Machine Learning Lead - Geospatial, Bellwether

You will be a hands-on Machine Learning engineer, contributing to all aspects of the project’s development and deployment of applications. We are looking for a motivated expert level ML Engineer with broad experience across systems architecture and design in one or more cloud platforms. This role would guide machine learning for Bellwether’s real-world products, and is not a research-based role.

Our team is small but mighty and highly collaborative, and values pair programming and cooperative ideation. We are committed to agile principles and rely heavily on this framework for efficient sprints and cycles. We are looking for passionate and driven people, who are comfortable moving between creative, big-picture thinking and specifics of how to execute. We operate in a fast-paced, fluid environment as our team moves from early stage development into production phases.

Embracing your ability to be a ML ‘expert generalist’, enjoying the fluidity of moving from architecting new production systems, to machine learning, to security and monitoring. From high level strategy to specific tactics.

Help drive and execute key decisions on software architecture and features, balancing business needs and our technology roadmap, balancing longevity with rapid prototyping

Contribute as a key team member to the creation of new systems and processes to ensure high quality development, deployment, and maintenance of live applications in production environments

Create and maintain Google Cloud Platform-based infrastructure for software development and high-volume production systems.

Present findings to team members, internal and external stakeholders, and help set a direction for future development.

Master's degree or PhD in Computer Science, Applied Mathematics, Physics, or equivalent practical experience

7 years experience with the machine learning development pipeline: research, experimentation, and ML-Ops

Experience in engineering management or as a technical lead, with a track record of guiding team strategy and mentoring engineers while remaining hands-on.

Expertise in ML frameworks (e.g., PyTorch, TensorFlow/Keras/JAX) and Python libraries (e.g., NumPy, SciPy, Pandas).

Experience with numerous common software design patterns (for example, Observer, Decorator, Visitor, Producer/Consumer, etc).

Experience with open source tools such as: Git, TensorFlow, Apache Beam/Dataflow, Google Compute Engine.

Python proficiency.

Experience working on an early stage project and environment where prototype technologies are evolved into a production phase.

An ability to thrive in an Agile-driven team: iteratively sprinting toward goals and products, contributing new ideas, standards, and processes.

Experience interfacing with customers

Production-level experience in the geospatial industry, with a wide variety of tasks, including code development, designing for, implementing, and managing security measures and controls, troubleshooting and debugging, designing and implementing code testing processes, and monitoring deployed application’s performance and health.

Experience working with a wide variety of geospatial data

Experience in Machine Learning Operations - scaling existing machine learning applications into production

The US base salary range for this full-time position is $197,000 - $311,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.