundamentals. Across the team you’ll see: • Python, Go, Rust, Scala • PostgreSQL, Snowflake • Kafka, Redis • Terraform, Kubernetes • ML: XGBoost, PyTorch, Feature stores, real-time scoring pipelines
If you love solving complex distributed systems challenges, building customer-facing ML products, or working on detection systems that must be both high-precision and low-latency, you’ll fit right in.
Roles are here: https://jobs.ashbyhq.com/sentilink?utm_source=hacker_news
If you have questions, feel free to reach out directly at liz.woodfield at sentilink dot com.
Feel free to get in touch directly with the CTO: https://www.linkedin.com/in/maxbarkhausen/ | max@tulana.io
Starbridge is building an AI platform that turns large-scale public and enterprise data into reliable sales insights. We are early, moving fast, and building from zero to one, so this role will have huge ownership and product impact.
Backend Engineer: (looking for Kotlin/Java/Scala experience). You'll work across the backend: building enterprise integrations, large-scale scraping and parsing pipelines, and systems that let users apply LLMs to millions of documents to generate insights at scale.
Product Engineer: (React/Typescript) who would work closely with product and design to build user-facing parts of the platform. You will craft performant, stable frontends that explain technical concepts to non-technical users and help us iterate fast based on customer feedback.
AI Engineer: Applied AI plus strong software engineering. You will build, evaluate, and deploy LLM-driven features like deep document analysis and interactive chat, working with models from OpenAI, Anthropic, and Gemini. Expect hands-on Python, ML system design, experimentation, and production reliability. Bonus for RAG depth and frameworks like LangChain, LlamaIndex, or Hugging Face.
We're looking to build our in-person team in NYC but also open to remote!
Apply: https://starbridge.ai/careers and mention HackerNews or email melissa@starbridge.ai with your resume.
- Radar is the geo-location dev tool
- Doing 1B+ API calls per day
- Our main languages are Rust and TypeScript, we also use mobile and offline pipeline languages (Python, Scala, and Terraform).
- We're based in NYC with our HQ in Union Square and remote friendly (US)
Interesting things we're working on:
- HorizonDB, our Geospatial database written in Rust
- Precise indoor location more accurate than iOS and Android leveraging Ultra-Wideband, other mobile sensors and ML.
- Extracting raw map data from satellite maps and the web leveraging ML and AI
- Anomaly detection to identify spoofed locations
- Mobile infrastructure that automatically configures itself optimizing battery-life and location accuracy for different use-cases over time
- Multi-Region AWS K8s deployment, 99.99%+ availability
- Frontend tools to visualize and debug location data at scale
Check out our jobs page here: https://radar.com/jobs#jobs If you have any questions, feel free to reply here or you can e-mail me at tim@radar.com