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Machine Learning Engineer (Remote)
- Durham, North Carolina, United States
- Durham, North Carolina, United States
Über
Machine Learning Engineer
Full-time
We are expanding rapidly and are seeking new, experienced and hands‑on team members who think outside of the box (and are not afraid to share their thoughts), will deliver unique ideas and like to work in a fast‑paced environment on cutting edge projects.
Our mission
We aim to map the best plots for solar panels in the United States.
The Machine Learning Engineer role is all about building, recruiting, management, internal communication and delivery — getting the product out the door, while ensuring the team is hitting their mark. Furthermore, the role will help to grow the engineering team, establish the engineering culture and remove impediments to help team members be able to provide their best.
Key Qualifications
You are a core contributor on ML projects with a focus on data ingestion, transformation and presentation for ML apps and reporting. Passionate and dedicated track record of designing and implementing scalable, performant data pipelines, data services, and data products. This is a hands‑on position, expect to write more code. Proficiency in at least one programming language (Java, Python or Scala) and a tried understanding of SQL. Previous experience of dealing with multivariate data at petabyte scale, especially in the time‑series domain. Be able to communicate collaboratively with Data Scientists and ML Software developers to understand requirements we have and deliver best in class data platform. Previous experience with statistical modeling and deep learning frameworks / libraries we use is required. Strong aptitude for learning new technologies related to Data Management and Data Science. Proven record to create and perform independently and within a fast‑paced, team‑oriented environment. Work with structured and unstructured data. Perform data cleansing, scraping unstructured data and converting into structured data. Evaluate, benchmark and improve the scalability, robustness, efficiency and performance of big data platform and applications. Experience with Kubernetes, Docker is a plus Description
In this role, handle implementing data pipelines focused on Machine Learning applications. You will develop data sets for POCs to demonstrate new insights. Several of these may lead to fully operational ML models and deploy and own the life‑cycle on in‑house and third party cloud environments. You will partner with various cross functional teams to define, develop and implement data technology solutions, with an emphasis on providing superior foundational data for ML applications. A strong understanding of distributed data systems and experience in using open source frameworks to build applications is required. A solid understanding of Deep learning platforms such as Keras, Tensor‑flow and/or PyTorch is highly desirable, as is an ability to deploy solutions based on these platforms. Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads, and working with partner teams to ensure scalability, business continuity and appropriate turnaround time is a key part of the operationalization effort. As a member of the team, you will be expected to take ownership of individual platform components and help set the vision and architecture for those. In the process, you will identify the requirements of new features, and propose design and drive the solution. A strong understanding of data governance and data privacy is expected for this role in keeping with Apple’s strong commitment to the same. Education & Experience
B.S or M.S in Computer Science, Mathematics, Statistics, Operational Research, Data Science / equivalent experience. Additional Requirements
3+ years of proven experience with Kubernetes, Docker is a plus Compensation 0.25% company equity, with vesting options up to 2%. A strong, competitive salary upon reaching a seed round of funding. In the range of $110k-$140k/ year.
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Sprachkenntnisse
- English
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