Staff ML Engineer

This is a fully remote position, open to applicants in California.

📋 Description

• Design, train, assess, and deploy ML systems that enhance governance and security functions, beginning with challenges such as prompt injection detection, behavioral anomaly detection, trust scoring, and policy suggestions.

• Develop the necessary infrastructure: data pipelines, feature stores, model serving, evaluation frameworks, and feedback loops that facilitate swift iterations.

• Make informed decisions regarding build-versus-buy scenarios. Utilize cutting-edge models, ready-made tools, and managed services for rapid progress; invest in custom solutions where they provide a sustainable advantage.

• Establish the technical direction for the team's ML initiatives. Take ownership of the architecture, evaluation methodologies, model lifecycle, and the standards for deployment.

• Assist in recruiting, mentoring, and shaping the team as it expands.

• This position may involve participating in a 24/7 on-call rotation for the Agentic Platform; assume genuine pager responsibility for the services you develop and manage.

⛳️ Requirements

• Over 5 years of extensive applied ML/AI experience with a proven record of delivering production systems. Experience in fraud, abuse, safety, security, or trust sectors, where adversarial dynamics, imbalanced data, and critical decision-making are essential.

• More than 8 years of professional, hands-on, full-time software engineering experience in backend, infrastructure, or platform engineering roles.

• A Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.

• You have developed and managed systems surrounding ML models, such as data pipelines, serving, evaluation, monitoring, etc., and have delivered customer-facing products from start to finish.

• You are proficient with modern AI tools in your everyday tasks and possess a keen instinct for determining when frontier models can supplant traditional ML, when they cannot, and when to integrate both.

• Experience with LLM-based systems in production — including evaluation, prompt engineering, fine-tuning, retrieval, guardrails, and agent frameworks.

• Familiarity with the agent/MCP ecosystem.

• You thrive in an early-stage environment where the roadmap is developed as work progresses, making clear decisions with limited information.

• Collaborative and low-ego; you work effectively across teams, communicate clearly, and engage others in the process.

🏝️ Benefits

• Freedom & flexibility; align your work schedule with your personal life.

• Designated quarterly Whaleness Days along with an end-of-year Whaleness break.

• Home office setup; we prioritize your comfort while you work.

• 16 weeks of paid parental leave (after 6 months of employment).

• Technology stipend equivalent to $100 USD net/month.

• PTO plan that encourages you to take time for activities you enjoy.

• Training stipend for conferences, courses, and classes.

• Equity; as a growing startup, we want all employees to share in the company’s success.

• Docker swag.

• Medical benefits, retirement plans, and holidays vary by country.

• Remote-first culture, with offices located in Seattle and Paris.