Machine Learning Engineer, Forest Ecosystems

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Overview

Planet is a global technology company that combines space and data to solve some of the world's most pressing environmental challenges. They are the architects behind the largest constellation of imaging satellites, which delivers an unparalleled dataset via a cloud-based platform. This information empowers users from various sectors including commercial, environmental, and humanitarian fields.

By marrying hardware design, manufacturing, data processing, and software engineering, Planet has established a people-centric company culture. They are committed to iterating in a way that prioritizes their employees while addressing essential global issues. This innovative company is now looking for a Machine Learning Engineer to join their Forest Ecosystems team.

Role Details

Position Overview

The Machine Learning Engineer will function within a cross-functional team, primarily composed of engineers and data scientists, focusing on optimizing and maintaining machine learning models that utilize remote sensing data. This role requires strong collaborative skills as you will engage with various stakeholders to improve algorithms, deploy models, and ensure efficient data pipelines.

The primary mission of the Forest Ecosystems team is to map and monitor the world's forests by converting high-resolution satellite imagery into quantifiable metrics, such as tree heights and carbon levels. The work involves utilizing deep learning models and continuously optimizing for performance.

Responsibilities

The Machine Learning Engineer will be entrusted with several key responsibilities, such as:

• Establishing and maintaining machine learning operations workflows for regular data generation.
• Running experiments to evaluate various machine learning algorithms and tuning operational procedures.
• Developing and implementing tests to ensure the robustness of deployed models.
• Contributing to full-stack development, including backend and APIs, alongside DevOps tasks and occasional frontend work.

Required Skills

Educational Background

Candidates should ideally possess a Bachelor's or Master's degree in Computer Science or a related field.

Experience and Technical Skills

• Professional Experience: A minimum of 4 years in software engineering, with at least 2 years focused on developing and designing computer vision and machine learning systems.
• Technical Proficiency: Expertise in Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch is required. Knowledge of software engineering best practices, including version control and CI/CD practices, is also essential.
• Containerization Skills: Experience with tools like Docker and Kubernetes is a plus, along with capabilities in monitoring and observability frameworks.
• Communication Skills: Strong documentation and technical communication skills are key to success in this role.

Desirable Attributes

Candidates with experience in remote sensing and a solid understanding of geospatial data will have an advantage, especially in using technologies relevant to raster and LiDAR data. Familiarity with deep learning applications in geospatial contexts will also be beneficial.

Compensation and Benefits

The role being offered is full-time and remote-friendly, allowing candidates from across the United States and Canada to apply. The salary ranges based on geographic location and level of expertise:

• For New York City and California, the salary ranges from $136,000 to $170,000 USD.
• For San Francisco, it ranges from $144,500 to $180,600 USD.
• For the national average in the U.S., the salary varies between $127,000 and $158,700 USD.

Benefits Provided

Planet provides a comprehensive range of benefits, which include:

• Extended health and dental insurance
• Health spending account
• Retirement savings plan with company contributions
• Paid time off including vacation and holidays
• Remote-friendly work environment
• Wellness programs and reimbursements for home office setups
• Tuition reimbursement opportunities and access to further educational resources like LinkedIn Learning.

Application Process

Application Deadline: Applicants should apply before June 10, 2025, to be considered for this exciting opportunity.

Planet aspires to create a workforce that reflects diverse backgrounds and encourages all individuals to apply, regardless of experience levels. They are committed to fostering a strong culture of belonging and inclusivity, making it imperative to embrace diverse talents in their teams.

Conclusion

If you are passionate about machine learning, environmental data, and remote sensing, this role at Planet presents a unique opportunity to contribute positively to the planet while advancing your career. It is an excellent chance for professionals looking to combine technology with humanitarian efforts in a collaborative, innovative environment.

This job offer was originally published on himalayas.app