MTS: AI Research Engineer

Type: Full Time, Hybrid Team: Research Focus: AI & Agent Systems Who We Are We're a team of founders, engineers, researchers, creatives, and operators building what we believe will be one of the defining companies of the AI era. Some of us came from startups. Some from academia. Some from hospitality, defense, design, or completely different worlds. We don’t care how you got here - we care about your energy, intelligence, curiosity, resilience, and ambition.

Who We Are Not We are not remote. We value the spontaneous moments that happen when we’re together - over dinner, in the hallway, around whiteboards. We like being around each other because the best conversations here rarely happen in meetings. We are not your typical team. It’s not just the 10 countries we’re from, the languages we speak or our non-traditional backgrounds. We’re solving hard problems with people we respect - we make the most of our time together, we make it special. We are not another “polished” SF startup. We value velocity over speed, raw talent over brands, and genuine human connection above all else. We value being successful, not looking successful. What You’ll Own & Build As a Member of Technical Staff within the Research Tribe, you’ll be one of the early engineers shaping the core systems that power Seldon. You won’t just build agents - you’ll design the infrastructure that governs how they operate: how they coordinate, how they’re evaluated, and how their behavior improves over time. This is a deeply technical role bridging distributed systems, machine intelligence, and product - turning stochastic models into reliable, production-grade systems. Multi-Agent Systems Architecture: Design and implement agentic systems, rather than prompt chains, at scale. You’ll define agent topologies, robust orchestration layers, structured state management, persistent and scoped memory, tool-use registries and execution, and build structured, inspectable systems. You’re building a long-running harness-based agentic platform, not wiring together LLM API calls. Behavioral & Persona Modeling: Simulate user archetypes with goal-directed behavior. You’ll design data-grounded personas, enable “computer-use” on real interfaces, and develop agents with critique and reflection loops. You’re producing measurable, actionable behavior. Evaluation & Prompt Engineering: Design prompt schemas and reasoning templates as integrated systems. You’ll build frameworks that measure behavioral fidelity and failure modes, and implement automated and HITL feedback. If it can’t be measured, it doesn’t ship. Signal & Insight Systems: Build systems that transform raw agent outputs into high-signal insights. You’ll cluster observations across runs, implement severity scoring, and map behavioral signals to product decisions. Turn noisy outputs into decisions. Production Reliability: Build the infrastructure to operate agents in production. You’ll implement tracing, attribution, and cost monitoring, detect failure modes and design fallbacks, circuit breakers, and evaluation pipelines. The bar is production reliability. Who You Are Systems, Not Prompts: You prioritize state machines, orchestration layers, and tool-use contracts over prompt hacking. You build for reliability, inspectability, and improvability - you’re uncomfortable with “it just works sometimes.” If it can’t be measured, it doesn’t ship. Production Experience: You have 5+ years building complex software and 2+ years shipping agentic LLM systems. You’ve built harnesses where agents manage tool selection, error recovery, and multi-step execution autonomously in production environments that run, break, and evolve. Orchestration Systems: You’re experienced with multi-agent orchestration, sandboxed execution, and complex backends. You optimize for coordination, scoped memory & context, and how agents degrade gracefully under pressure. Python Mastery: You’re an expert in async programming and structured data modeling (Pydantic), building maintainable, scalable systems designed for extensibility. Fast, Iterative Builder: You thrive when research and product move together. You’re comfortable shipping quickly, learning from real users, and refining systems in tight loops. High Ownership, Low Ego: You take responsibility for what you build. You’re willing to be wrong, change your mind, and prioritize being effective over being “theoretically right. Comfortable at the Frontier: You’re excited by ambiguous problems. You’re not waiting for best practices - you’re helping define them. Product Intuition: You prioritize signal over noise because outputs matter. You care that what you build helps someone make a decision. All Backgrounds Welcome: Some of us are dropouts, some have PhDs. Some are tech veterans, some are first-timers. What matters - how you think, how you build, and how you work in teams.

Why Seldon The People: Join a global team of founders, engineers, researchers, and adventurers obsessed with human behavior - we’re curious, willing to be wrong, and privileged to be solving hard problems at the frontier. The Problem: Deep science with real impact. We leverage behavioral modeling, cognitive science, and cutting-edge AI to solve real product challenges for real customers. The Velocity: Ship fast and learn faster. Work directly with customers and see the impact of your work in hours, not weeks or months. The World-Class Backing: Backed by top funds including MaC VC, Protagonist, Rackhouse, Blank, and Weekend Fund, as well as scouts at a16z, Greylock and CRV, and product leaders and researchers from orgs. inc. Meta, Airbnb, Google, Discord, Uber and more. The Member Of Staff Philosophy: You don’t care about titles - you value extreme ownership. Comp & Benefits Salary: $180-250k base + equity Health (US only): 100% paid medical, dental & vision PTO: 28 days (inc 5 company-wide days on stats) Environment: Beautiful offices in SoMa & Tower Bridge optimized for deep collaboration WFH: 2 days/week (Mon & Fri) to catch up on laundry, save time commuting, and let your cat walk across the keyboard Adventures: Team dinners, offsites, and events throughout the year