Staff ML Software Engineer (Geospatial)

Location: Mountain View, California, United States (HQ)

US base salary: $262,000–$369,000 per year, plus bonus, equity, and benefits.

Company

hirify.global, builds and launches ambitious technologies aimed at addressing large-scale global challenges.

What you will do

• Guide machine learning development and deployment for Bellwether’s real-world geospatial products.
• Architect and implement Google Cloud Platform infrastructure for software development and high-volume production systems.
• Drive software architecture and feature decisions while balancing rapid prototyping, business needs, and long-term maintainability.
• Build systems and processes for reliable development, deployment, maintenance, security, and monitoring of live applications.
• Present findings to internal and external stakeholders and help shape future product direction.
• Mentor engineers, guide team strategy, and collaborate through pair programming and agile sprints.

Requirements

• Master’s degree or PhD in Computer Science, Applied Mathematics, Physics, or equivalent practical experience.
• At least 7 years of experience across the machine learning development pipeline, including research, experimentation, and ML-Ops.
• Experience as an engineering manager or technical lead, with a record of guiding strategy and mentoring engineers while remaining hands-on.
• Expertise with ML frameworks such as PyTorch, TensorFlow/Keras, or JAX, and Python libraries including NumPy, SciPy, and Pandas.
• Python proficiency, software design patterns, Git, Apache Beam/Dataflow, and Google Compute Engine experience.
• Experience evolving prototypes into production systems, working in agile teams, and interfacing with customers.

Nice to have

• Production-level experience in the geospatial industry.
• Experience with varied geospatial data and production ML application scaling.
• Experience designing security controls, testing processes, troubleshooting systems, and monitoring application health.

Culture & Benefits

• Work in a small, collaborative team focused on machine learning, geospatial data, and climate-related severe weather.
• Use agile principles, iterative sprints, pair programming, and cooperative ideation.
• Participate in projects moving from early-stage development into production.
• Compensation includes bonus, equity, and benefits in addition to the base salary.