Software Engineer: Industry Experience

Key Skills

JavaScript, Machine learning techniques, NumPy, Python Programming, PyTorch, TensorFlow

Job Description

OUR MISSION

Mineral’s mission is to discover the intelligence of plantkind to feed and protect humankind. Our technology embraces the complexity of nature, unlocking agriculture data so the world can reimagine sustainable food production. This means leveraging advanced technology and use of AI across the total plant ecosystem to turn complex data into understandings that enable greater efficiency, productivity and sustainability.

Agriculture background preferred but not required — just the curiosity and passion to learn. If you are excited to make a difference in global food production and help work toward a more sustainable future for agriculture, we’d love to talk with you.

About the role:

As a Software Engineer on the team, you will be working to shape effective and efficient ML model development user journeys.You will learn and build a ML system to revitalize the end-to-end workflow of building and landing ML models. This includes collecting and processing data, training and evaluating models, deploying models in our customers’ production environments, and ensuring the models’ quality. You will also have the opportunity to work with our research team and experiment SOTA ML models.

• Design and implement scalable and robust data lake, data pipelines framework, and a efficient data labeling system to empower data-centric ML system
• Build efficient ML model training, model management, and resource management system to enable streamlined, scalable, and stable model training workflow
• Support research team to experiment SOTA ML models
• Develop, build, and release tools on Google Cloud Platform
• Build and implement edge model training and evaluation solutions for production hardware
• Be a thoughtful engineer on the decisions on software architecture
• See through a project from conception to finished product, and meet both technical and consumer needs

What you should have:

• Bachelor's degree in Computer Science, Machine Learning, similar technical field of study, or equivalent practical experience
• 2+ years industry experience in a software engineer role or 1 year of industry/internship experience with a PhD degree
• Experience solving problems using Machine Learning with Tensorflow, PyTorch, or equivalent tools
• Strong team player with excellent verbal and written communication skills
• Strong experience programming in Python with robust and efficient code

It would be great if you also had these:

• Master's degree in Computer Science Machine Learning, similar technical field of study, or equivalent practical experience
• Experience tackling computer vision problems using Deep Learning models
• Experience working with intensive time series or other sequence data
• Willing to work in a fast-paced, start-up-like environment. Fast learner who can think through and adapt to new problems quickly
• Agriculture background

The US base salary range for this full-time position is $132,500 - $203,000 + 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. Learn more about benefits at Google

At Mineral, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.