AWS Infrastructure Engineer Data Science - Senior
Position Overview:
Our team builds and manages the AWS infrastructure that supports Model (ML) development across the company. Our platforms run on Kubernetes and leverage AWS tooling to provide highly scalable and dynamic platform features used by data scientists daily. You will directly drive the results for the team and own components of the platform from design through deployment.
Our Impact:
Our platforms are used across all business lines for Data Science development and deployment work as well as data exploration. This team is highly visible and works directly with emerging AI and ML technologies.
Your Impact:
You will design, develop and own product solutions from start to finish. On a day-to-day basis you will interact with data scientists to identify issues and new product solutions. You will continually be researching and testing new AI/ML tools and procedures to offer to offer to the wider company.
Qualifications:
- Bachelor's degree in Computer Science, Engineering (any field), Information Technology Management, or related discipline; or equivalent experience; advanced studies/degree preferred.
- 5 years of hands-on experience managing AWS infrastructure through console and Infrastructure as Code (IaC);
- Hands-on experience with AWS SageMaker and MLOps;
- 5 years of experience working python coding;
- 5 years of experience deploying application solutions;
- 3 years of experience with code repository GIT and Bitbucket; and,
- Demonstrated knowledge of infrastructure design principles.
Keys to Success in this Role:
- Demonstrate a strong desire to learn new technologies and tools in the AI/ML space
- Quickly identify solutions to issues raised by Data Scientists
- Have a strong understanding of the varies AWS components needed to run AI/ML infrastructure
- Ability to help junior team members grow their knowledge and abilities
Current Freddie Mac employees please apply through the internal career site.
We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
A safe and secure environment is critical to Freddie Mac's business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.
CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit and register with our referral code: MAC.
Time-type:Full time
FLSA Status:Exempt
Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.
This position has an annualized market-based salary range of $127,000 - $191,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.
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