- Company Name
- Raindrop
- Job Title
- Founding ML Engineer
- Job Description
-
**Job Title**
Founding Machine Learning Engineer
**Role Summary**
Lead the design, implementation, and scaling of machine‑learning systems that detect silent failures in AI agents. Own end‑to‑end ML pipelines, from data ingestion to production inference, and collaborate closely with product and engineering to deliver a high‑volume, real‑time alerting platform.
**Expectations**
- Deliver a production‑grade product that handles millions of events daily.
- Balance rapid iteration with rigorous testing and monitoring.
- Own technical strategy, choose appropriate frameworks, and influence product roadmap.
- Exhibit a growth mindset, strong problem‑solving ability, and a passion for building elegant, well‑designed solutions.
**Key Responsibilities**
- Architect scalable data pipelines for ingesting, processing, and storing vast volumes of event data.
- Design, train, and tune custom models that identify diverse failure modes (e.g., laziness, forgetting, task‑failure) across AI agents.
- Deploy models to production, ensuring low latency, high availability, and continuous monitoring of performance.
- Iterate rapidly on models and infrastructure while maintaining robust testing and documentation.
- Work with product and engineering teams to translate user needs into technical requirements and features.
- Mentor and guide junior engineers; contribute to hiring and team culture.
- Evaluate and integrate new ML/AI tools, frameworks, and best practices into the stack.
**Required Skills**
- Proficient in Python, deep learning frameworks (TensorFlow, PyTorch, JAX).
- Strong background in data engineering: streaming, batch processing, and data warehousing.
- Experience building and deploying scalable MLOps pipelines (MLflow, SageMaker, Kubeflow, Airflow).
- Knowledge of monitoring, logging, and alerting systems for AI/ML applications.
- Solid understanding of software engineering fundamentals (CI/CD, version control, testing).
- Ability to prototype quickly, debug complex distributed systems, and optimize for performance.
- Excellent communication skills and a collaborative mindset.
**Required Education & Certifications**
- Bachelor’s degree or higher in Computer Science, Electrical Engineering, Machine Learning, or related field (equivalent experience acceptable).
- Certifications in ML/AI or cloud services preferred (TensorFlow Developer, AWS Certified Machine Learning, Google Cloud Professional ML Engineer).
San francisco, United states
On site
10-03-2026