Machine Learning Engineer
Ann Arbor, MI - Remote
About SkySpecs
SkySpecs is simplifying renewable energy asset management by offering purpose-built technologies and services that help our customers deliver industry-leading productivity, efficiency, and returns. Every day we help our customers unlock the power of their data so they can make confident, informed decisions. Our team brings deep industry experience and a willingness to get our hands dirty to first understand and then solve customer problems on the ground.
SkySpecs launched the world’s first completely autonomous blade inspection product in 2016 with a custom designed drone system. Since then, SkySpecs has inspected over 90% of the wind turbines in the US and we’ve expanded globally, becoming the world leader in understanding the health of turbine blades. Identifying issues with turbine blades is only the first step. In 2019, SkySpecs launched Horizon to be a platform for SkySpecs to offer a multi-layered solution for customers that includes: data collection, wind turbine blade engineering expertise, and a place for all stakeholders to collaborate to manage and analyze massive amounts of data, spot trends, and create plans for high-cost repair campaigns. In 2021, SkySpecs acquired two companies specializing in wind turbine drivetrain monitoring and financial management, further expanding our asset management portfolio. Ultimately, this will help reduce the cost and risk of operations for the industry.
What will I be getting myself into?
SkySpecs will probably be unlike any place you’ve ever worked. The second you walk in the door (or log in, if you are remote), you will feel the high-energy environment filled with incredibly smart people solving hard problems. SkySpecs values collaboration, multidisciplinary problem solving, and a mantra of ‘under-promise, over-deliver’. SkySpecs is at a critical growth period where there are endless opportunities to make an impact.
SkySpecs is seeking a Machine Learning Engineer for the Inspection Vision team. This team works closely with relevant internal and external stakeholders to produce state-of-the-art Computer Vision algorithms using wind turbine visual data. The entire lifecycle of the built models - from research to deployment and beyond is managed within the team. The ideal candidate for this position is a team player and thrives in an agile work environment.
As a Machine Learning Engineer, you will:
- Support the design and implementation of machine learning algorithms for the analysis of image/video feeds
- Work with the Inspection Vision team to architect, build and support machine learning training and model deployment pipelines
- Build continuous monitoring and evaluation systems that analyze and track model performance metrics
- Work with the team to solidify model and data versioning process and experiment tracking
- Spend about 30% of your time developing and supporting Machine Learning models and about 70% of your time building Machine Learning infrastructure and productionalizing models
- Engage in collaborative development and peer code reviews
Requirements of the job:
- Good foundation of Machine Learning concepts
- Experience building and deploying Machine Learning models
- Experience with MLOps tools that support model versioning, experiment tracking, deployment, production monitoring etc
- Fluency in Python or other relevant programming languages
- Familiarity with software engineering tools including git, github and CI/CD
- Knowledge of deep learning frameworks such as PyTorch, Tensorflow, Keras (Pytorch preferred)
- Comfortable working in Unix-based environments
- Bachelor's degree and 3+ years' relevant research/project/Industry experience (or) Master's degree and relevant experience
Bonus points for:
- Ability to design and implement cloud-based solutions and scalable data pipelines (AWS preferred)
- Experience operationalizing large scale Machine Learning project
- Experience working on Computer Vision application
- Database and programming languages experience and data manipulation and integration skills using SQL/Postgres, GraphQL, NoSQL Databases, etc.
- Experience with container orchestration like Kubernetes / Nomad etc.
- Startup experience
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS CI/CD Computer Vision Data pipelines Deep Learning Engineering Git GitHub GraphQL Keras Kubernetes Machine Learning ML infrastructure ML models MLOps Model deployment NoSQL Pipelines PostgreSQL Python PyTorch Research SQL TensorFlow
Perks/benefits: Career development Startup environment
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