Senior Machine Learning Systems Engineer
The Mission :
We are building the next generation of intelligence. This isn’t just about calling an API; it’s about engineering the plumbing, the memory, and the reasoning logic that allows AI to navigate complex datasets. You will be responsible for delivering fast, brilliant, and architecturally sound solutions.
What You’ll Own:
- Cognitive Architecture: Beyond simple prompts, you will engineer the decision-making loops (agents) that allow our tools to self-correct and execute multi-step coding tasks.
- Context Engineering: Develop the retrieval and embedding logic that ensures the model “sees” the right data at the right time, minimizing noise and maximizing signal.
- System Integrity: Move beyond “vibe-based” testing. You’ll build rigorous, automated frameworks to quantify model behavior and prevent regressions in production.
- Model Lifecycle: Own the decision between fine-tuning a specialized small model versus orchestrating a frontier LLM, balancing latency with reasoning depth.
- Technical Leadership: Act as the “Engineer’s Engineer,” setting the standard for how we write production-grade ML code and mentor the team on high-stakes delivery.
Your Technical Toolkit :
- The GenAI Stack: Extensive experience with the “Agentic” ecosystem (orchestration frameworks, vector-native databases, and semantic search).
- Production ML: A history of shipping models that actually handle traffic. You know that “done” means deployed, monitored, and stable.
- Code-Fluent: You are a strong software engineer. You are as comfortable in the depths of a Python backend as you are tweaking a model’s temperature. Familiarity with JVM-based languages (Java/Kotlin) is a significant edge.
- The Scientific Method: You don’t guess; you experiment. You have a background in statistical validation and know how to prove a model’s value via data.
Why You’re a Fit :
- You find the “unknowns” of Agentic AI exciting, not paralyzing.
- You believe that a model is only as good as the data pipeline feeding it.
- You are tired of “wrapper” apps and want to build deep, integrated AI systems.
- You have 5+ years of total ML experience, with a heavy recent focus on the LLM frontier.