Senior AI/ML Engineer
Cyberhaven
full-time
Posted on:
Location Type: Remote
Location: United Kingdom
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Job Level
About the role
- Design and scale distributed systems: Architect, build, and optimize highly scalable and fault-tolerant systems that process large graph datasets at enterprise scale, handling billions of events in real time from tens of thousands of endpoints with sub-second latency.
- Solve complex scaling challenges: Tackle real-world performance and reliability problems through deep analysis, profiling, and systematic troubleshooting in high-throughput distributed environments.
- Build with modern infrastructure: Develop and evolve a microservices-based architecture using technologies such as Go, Kubernetes, Docker, and Redis, in a continuously improving production stack.
- Engineer secure-by-design software: Write hardened, security-first code capable of safely processing untrusted data, resisting real-world attack vectors, and operating reliably across large-scale, internet-facing systems.
- Productionize AI systems: Partner with research and product teams to operationalize AI prototypes, turning experimental models into robust, scalable, and production-ready services.
Requirements
- Proven Backend Expertise: 6+ years of experience building and scaling backend systems, with strong proficiency in Python and/or Go, powering production applications used at scale.
- Full-Stack Impact: Demonstrated track record of designing and delivering full-stack applications that are actively used in real-world, high-traffic environments.
- Generative AI & ML at Scale: Hands-on production experience with large-scale foundational models and transformer-based architectures, including deploying, monitoring, and iterating on GenAI systems.
- Agent & Workflow Systems: At least 1 year of experience building AI agents and orchestration workflows using frameworks such as LangChain, LangGraph, Genkit, or similar technologies.
- ML Systems & Data Pipelines: Experience delivering machine learning systems at scale, including robust model evaluation, continuous quality improvement pipelines, and data processing using columnar databases and large messaging systems (e.g., Pub/Sub, Kafka).
- Ownership & Innovation Mindset: Comfortable working in remote, fast-paced environments, with an entrepreneurial mindset-driven to solve complex, real-world problems through innovation and breakthrough technology.
Benefits
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Applicant Tracking System Keywords
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Hard Skills & Tools
PythonGomicroservicesdistributed systemsAI systemsmachine learningdata processingmodel evaluationscalabilityfault-tolerance
Soft Skills
problem-solvinginnovation mindsetownershipentrepreneurial mindsetcollaborationcommunicationadaptabilityanalytical thinkingtroubleshootingperformance analysis