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The role involves developing and optimizing ML cloud infrastructure, ensuring scalable deployment of machine learning models, and collaborating with data science teams.
At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.
We are looking for a highly skilled Senior Software Engineer 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 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.
- Monitor and optimize the performance of ML models in production, addressing issues related to latency, scalability, and resource utilization.
- Act as a key technical partner to Data Scientists, providing guidance on best practices for model deployment, versioning, and infrastructure design.
- 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.
- 5+ years of experience in software engineering, with a significant focus on building and maintaining ML infrastructure in cloud environments.
- Deep expertise in AWS services, including but not limited to SageMaker, Lambda, ECS, S3, and IAM, with the ability to design and optimize cloud-based ML infrastructure.
- Strong programming skills in languages such as Python or Java, with a focus on building robust, maintainable code.
- Proven experience in productionalizing ML models, including building APIs and services that enable real-time inference.
- Expertise in designing scalable, resilient cloud architectures that support large-scale ML operations.Strong understanding of microservices, distributed systems, and the challenges of deploying and maintaining ML models in production environments.
- Excellent collaboration skills, with the ability to work closely with Data Scientists, AI and Software teams, and other cross-functional stakeholders.
- Agile Methodologies: Experience working in Agile/Scrum environments, with a focus on rapid iteration and continuous improvement.
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.
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $150,000-$210,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.
Learn more about WHOOP.
Top Skills
Aws Ecs
Aws Lambda
Aws S3
Aws Sagemaker
Java
Python
WHOOP Boston, Massachusetts, USA Office
1 Kenmore Sq, Boston, MA, United States, 02215
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