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Remote Google Machine Learning Engineer Jobs in North Carolina

Sunergi Inc

$110K - $140K/yr

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.

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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Remote Google Machine Learning Engineer information

What is a remote Google machine learning engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

What are the key skills and qualifications needed to thrive as a remote Google machine learning engineer?

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do remote Google machine learning engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.

What are the most commonly searched types of Google Machine Learning Engineer jobs in North Carolina?

The most popular types of Google Machine Learning Engineer jobs in North Carolina are:

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For Remote Google Machine Learning Engineer jobs in North Carolina, the most frequently searched job titles are:

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The top searched job categories for Remote Google Machine Learning Engineer jobs in North Carolina are:

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Remote Google Machine Learning Engineer jobs near you

Machine Learning Engineer (Remote)

Sunergi Inc

Remote

$110K - $140K/yr

Full-time

Re-posted 11 days ago

Key responsibilities

  • Implement data pipelines focused on Machine Learning applications and develop data sets for proof of concepts.

  • Partner with cross-functional teams to define, develop, and implement data technology solutions for ML applications.

  • Take ownership of individual platform components, help set the vision and architecture, and identify requirements for new features.

Job description

Sunergi Inc.Machine Learning EngineerFull-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 missionWe 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.



Employment Type: FULL_TIME

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