Staff ML Software Engineer (Geospatial)

TL;DR

Staff ML Software Engineer (Geospatial): Developing and deploying machine learning applications focused on geospatial data to address climate change impacts such as wildfires. With an accent on production system architecture, ML operations, and cloud infrastructure. Focus on designing scalable ML systems, security, monitoring, and delivering real-world products in a fast-paced environment.

Location: Mountain View, CA (onsite)

Salary: $197,000 - $311,000 (base only)

Company

hirify.global is a diverse group of inventors and entrepreneurs building breakthrough technologies aimed at 10x impact on global challenges, combining research ambition with startup speed.

What you will do

• Architect and develop production ML systems and software features balancing business needs and technology roadmap.
• Contribute to high-quality development, deployment, and maintenance of live ML applications in production.
• Create and maintain Google Cloud Platform infrastructure for software development and production systems.
• Collaborate closely in an agile team environment with pair programming and cooperative ideation.
• Present findings and guide future development directions to internal and external stakeholders.

Requirements

• Location: Must be able to commute or relocate to Mountain View, CA
• 7+ years experience in machine learning development pipeline including research, experimentation, and ML-Ops.
• Expertise in ML frameworks (PyTorch, TensorFlow/Keras/JAX) and Python libraries (NumPy, SciPy, Pandas).
• Experience with software design patterns and open source tools like Git, Apache Beam/Dataflow, Google Compute Engine.
• Proven ability to work in agile teams and early-stage projects evolving into production.
• Experience interfacing with customers and collaborating cross-functionally.

Nice to have

• Production-level experience in geospatial industry including security, testing, and monitoring deployed applications.
• Experience working with diverse geospatial data sets.
• Experience scaling machine learning applications into production (ML-Ops).

Culture & Benefits

• Equal opportunity workplace committed to diversity and inclusion.
• Supportive environment for people with disabilities and protected veterans.
• Fast-paced, collaborative, and agile-driven team culture.