Machine Learning Engineer
: Job Details :

Space is in our DNA. Orbital Sidekick (OSK) has a mission to leverage the untapped power of hyperspectral imagery (HSI) to address global environmental, health, and safety needs while helping companies reach their sustainability goals. Orbital Sidekick is establishing a space-based infrastructure of HSI sensors and analytic capabilities to enable real-time monitoring, detection, and risk management.

We're looking for a Machine Learning Engineer who will build out and design machine learning infrastructure for a team of data & remote sensing scientists, working collaboratively with the Analytics and Software teams to deliver data-driven products and solutions. If you are a smart-creative individual seeking to innovate and produce real, tangible value; take ownership of your role and position within a cutting-edge tech company; and inform the future vision of an up-and-coming San Francisco start-up, you'll fit right in.

You will contribute to a cross-functional team that is responsible for the full algorithm development process, all the way from human annotation to integration with the platform. Your role as Machine Learning Engineer means that you will be responsible for owning infrastructure for experiment tracking, model training/inference, dataset version control, and imagery annotation campaign creation and data extraction. You will work collaboratively within the company to produce high-level engineering of both the data collection and information delivery platforms.

As a Machine Learning Engineer your responsibilities will include:

• Setting up Machine Learning infrastructure including model repositories, experiment tracking, workflow orchestration (Prefect, Airflow, Dagster)
• Optimizing resources for both development and production in the cloud
• Deploying models for both batch and online inference
• Establishing model monitoring, model registries, experiment tracking, CI/CD, and continuous training
• Role will initially be focused on setting up MLOps and then grow into researching, developing, debugging, and deploying models to production using our hyperspectral data

Basic qualifications:

• 3+ years postgraduate experience as a MLEBS, MS, or PhD in Computer Science, Engineering, Physics, Mathematics or similar.
• Proficiency in Python, Pytorch, Weights and Biases, ML Flow, DVC, Ray, Dask, data science stack
• Experience with deploying and monitoring models in cloud environments (AWS)
• Ability to work independently as well as collaboratively in a startup environment
• Comfortable with rapid decision-making and taking ownership of system design
• Excellent written and oral communication skills

Standout candidates will have:

• Experience in machine learning for remote sensing data, hyperspectral data, and Geospatial data
• Familiarity with common remote sensing data types and tools, GeoTiffs, GDAL, rasterio, xarray, ENVI

Benefits of working at OSK:

• We offer competitive compensation and equity packages
• Company-sponsored 401K, as well as medical, dental, and vision insurance with 100% premiums covered by OSK for employees and 50% for dependents

$110,000 - $160,000 a yearSalary range is for California, Washington & New York City. Salary range for Colorado is $100,000-$150,000.Orbital Sidekick's compensation packages are determined based on multiple factors including business requirements, experience, and location.

ITAR Requirements: U.S. Government space technologies export/ITAR regulations apply here, applicant must be a U.S. citizen or a lawful permanent resident of the U.S., or eligible to obtain the required authorizations from the U.S. Department of State.

Orbital Sidekick is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. We are an equal opportunity employer committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, marital status, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, age, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws.

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