Senior Machine Learning Engineer (Agent 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

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

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

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

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.

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.