Senior Research Engineer, Solid Mechanics

Team: R&D

Location: San Francisco, CA

Commitment: Full-Time

Workplace Type: hybrid

Responsibilities

• Design physics-based measurement algorithms.

• Determine which physical and structural input parameters most reduce algorithm uncertainty, to what precision they are needed, and how to acquire them—optimizing the tradeoff between input data cost and measurement accuracy. Identify which error sources dominate and mitigate them.

• Design and execute field validation studies: develop the protocol, sample size, acceptance criteria, and ground truth measurement methods to evaluate our measurement products.

• Serve as the team’s theoretical subject matter expert on structure mechanics: failure modes, material nonlinearity, creep, damage progression, soil-structure interaction, and regulatory strength standards.

• Investigate alternative measurement principles that could improve accuracy or add interpretability.

• Mentor team members on structural mechanics fundamentals and raise the rigor of the team’s scientific work.

• Collaborate closely with cross functional stakeholders to operationalize new capabilities from measurement to customer delivery.

Required Skills

• PhD in Mechanical Engineering, Civil/Structural Engineering, or a closely related field plus 3+ years of relevant industry experience, or MS in one of those fields plus 6+ years of relevant industry experience with a demonstrated track record of leading structural mechanics work end-to-end.

• Deep expertise in solid mechanics: beam theory, stress-strain constitutive models, failure criteria, fracture mechanics, fatigue. Able to derive and critically evaluate structural models from first principles.

• Experience with nonlinear material behavior—specifically wood, composites, biological materials, or other anisotropic/viscoelastic materials. Understanding of how material structural variability, environmental factors, anisotropy, and aging affect mechanical properties.

• Track record of designing and analyzing physical experiments or validation studies with quantitative rigor—defining acceptance criteria, characterizing uncertainty, and drawing defensible conclusions.

• Scientific computing: comfortable developing mechanics models and writing experimental analysis pipelines in Python, MATLAB, or equivalent.

• Strong technical judgment, communication, and ability to translate complex mechanics into actionable engineering recommendations.

• Experience leading technically complex work across multiple stakeholders and deadlines.

Relevant Depth Areas

We do not expect every senior candidate to be equally deep in every area below. Strong candidates will usually bring deep experience in several of these areas.

• Wood, timber, or nonlinear material mechanics: experience with the mechanical behavior of wood, fiber-reinforced composites, or other anisotropic/viscoelastic materials—species- or batch-dependent properties, moisture and environmental effects, progressive degradation, load duration factors, and relevant standards.

• Sensor data interpretation for physical systems: experience using sensor signals to infer the physical state of a structure or system—developing physics-based models that connect indirect measurements to quantities of interest, and understanding how measurement error propagates into derived quantities.

• Geotechnical mechanics: soil-structure interaction modeling, foundation stiffness characterization, or embedded pile/pole analysis.

• Probabilistic structural analysis: reliability methods, Monte Carlo simulation, extreme value statistics, or load and resistance factor design (LRFD) applied to structural systems.

• Experimental mechanics: strain gauging, load testing, DIC, or other experimental stress/strain measurement on structures. Experience designing controlled loading experiments.

• FEA of nonlinear or composite structures: finite element modeling of wood, composite, or other nonlinear material systems under combined loading—including material model selection, mesh sensitivity, and validation against experimental data.

Bonus Skills

Bonus Experience

• Familiarity with GIS tools or spatial analysis for infrastructure data.

• Published research in wood mechanics, structural reliability, or structural health monitoring.

• Experience designing field studies or validation trials with external partners.