About 44moles
We are a startup building the next-generation of products to digitalize the forestry sector. Our mission is to revolutionize how forests are measured and managed. We combine the latest LiDAR technology with intelligent data processing to deliver forest inventories that are faster, more complete, and accurate - empowering landowners with the data for improved forest and land management.
Your mission
We're seeking a passionate Machine Learning Engineer to join our data team, and help us build our product to power forest intelligence through LiDAR.
* Shape the way forests are measured : Develop and deploy machine learning models for our core software algorithms, enabling us to accurately measure and process forestry data across diverse ecosystems and at scale.
* Take ownership and build a transformative product: Work in a product-focused way to ensure our deliverables align closely with user needs. Design new features and algorithms, prototype fast, and take responsibility for integrating and maintaining solutions in production. We trust you to shepherd your work from concept through to feature release.
* Work across teams → Partner closely with our development team to ensure seamless integration of models and outputs into our product offering.
* Ensure quality → Validate model outputs and conduct thorough quality assurance to ensure our calculated metrics and measurements meet the highest standards - because landowners depend on our accuracy for critical decisions.
Your Responsibilities
* Contribute to our core ML framework : Design and implement machine learning using Python, leveraging data technologies such as Airflow, Kafka, and the AWS cloud environment. Design and enhance our suite of ML models for tree species detection and instance segmentation.
* Optimize algorithmic efficiency: Improve throughput and compute for pipeline performance with respect to function implementations for 3D point cloud and geospatial data. Work on efficient data representations and schemas for high-volume 3D data.
* Keep updated with research and prototype solutions to test them for integration into our software solutions. Implement scientific papers and methods.
* Validation Benchmarks: Validate and test ML models. Develop benchmark datasets and model validation tools.
* Collaboration: Collaborate with senior scientists on environmental research
Your Profile
We are looking for candidates with a strong technical background who thrive in fast-paced environments (e.g. high-growth startups, or rapid scale-ups).
* 2-4 years of professional experience in Data Science or Software Engineering and a Masters degree in STEM (Computer Science, Data Science, Engineering).
* You bring a strong background in Machine Learning engineering, with proven experience developing, testing, and maintaining models in containerized production environments (e.g., Docker, AWS). You have a strong understanding of core algorithms, data structures, and model performance evaluation.
* Proficiency in SQL and data loading pipelines to support efficient data ingestion for ML and processing pipelines.
* High-Paced Experience: You have survived and thrived in fast-paced environments where requirements change daily. You don't need hand-holding.
* Strong Python knowledge including experience with ML frameworks (PyTorch/TensorFlow) and tools (Weights and Biases / MLflow) commonly used in the ML ecosystem.
* Broad (Software) Engineering skills with the ability to reason and structure analyses. Write clean, documented code. Experience with Git.
* Comfortable working in an agile environment, contributing to iterative development cycles and cross-functional teams.
* Experience with MLOps tools and practices (e.g., Docker, SageMaker, CI/CD pipelines) → bonus ⭐
* Knowledge of geospatial data processing and experience with point cloud processing (PCL, Open3D) → bonus ⭐
What we offer
* Work in a emerging, scientific domain with visible impact
* Direct influence on product and research direction
* Competitive salary
* 28 days of vacation
* State-of-the-art office spaces
* A vibrant, inclusive, and cooperative international team
More Information
We offer a hybrid work option for this role. To help you get off to a great start and settle into the team, we would like you to spend the first three months (or longer, depending on requirements) primarily working from the office.
We kindly request that you do not send applications by any means other than via our website as we cannot guarantee that we will be able to process applications that are not made via our website.