Role Summary

As a NLP Machine Learning engineer, you will be responsible for developing NLP microservices that will enable the core offerings of semantic context-based search of Earth data. You will work collaboratively with the CTO, Head of ML, Head of Engineering, & Head of Product to deliver innovative, operational solutions that solve the fundamental need of translating a naturally phrased query into a machine query that can return context-bound and semantically relevant Earth data results. Your role in managing the lifecycle of our NLP capabilities will be a critical aspect of ensuring the success of the business.

What You’ll Do

• You’ll be responsible for model design, implementation, training, and testing of cutting edge Natural Language models for human to machine translation for semantic search
• You’ll use your expertise in a variety of NLP areas such as LLM, NLU/NLG, tokenization, lemmatization, entity classification, LDA, POS, etc. to solve a variety of complex challenges
• You’ll be responsible for the entire lifecycle of model development, operations, and maintenance
• You’ll research new techniques and technologies in the NLP space (including GenAI), evaluate their potential for improving the quality of the core product, and document your findings
• You’ll define key system metrics and data you need to develop models/approaches effectively
• You’ll work collaboratively with the team and foster an agile MLOps culture that encompasses model development, training, tuning, and validation to ensure timely, quality, product delivery, and lifecycle management
• You’ll contribute to advanced algorithms that transform data and relational graphs into interpretable information that feed into semantic search services that will delight, connect, and enable non-experts to become consumers of earth data

What We Are Looking For

• You are collaborative with a go-getter mindset, and self directing behaviors for the benefit of the team, the customer, and the company culture
• You have high integrity - you seek open and honest communication, and you hold yourself to high moral and ethical standards
• You are able to effectively manage concurrent technical tasks with competing priorities independently, approach difficult problems with enthusiasm and creativity, effective team communicator, and the ability to change focus when necessary
• You have a strong customer oriented mindset, and drive to focus on what a customer truly wants
• You have hands on experience with building NLP Applications
• You are proficient in ML Toolkits (e.g. PyTorch, Tensorflow), and are strong in one or more programming languages: Python, C, Rust, C++
• You are experienced with data taxonomies, data correlation, and recommendation engines
• Ideally, PhD in computer science/machine learning
• You have 5+ years experience in the machine learning/NLP/NLU field
• Comfortable traveling within the U.S. for quarterly team meetups and occasional in-person customer meetings or demos

What You Get

• Competitive compensation, including company equity to ensure you can share in the success of your work
• Full health benefits
• A 401k Vehicle
• Opportunity to change how Individuals, Businesses, and Governments interact with Earth data
• Fun, collaborative work environment that is hybrid (remote / onsite)
• Fast paced startup environment
• Lots of personal responsibility, opportunities for growth and learning

This very exciting opportunity to join a new company at its inception that will reward you with a ton of experience, positive collaborative team oriented culture, and significant equity stake in the company. If you value learning, developing products that have real impact on our world, and working with a positive collaborative time along the way then this is the place for you!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.