Eureka Labs

Full-stack Engineer

• Design, build, and maintain full-stack solutions across frontend, backend, APIs, and integrations.
• Develop and support growth-related initiatives, experiments, and internal tools.
• Design measurement systems and analytics architecture, not just implement tracking requirements.
• Work across multiple systems and technologies to solve business and product challenges.
• Collaborate closely with product, growth, and leadership stakeholders to identify opportunities and implement solutions.
• Design and improve analytics, tracking, and measurement systems to support data-driven decision-making.
• Implement and maintain integrations with third-party platforms and services such as Stripe, analytics tools, and external APIs.
• Contribute to architectural and technical decisions with a pragmatic and scalable mindset.
• Operate effectively in an environment with evolving priorities and limited structure.
• Take ownership of initiatives from discovery through implementation and iteration.
• Continuously evaluate and improve processes, tooling, and system efficiency.

Staff Full-Stack Engineer

Backend Engineer

• Work closely with product and design teams to develop web applications.
• Collaborate with a team to define, design, and ship new features.
• Design, build, and maintain high-performance, reusable, and reliable backend code using Python.
• Contribute industry best practices and technology to developing and maintaining software applications.
• Help maintain code quality by implementing bug fixes and code reviews.
• Design, build, and automate high-quality tests that scale with app growth.
• Conduct code reviews, develop high-quality documentation, and build robust test suites for your products.
• Respond to and troubleshoot highly complex problems quickly, efficiently, and effectively.

Python Developer

Data Scientist

• Design, train, evaluate, and deploy machine learning models for real-time and near–real-time applications.
• Partner with the Senior Cloud Engineer to deploy models within cloud pipelines.
• Collaborate on the design and optimization of data pipelines used for model training, inference, and monitoring.
• Establish metrics for model performance, data drift, and system health.
• Analyze the impact of new features and model changes in production environments.
• Work closely with cloud, perception, and UI engineering teams to integrate ML outputs into customer-facing products.

Staff Full-Stack Engineer

Python Developer

Freelance Data Scientist