What are the responsibilities and job description for the Engineer II, Machine Learning position at QTS Data Centers?
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The Machine Learning Engineer II is responsible for building, testing, and deploying ML based software applications to solve moderately complex internal and customer facing automation problems. As part of the AI & Analytics Innovation Team, this role will work together with engineers and data scientists to rapidly prototype, evaluate, and deploy solution to solve QTS’s most demanding automation challenges. The Machine Learning Engineer II will develop ML based software applications that drive operational outcomes for internal teams as well as customers. Additionally, this role will identify ML software issues and recognize/implement additional features for existing software and leverage experience with machine learning model development/deployment, data preparation, and API based system integration.
RESPONSIBILITIES, Other Duties May Be Assigned.
The "Know Your Rights" Poster is included here:
Know Your Rights (English)
Know Your Rights (Spanish)
The pay transparency policy is available here:
Pay Transparency Nondiscrimination Poster-Formatted
QTS is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to talentacquisition@qtsdatacenters.com and let us know the nature of your request and your contact information.
The Machine Learning Engineer II is responsible for building, testing, and deploying ML based software applications to solve moderately complex internal and customer facing automation problems. As part of the AI & Analytics Innovation Team, this role will work together with engineers and data scientists to rapidly prototype, evaluate, and deploy solution to solve QTS’s most demanding automation challenges. The Machine Learning Engineer II will develop ML based software applications that drive operational outcomes for internal teams as well as customers. Additionally, this role will identify ML software issues and recognize/implement additional features for existing software and leverage experience with machine learning model development/deployment, data preparation, and API based system integration.
RESPONSIBILITIES, Other Duties May Be Assigned.
- Create high-uptime, high-volume data integration systems (MM datapoints / second) to support AI / Analytics systems
- Build, test, deploy API based systems to connect data silos
- Work collaboratively as part of distributed, fast paced team
- Collaborate with the AI & Analytics team on overall system development / testing / deployment
- Develop and optimize API based integrations to support system interoperability
- Rapidly build python-based prototype systems to vet use case feasibility
- Maintain / update deployed API based systems and infrastructure
- Create unit tests for prototype systems to evaluate prototype feasibility / efficacy
- Build / maintain data aggregation services and systems
- Assist with maintaining current ML Models
- Assist with investigating and developing new ML models related to critical operations
- Assist with development and population of new database structures
- Minimum 5 years of hands-on experience in designing / prototyping / deploying production quality software systems.
- Minimum 3 years of experience developing distributed web APIs to include proficiency with gRPC and RESTful APIs.
- Demonstrated record of work ethic, team collaboration, accountability, and holding yourself and your team to higher standards
- Advanced experience with Python application development
- Experience with traditional Machine Learning model development best practices and tools
- Data analysis and Extract Transform Load (ETL) best practices
- Strong verbal / written communication skills
- Experience with Kubernetes and container orchestration for microservices based architectures
- Experience building automation systems using IOT data
- Familiarity with critical facilities and environments
- Experience with IOT based streaming protocols such as MQTT
- Experience with graph, relational, NoSQL, and time series databases
- Experience with cloud-based application development (AWS / Azure) and hybrid (on-prem / cloud) application architecture
- Excellent problem solving ability
- Ability to think outside the box and distill ideas that represent the “art of the possible” into practical, value add use cases
- Must be a capable, proven team player that both fosters and operates well within internal and external team environments.
- Able to solve problems at a tactical and functional level
- Rapidly prototype and evaluate use case ideas to vet feasibility and value
- Create high-uptime, high-volume data integration systems (MM datapoints / second) to support AI / Analytics systems
- Build, test, deploy API based systems to connect data silos
- Work collaboratively as part of distributed, fast paced team
- Ability to identify, describe and come up with solutions to identified system deficiencies
- This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending and HSA accounts; paid holidays; paid time off; paid volunteer days; employee assistance program; tuition assistance; parental leave; military leave assistance; QTS scholarship for dependents; wellness program, and other company benefits.
- This position is bonus eligible.
The "Know Your Rights" Poster is included here:
Know Your Rights (English)
Know Your Rights (Spanish)
The pay transparency policy is available here:
Pay Transparency Nondiscrimination Poster-Formatted
QTS is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to talentacquisition@qtsdatacenters.com and let us know the nature of your request and your contact information.