Who we are
SnoFox Sciences provides energy efficiency and predictive maintenance solutions to cold chain logistics providers. A VC-backed startup at the intersection of thermodynamics, data science, and mechanical engineering, SnoFox Sciences is revolutionizing the global cold chain through physics-based analytics.
The stakes couldn't be higher: the refrigeration sector is responsible for ~17% of global energy consumption. The UN estimates that demand on the food supply chain will increase by 70% in the coming years, and this year 80 billion pounds of food was wasted in the US alone – 30% of which is attributed to cold chain failure. Tragically, 50% of the world's vaccine supply goes to waste every year resulting in 1.5 million child deaths per year from vaccine-preventable illnesses.
What we're looking for
We are looking for a strong engineer who is excited to build out the platform and tools to enable our team to ship great products: spinning-up and managing infrastructure, deploying developer tools, improving our Mechanical Engineering team’s workflow, learning about thermodynamics and cooling systems, and helping set direction for the company. You will be joining as an early member of the team that will shape everything that comes next at SnoFox. Your past experience should demonstrate a track record of building platforms that underly powerful, data-heavy applications.
What you’ll do
Build out the platform to support our state of the art cold-chain analytics, visualization, and machine-learning platform
Create tools to help our Mechanical Engineering team integrate diverse sensor data with advanced physical models and enable customers to spot problems before they occur
Help design our tech stack and deploy tools to streamline our team’s development practices
Collaborate with our founders to help set the direction of the product
Balance speed and quality, with a focus on tangible results
4+ years experience as a software engineer
Expertise in building and managing containerized applications (Docker/Kubernetes) and cloud hosting (AWS/GCP/Azure)
Experience deploying unit testing, integration testing, and continuous integration/continuous deployment (CI/CD) pipelines
Experience in extraction and manipulation of large data sets using standard tools such as Python, R, SQL, ELK Stack
Skills in machine learning (scikit-learn, PyTorch, Keras, Tensorflow), data science, forecasting, statistics, mechanical/process engineering, modeling and optimization
Experience building data pipelines using tools like AWS SQS, AWS Code Steps, Airflow
Experience at an early stage startup (<10 person engineering team)
Salary and Benefits
Salary range: $160,000 – 180,000, dependent on experience
Eligibility for equity under the company’s employee incentive plan
Health insurance with 80% of premium covered for employees and dependents
Unlimited vacation / sick leave
Annual company retreat