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WHOOP

Software Engineer II (MLOps)

Posted Yesterday
Easy Apply
Hybrid
Boston, MA
Mid level
Easy Apply
Hybrid
Boston, MA
Mid level
The Software Engineer II will develop and optimize ML cloud infrastructure, supporting Data Science and AI teams by building scalable ML model systems for production.
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At WHOOP, we're on a mission to unlock human performance. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.


We are looking for a talented and passionate Software Engineer II to join our MLOps team, focusing on the development and optimization of ML cloud infrastructure. In this role, you will play a critical part in supporting our Data Science and AI teams by building robust, scalable systems for the productionalization of machine learning models. Your work will be at the heart of bringing advanced ML/AI solutions into production, ensuring they are reliable, scalable, and ready to drive value across WHOOP.

RESPONSIBILITIES:

  • Design, develop, and maintain cloud-based infrastructure to support the deployment and scaling of machine learning models. Implement automated pipelines for continuous integration and continuous deployment (CI/CD) of ML models, ensuring seamless transitions from development to production environments.
  • Collaborate closely with Data Scientists and AI teams to understand model requirements and facilitate the transition from prototype to production. 
  • Develop APIs, microservices, and other components necessary to integrate ML models into existing systems, enabling real-time inference and decision-making.
  • Leverage cloud services to optimize the deployment and performance of machine learning models and associated infrastructure. Utilize services such as AWS SageMaker, Lambda, and ECS to build scalable, cost-effective solutions that support real-time ML/AI workloads.
  • Support AI teams by troubleshooting and resolving technical challenges related to model deployment and performance in production.
  • Stay up-to-date with the latest advancements in ML infrastructure, cloud computing, and AI deployment strategies. Proactively suggest and implement improvements to enhance the efficiency, reliability, and scalability of ML operations within the organization.

QUALIFICATIONS:

  • Bachelor’s Degree: A degree in Computer Science, Software Engineering, or a related field; or equivalent practical experience.
  • 2+ years of experience in software engineering, with a significant focus on building and maintaining ML infrastructure in cloud environments.
  • Familiarity with Cloud Computing concepts and design patterns.
  • Experience in writing code in a functional or object oriented programming language such as Python or Java.
  • An understanding of the steps of ML lifecycle including model training and evaluation as well as monitoring a model in production.
  • Excellent collaboration skills, with the ability to work closely with Data Scientists, AI and Software teams, and other cross-functional stakeholders.
  • A high level of curiosity to keep up with industry trends and a proven ability to find creative solutions to novel problems.

This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. 


Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.


WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility.  It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Top Skills

AI
Data Science
Machine Learning Models
Ml Cloud Infrastructure

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