Lead RF Data Scientist

Forterra • Durham, NC

1d • $175,000 - $220,000

About The Position

Forterra is hiring a hands-on applied-research technical lead to develop RF statistical-learning techniques for challenging real-world sensing environments. The work combines signal processing, statistical learning, and carefully designed experiments to recognize and understand signals when data is imperfect. The role takes ideas from mathematical formulation through working techniques, testing, and operationally relevant evaluation, with the goal of creating useful, understandable, and dependable capabilities.

The role works closely with RF and DSP engineers, platform engineers, analysts, runtime engineers, and operational users. It involves developing techniques for detection, classification, parameter estimation, and understanding complex signal environments; building disciplined, reproducible data and evaluation practices; characterizing synthetic-to-collected-data transfer; qualifying techniques; and translating learned signal behavior into structured event and object descriptions. The position requires producing durable technical artifacts and includes travel up to 10% to collection sites and test events, as well as the ability to commute to Durham (RTP), NC or Arlington, VA as needed.

Requirements

• M.S. or Ph.D. in electrical engineering, statistics, applied mathematics, computer science, physics, or a related quantitative discipline, or equivalent experience.
• At least 3 years of applied research or product development using measured data, including ownership of experiments from hypothesis through evaluation and release recommendation.
• Strong foundations in statistical learning, estimation, optimization, linear algebra, numerical methods, and experimental design.
• Ability to reason about uncertainty, identifiability, calibration, and failure modes, rather than only optimizing a leaderboard metric.
• Demonstrated experience building reproducible training and evaluation pipelines, including dataset versioning, data-quality controls, held-out evaluation, and experiment tracking.
• Proficiency in Python and the scientific Python ecosystem, such as NumPy, SciPy, PyTorch, or JAX.
• Ability to read C++ and CUDA sufficiently to verify deployed numerical behavior against the intended technique contract.
• Ability to author a technique specification, evaluation plan, and clear evidence-backed recommendation that another technical reviewer can audit.
• Strong written and verbal communication, and ability to work with engineers, analysts, and operational users while maintaining technical rigor.
• Must be a U.S. person eligible to obtain and maintain a U.S. security clearance.

Nice To Haves

• RF signal-processing experience with complex IQ, spectrograms, modulation, radar waveform parameters, receiver/channel impairments, and multi-signal interference; or a strong signal-processing background and ability to learn RF domain specifics quickly.
• Experience with source separation, multi-target tracking, structured prediction, time-frequency analysis, inverse problems, Bayesian methods, or uncertainty-aware deep learning.
• Applied research experience on national-security, intelligence-analysis, autonomy, communications, sensing, or other high-consequence operational problems.
• Experience building GPU-backed techniques or numerical pipelines in PyTorch, JAX, CUDA, or equivalent tooling.
• Experience with human-in-the-loop labeling, active learning, data-centric methods, or evaluation of partially labeled real-world corpora.
• Experience with ontology engineering, knowledge representation, or mapping technique outputs to structured semantic or event systems.
• Experience with technique release governance, model cards, safety cases, reproducible science, or formal verification of numerical software.

Responsibilities

• Lead RF technique development for detection, classification, parameter estimation, and understanding complex signal environments, selecting methods appropriate to the problem.
• Define technique inputs, targets, loss functions, uncertainty outputs, and decision rules for real RF collections, accounting for signal and receiver characteristics, incomplete labels, interference, and overlapping or confusable signals.
• Build disciplined data practices, including versioned datasets and splits, label-quality rules, leakage checks, and reproducible training and evaluation recipes.
• Clearly distinguish synthetic, simulated, and collected data in results.
• Design synthetic and hybrid data generation to exercise intended operating conditions and characterize transfer to collected data.
• Run training and ablation studies, diagnose failures, and design smaller, more informative follow-up experiments.
• Establish technique qualification through held-out and stress evaluation, calibration, confusion analysis, uncertainty behavior, tail-failure analysis, and readiness criteria.
• Map learned signal behavior to consistent, structured event and object descriptions with explicit evidence rules.
• Work with runtime engineers to specify technique artifacts, features, preprocessing, numerical tolerances, test vectors, and fallback behavior.
• Review C++/CUDA implementation changes for fidelity to the technique specification.
• Work with analysts and field teams to turn collection observations into prioritized labeling, replay, and evaluation work, and use findings to improve techniques or narrow their approved operating envelope.
• Produce derivations, experiment plans, technique documentation, data and label specifications, evaluation reports, and design reviews that distinguish measured evidence from assumptions.
• Travel up to 10% to collection sites and test events and commute to Durham (RTP), NC or Arlington, VA as needed.

Benefits

• Equity is included in most full-time, high-demand roles.
• Three premium healthcare plan options, including an HSA-eligible plan; Forterra covers 80% of the plan premium for the employee and dependents.
• Basic life/AD&D and short- and long-term disability insurance plans fully covered by Forterra, with the option to purchase additional life insurance for the employee and dependents.
• Company holiday calendar including a winter break in December.
• 20 days of paid time off accrued per year.
• At least 7 weeks of fully paid parental leave for birth or adoption.
• $9,000 annual tuition reimbursement or professional development stipend.
• Fully stocked beverage refrigerators.
• 401(k) retirement savings plan with traditional, Roth 401(k), and after-tax deferral options, with company matching up to 4%.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level