Senior Machine Learning Engineer (Agent Systems)
About e:cue e:cue is a fast-paced, high-growth startup building custom AI analysts for leaders in marketing, finance, and revenue. Our platform combines production-grade application services, cloud infrastructure, and agent systems that power high-stakes business decisions. We're looking for a senior engineer who can take work from ticket to outcome: scope it, build it, ship it, and own it in production. Role Overview This role owns core parts of the agent stack, deciding how agents plan and execute, how they interact with data, and how we evaluate and improve them over time. You'll work across: Agent systems: planning, tool use, multi agent orchestration, long-context workflows Backend and infrastructure: agent services, data pipelines, and observability Evaluation and post-training: Designing evaluation harnesses, feedback loops, datasets, and improving agent behavior
What You'll Do
Design and build production agent systems: Tool execution frameworks (MCP servers, sandbox environments, tool architectures) Planning and reasoning pipelines Context and dependency aware agent execution Own services that power production agents: Reliability, latency, and scaling improvements Observability integrity (logging, tracing, evaluation hooks for offline and online evaluation) Develop evaluation and feedback systems: Define metrics for agent performance (offline and online) Own evaluation harnesses and test suites Instrument systems to generate high-quality evaluation and training data Contribute to post-training and model improvement: Dataset generation (trajectory collection, preference data) Fine-tuning (SFT, DPO, etc.) for modules where context engineering isn't enough Prompting and system design for better reasoning and context management
What We're Looking For
Experience building or working with LLM-powered systems Familiarity with Agents, tool use, or structured reasoning systems Experience with ML evaluation systems for ambiguous objectives Ability to own problems end-to-end Strong product intuition
Nice to Have
Experience with ML systems or training workflows, finetuning (SFT, DPO, RLHF, etc.), dataset construction and evaluation pipelines Experience building agent frameworks for tool-using LLMs for long-context or retrieval-heavy workflows Familiarity with modern inference, frontier APIs, and serving stacks (vLLM, SGLang, or similar) Experience at a startup owning large systems independently
Why Join Us
Build meaningful AI capabilities with direct business impact. Own state of the art agent development for domain specific workflows Work on both product and infrastructure with real ownership. Help shape architecture, reliability standards, and team practices as we scale. Join a small team where strong execution is visible and valued. Our Benefits and Total Rewards Remote team: work from where you need to Flexible paid time off: because you're an adult Generous health insurance reimbursement through QSEHRA Competitive salary Equity packages Company-performance bonus Equal Opportunity Employer We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected characteristic. We are committed to creating an inclusive environment for all employees and encourage individuals from underrepresented backgrounds to apply. Apply To This Job