Software Engineer, Machine Learning, Applied AI

Role overview

Responsibilities

• Collaborate across product, design, operations, and infrastructure to build application experiences and custom user interfaces.
• Optimize code quality, efficiency, and performance; review peers’ code.
• Set team direction, lead initiatives, mentor peers, and support onboarding.
• Architect scalable systems, address performance issues, and reduce technical debt.
• Own components, features, or systems end to end.
• Identify model capability gaps and build complex systems, agentic pipelines, reinforcement-learning environments, and evaluations that produce training signals.

Minimum qualifications

• Demonstrated experience driving organizational change and leading complex technical projects.
• Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.

Preferred qualifications

• Master’s degree or PhD in Computer Science or a related technical field.
• Experience with TensorFlow, PyTorch, or Scikit-learn; understanding of information retrieval and NLP techniques.
• Knowledge of data structures and algorithms, including graph theory and optimization.
• Ability to integrate AI tools into workflows and implement responsible, ethical AI practices.
• Ongoing AI skill development, including prompt or context engineering and agent orchestration.
• Experience designing synthetic training-data or evaluation pipelines and verifiable training-data quality controls.
• Ability to solve ambiguous problems and propose technical or process improvements in a dynamic organization.

Compensation

• The posting describes base compensation as potentially hourly, monthly, or annual; it does not specify which cadence applies to this role.
• Compensation depends on skills, qualifications, experience, and location; bonus, equity, or sales incentives may be additional.

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