7 months ago
Base Salary
$140k - $220k/yr
Responsibilities
- Turn ambiguous client problems into shipping code.
- Drive projects from discovery to deployment.
- Collaborate with client and internal project teams.
- Design and write clean, scalable code at appropriate quality standards.
- Design, integrate, and productionize ML solutions including predictive models and GenAI systems.
- Collaborate with domain experts to translate business needs into ML solutions.
- Advocate for engineering best practices and positive dev culture.
Requirements
- 5+ years building and deploying ML systems in production environments.
- Expert-level Python and experience with PyTorch / TensorFlow.
- Deep expertise in at least one domain: NLP, Computer Vision, Time-Series, or Reinforcement Learning.
- Experience with generative AI and LLM-related capabilities.
- Proficiency in MLOps and infrastructure automation.
- Strong engineering fundamentals in system design, scalability, testing, and monitoring.
- Track record of translating ambiguous business problems into production ML solutions.
- Experience with cloud ML platforms like AWS SageMaker, GCP Vertex AI, or Azure ML.
- Champion for quality in model validation and monitoring.
Benefits
- Competitive early-stage startup compensation.
- Bonus eligibility.
- Health insurance with meaningful coverage for dependents.
- Flexible paid time off.
- Equity.
- Fully remote culture with a cluster of teammates in Seattle.
- Training and learning opportunities.