ML Engineer - Verifications

Parity

ABOUT US Parity is one of the world’s most experienced companies building the core infrastructure behind blockchain — the system that allows information and value to be shared securely without needing an intermediary. We’re laying the foundation for a better web which respects the freedom and data of individuals, and empowers developers to build better, more trustworthy online services. Our remote-first, global team develop open-source software that anyone can use or improve. This includes Polkadot, Polkadot SDK, and Kusama — key parts of the Web3 tech stack, the next generation of the internet. Our mission is to make Polkadot the most active and innovative community in blockchain, powering a new era of connected and decentralised applications. ABOUT THE TEAM Parity’s Security Engineering team is at the forefront of protecting the Polkadot ecosystem by designing and implementing secure software, auditing code for vulnerabilities, and building cutting-edge ML tools to automate security analysis. We work closely with development teams to embed security best practices across our open-source stack, ensuring that our blockchain infrastructure is robust, resilient, and secure by design. ABOUT THE ROLE As a security-focused software engineer, you will go beyond traditional application security - you’ll audit and ideally write secure Rust code where needed, conduct deep manual and automated code audits, and leverage machine learning to enhance security across our ecosystem. This is an opportunity to shape the security landscape of the next generation of decentralized applications and protocols. * Assist in developing Secure Software – Write and optimise Rust code to build security-critical components and tools. * Code Auditing & Vulnerability Analysis – Perform deep manual and automated code reviews to identify and mitigate security vulnerabilities. * ML-Powered Security – Design and implement machine learning models for automated security analysis, anomaly detection, and threat mitigation. * Bug Bounty & Vulnerability Management – Manage bug bounty submissions, triage security reports, and collaborate with ethical hackers to resolve issues. * Secure Development Best Practices – Work with engineering teams to integrate security best practices into the software development lifecycle. * Threat Modeling & Risk Assessment – Identify and assess security risks in our blockchain infrastructure, smart contracts, and core software. * Stay Cutting-Edge – Research and implement the latest advancements in secure coding, ML-driven security, and blockchain security. WHAT WE'RE LOOKING FOR * Experience with secure coding practices and memory safety concepts. * Background in code auditing, vulnerability analysis, or exploit development. * Experience triaging and resolving bug bounty reports. * Knowledge of machine learning techniques applied to security (e.g., anomaly detection, fuzzing, automated threat detection). * Familiarity with cryptographic principles, blockchain security, or decentralized systems. * Strong problem-solving skills and an offensive security mindset. If you're excited about writing secure software, auditing code, and pioneering ML-driven security solutions for Web3, we’d love to hear from you! ABOUT WORKING WITH US Joining Parity means joining team mates who are genuinely excited about the impact their projects are having, and the opportunity to grow alongside some of the brightest minds in the Web3 space! You’ll work remotely and flexibly, while still getting to meet your team mates throughout the year at team and company-wide retreats. Upon receiving an offer, all candidates undergo a background check through Zinc, our trusted third-party provider. Team members will be taken on as a contractor via our UK entity. View our Applicant Notice to see how we use your data. Parity is an Equal Opportunity Employer. We welcome diversity in our global team and care about everyone in our collective feeling included and welcome. Is this position not quite your match? Browse our other open roles.

Quadrivia

ABOUT US Quadrivia is the health technology company behind Q, a comprehensive, controllable, and customizable assistant AI built by clinicians, for clinicians. Addressing the urgent shortage of healthcare professionals, Q provides real-time, personal, and reliable support for clinical tasks across the care continuum. Designed for providers, payers, and pharmaceutical companies, Q is easy to customize and integrates seamlessly into workflows, delivering precise assistance across the care spectrum. THE ROLE You'll build and run Cortex, the core AI architecture behind Qu, and the services that sit on top of it: automated AI audits, patient simulators, retrieval (RAG), and the escalation agents that take over in red-guardrail situations. This is a backend role first. The job is to make our AI systems reliable, fast, and observable in production, not to invent new ML. You own the software underneath the agents. We're a small team that ships real systems. We've built our entire AI-driven evaluation system, our voice orchestrator, and a multi-hierarchical RAG platform from scratch. WHAT YOU'LL DO * Design and maintain robust, modular backend systems using clean architectural (SOLID) principles to ensure long-term maintainability, scalability and flexibility as the agentic stack evolves. * Own Cortex end-to-end: architecture, API design, service boundaries, reliability targets, and proactively managing failure modes. * Build the platform services around it. The automated audit and eval pipeline, patient simulators for testing agents at scale, and the retrieval layer. * Write fast, well-tested Python services with FastAPI, asyncio, and pydantic, and get the queues, caching, and data stores right. * Wire up the multi-agent orchestration: routing between agents, shared state, and clean tool interfaces. * Engineer the RAG pipeline for high-signal retrieval (chunking, hybrid search, re-ranking, caching) and prove the grounding holds. * Make the whole thing observable: structured logs, OTEL tracing across the agent graph, cost, latency and token visibility, dashboards, and CI gates that catch regressions before they ship. MINIMUM QUALIFICATIONS * Your core is backend and software engineering. You write clean, maintainable services and you care how they behave in production. * Deep understanding of architectural design patterns (e.g., Clean/Hexagonal Architecture, Domain-Driven Design, SOLID, event-driven) to manage complex system boundaries. * At least 2 years, demonstrable, building or scaling user-facing AI software that real users touched. We'll want to see it. * Expert Python, with strong FastAPI, asyncio, pydantic, and production observability. * Comfortable with agent patterns and eval-driven development. * You've worked at a startup before and know what wearing several hats actually costs. NICE TO HAVE * Real-time and voice: WebRTC, LiveKit, SIP, VAD, barge-in, turn-taking. Useful here, not required. * Programmatic prompt optimization techniques. * LLM-as-judge setups and other evaluation tooling. * GCP: Cloud Run or GKE, Pub/Sub, Vertex AI, GCS, Secret Manager, Cloud Logging and Trace. * Healthcare data familiarity. EXAMPLE PROBLEMS YOU'LL TACKLE * Stand up the AI audit pipeline so evals run automatically on slices of production traffic, with regression gates wired into CI. * Build a patient simulator that lets us stress-test agents at scale before they ever reach a real call. * Improve the RAG pipeline with hybrid retrieval and re-ranking, then prove the gains with faithfulness and context metrics. * Get OTEL-first tracing across the agent graph, with automated eval triggers on live traffic. * Turn EHR integrations into reliable tools the agents can call. TECH STACK Python, FastAPI, pydantic, asyncio, Redis, Postgres, vector stores, Docker, Kubernetes, Terraform, ArgoCD, OTEL, TypeScript, React. Real-time stacks (WebRTC, LiveKit, SIP, STT/TTS) where the work touches voice. WHAT SUCCESS LOOKS LIKE * Quadrivia's backend becomes a reference for reliability, safety, and performance. * Your services run above 99.99% availability under strict regulatory constraints. * Other engineers build new clinical workflows and agent capabilities quickly and safely. * AI-generated code gets reviewed, corrected, and owned by you.

Rerun

SOFTWARE ENGINEER, INFRASTRUCTURE At Rerun, we're building a new multimodal data stack for Physical l AI. Large parts of the physical-world economy will be transformed by these technologies, and we're building the data infrastructure and tools that enable it to happen. Rerun's open source project is already loved by some of the best teams in the world. Our commercial product, Rerun Hub, is a catalog and storage engine that already handles petabytes of robot training data for early customers, and we're now ready to onboard more teams. Read our latest post on what we're building: A new data layer for robot learning. You'll join a small team building Rerun Hub, and you'll own the control plane that makes it run, including the Kubernetes operator that automates deploying Hub into customer environments. WHAT YOU'LL WORK ON * Own our Kubernetes operator: the control plane that provisions, configures, and manages Rerun Hub deployments across our own cloud infrastructure and inside customer accounts. This is real software engineering: CRDs, controllers, reconciliation, APIs, tests, releases. * Deep customer onboarding: When a customer brings new infrastructure requirements, you extend our control plane to accommodate that. Your reconcilers will make Rerun Hub work end-to-end from networking, IAM, storage to cluster configuration. * Production reliability and scale: Observability, CI/CD, incident response, and the deployment experience from local dev through staging to prod. * Follow-the-sun on-call with the rest of the team. WE'D LOVE IT IF YOU HAVE * A strong software engineering background. You think of infrastructure as software you build, not just systems you operate. * Deep Kubernetes experience, specifically with the operator pattern: you've designed CRDs, written controllers (controller-runtime / kubebuilder / operator-sdk), and shipped them to production. Earlier-career engineers with strong Go and distributed-systems/kubernetes fundamentals plus genuine interest in this work are equally welcome; we're hiring across levels. * Proficiency in Go, and ability to read and contribute to an asynchronous Rust codebase (or eagerness to learn; much of our stack is Rust). * Solid experience with AWS, infrastructure-as-code (ideally Terraform/OpenTofu), and production-grade observability. * Comfort being customer-adjacent: going into a customer's cloud account and doing the deep plumbing to onboard them. * Great communication in English, an ownership mindset, and a curious, helpful attitude. BONUS * Experience with high-throughput, time-series, or analytical database systems * Background in data-intensive infrastructure * Interest in robotics, AR/VR, ML, or simulation HOW WE WORK AT RERUN * We're a remote company headquartered in Stockholm, Sweden. * We meet up in person for a week roughly once a quarter * The team you'll join has members in European and US-east timezones * Everyone is available for synchronous work between 1:30–5:00pm CET. Given our current team distribution, candidates outside of Europe or the US will be considered on a case-by-case basis to ensure there’s enough overlap for effective collaboration. * We've put together an uncommonly talented tech team, value agency and helpfulness highly, and expect everyone to take broad responsibility for what they build * We offer competitive cash and equity compensation, six weeks paid vacation, and whatever hardware and software you need to do your job