Staff Software Engineer

Responsibilities

• Lead projects within QPU calibration and automation software while coordinating work across scientists and engineering teams.
• Develop and evaluate machine learning approaches for parameter estimation, surrogate modeling, anomaly detection, drift detection, and adaptive experiment selection.
• Build reproducible data and model pipelines covering validation, training, versioning, deployment, and monitoring.
• Evaluate models against numerical and statistical baselines using simulation, historical data, and controlled hardware experiments.
• Integrate validated models into calibration workflows with operational limits, fallbacks, traceability, and failure investigation.
• Architect and maintain Python services, REST APIs, relational data stores, and user interfaces for experimental and model results.
• Improve testing, observability, reliability, and technical quality practices, and mentor junior and new team members.

Requirements

• MS or higher in Computer Science, Electrical or Computer Engineering, Mathematics, Physics, or a related field, or equivalent relevant professional experience.
• At least 6 years of professional software development experience delivering production systems and contributing to technical decisions.
• Demonstrated ownership of machine learning initiatives from problem definition and model development through evaluation, deployment, and measurable outcomes.
• Strong Python skills and experience with scientific computing and machine learning libraries such as NumPy, pandas, SciPy, scikit-learn, PyTorch, or TensorFlow.
• Proficiency in another language such as Go, Java, C, or C++.
• Practical knowledge of statistical modeling, optimization, experimental design, model evaluation, data leakage, overfitting, uncertainty, and reproducibility.
• Experience translating scientific or engineering problems into machine learning tasks and explaining results and limitations to domain experts.
• Experience building maintainable services and REST APIs with SQL and relational databases such as PostgreSQL, and developing interfaces with React, Angular, Vue.js, or comparable technologies.
• Experience with Git, AWS, automated unit, integration, and end-to-end testing, and code review.
• Familiarity with LLM-based coding assistants and the ability to review their output for correctness, security, and maintainability.

Benefits

• D-Wave describes a total rewards package including company ownership, competitive pay, equity, bonus, perks, benefits, and career growth support.
• The role is based in New Haven.