Algorithms Team Lead (Geophysics)

Location: Tel Aviv, Israel; field work may be required.

Company

hirify.global develops geotechnical algorithms for processing real field data from diverse sensor systems and producing subsurface analysis for customers.

What you will do

• Lead the algorithms team within the Geotech group and translate business needs, customer requirements, and field constraints into an algorithmic roadmap with measurable goals and timelines.
• Set priorities across parallel workstreams, stop directions that are not maturing, and protect the team from interruptions that do not support the roadmap.
• Manage individual goals, feedback, professional development, hiring, and onboarding.
• Define validation methods, performance metrics, datasets, and ground truth; own code quality, reproducibility, documentation, and engineering standards.
• Independently develop and prototype algorithms, analyze failure cases and anomalies, and review work at a deep technical level.
• Work with field teams, including going into the field as needed, to understand noise sources and physical limitations.

Requirements

• Proven experience developing signal-processing algorithms on real physical data, not simulation-only data.
• Strong DSP fundamentals, including time- and frequency-domain analysis, filtering, deconvolution, SNR, and sampling.
• Experience with inverse problems and/or reconstruction and imaging, including tomography or migration, ill-posed problems, and regularization.
• Full command of Python and the scientific stack, including NumPy, SciPy, and related tools, with the ability to write clean, maintainable code.
• Prior management experience, or proven technical leadership of several developers and an end-to-end project.
• Ability to make decisions under uncertainty and prioritize competing directions.
• Professional-level Hebrew and English.

Nice to have

• Background in geophysics or in a field measuring physical phenomena through a complex medium, such as medical imaging, sonar, radar, NDT, seismology, or acoustics.
• Experience with ML/DL applied to signals and imaging, including judgment about when a classical approach is preferable.
• Experience taking an algorithm from R&D into production.
• Familiarity with physical models and forward modeling.

Culture & Benefits

• Hands-on technical leadership rather than management from a distance.
• Direct involvement in quantitative validation, reproducibility, documentation, and engineering quality.
• Collaboration with field teams and exposure to real-world sensor data and physical constraints.