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Senior Distributed Systems / ML Engineer at Loom

83% Flex
Full Remote
Full time
Mid-level (2-5 years)
146 - 235 K yearly
  • Remote from:United States
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Senior Distributed Systems / ML Engineer at Loom

83% Flex
Remote: Full Remote
Contract: Full time
Salary: 146 - 235K yearly
Experience: Mid-level (2-5 years)
Work from: United States...

Offer summary

Qualifications: Bachelor's or advanced degree in Computer Science, Engineering, or related field, 4+ years experience building and scaling cloud systems, Strong proficiency in programming languages like Java, C++, JavaScript or Python, Solid understanding of cloud platforms, containerization, Docker, Kubernetes, machine learning frameworks (e.g. TensorFlow, PyTorch).

Key responsabilities:

  • Maintain existing and develop new machine learning infrastructure pipelines
  • Monitor industry trends for infrastructure enhancement strategies
  • Preprocess data, engineer features, evaluate models, and collaborate on scalable data pipelines
  • Ensure seamless integration of machine learning models and document processes
Atlassian logo
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Atlassian
Computer Software / SaaSLarge

http://www.atlassian.com/

5001 - 10000 Employees
HQ: Sydney

Job description

Logo JobgetherYour missions

Overview

This is a remote position. To help our teams work together effectively, this role requires you to be located in the US.

Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. **

Your future team**

Loom is the video communication platform for async work that helps companies communicate better at scale. The Media & Intelligence Team lives at the heart of Loom’s product development, providing a set of libraries, services, platforms, and APIs used across our systems to power recording, playback, editing, and advanced AI features.

We are seeking an experienced systems engineer to architect, implement, and optimize ML systems and contribute to the success of AI initiatives. You will report to the Senior EM of this team and collaborate with Engineering, Product, Data, Design and UXR teams. **

Responsibilities**

  • Maintain the stability and performance of existing systems.
  • Contribute to the design and implementation of new machine learning infrastructure pipelines to help deploy modern AI applications.
  • Stay abreast of industry trends and emerging technologies to inform infrastructure development strategies.
  • Implement optimization strategies to enhance the efficiency of existing infrastructure.
  • Perform data preprocessing, feature engineering, and model evaluation.
  • Collaborate with data engineers to build scalable and efficient data pipelines for training and testing.
  • Collaborate with cross-functional teams to ensure seamless integration of machine learning models into the infrastructure and contribute to the overall success of AI initiatives.
  • Create and maintain comprehensive documentation.

Qualifications

  • Bachelor’s or advanced degree in Computer Science, Engineering, or a related field.
  • 4+ years of proven experience with building and scaling cloud systems.
  • Proficiency in programming languages such as Java, C++, JavaScript or Python.
  • Strong understanding of cloud platforms, containerization, and orchestration tools (e.g., Docker, Kubernetes).
  • Solid knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in deploying machine learning models in production environments.
  • Experience with cloud-based machine learning services (e.g. AWS SageMaker, GCP AI Platform, Azure Machine Learning Studio) is a big plus.
  • Previous experience designing and implementing machine learning pipelines.
  • Experience handling and processing large-scale datasets, including the design and optimization of data processing workflows.
  • Obsessive about deeply understanding how systems work.

Compensation

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:

Zone A: $176,200 - $234,900

Zone B: $158,600 - $211,500

Zone C: $146,300 - $195,000

This role may also be eligible for benefits, bonuses, commissions, and equity.

Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. **

Our Perks & Benefits**

Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more. **

About Atlassian**

At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

To learn more about our culture and hiring process, visit go.atlassian.com/crh .

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