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Senior Elastic Engineer

Freddie Mac -
McLean, VA

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Job Details

Full-time
$122,000 - $184,000 a year

Qualifications

AI models
Containerization systems
Elasticsearch
Continuous Delivery (CD) implementation
Tooling
IT system monitoring
AI tools proficiency
System design
Employee relationship building
Public Cloud
Scalable systems
Programming languages
Data Architecture Design (Architecture design skills)
Machine intelligence
Outlier detection
Scalability
Machine learning (ML) fundamentals
DevOps automation
Design (software development lifecycle)
System performance monitoring

Full Job Description

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

Position Overview:

The Engineering Senior (Elastic) will be an active part of a team of about 9 Elastic Engineers providing observability services to the customers across the organization. Elastic is used for several specific cases with varying degrees of criticality. They will bring both technical expertise and coaching to junior members on the team.

Our Impact:

The Elastic team works on logging and monitoring for any operational based needs across the organization. Their work directly impacts the health and operational effectiveness of most Freddie Mac systems. They are seen as technical authorities and trusted advisors to a broad range of customers.

Your Impact:

You will drive and contribute to the development, optimization, and maintenance of our Elastic stack solutions. As the Engineering Senior (Elastic), you will implement technical solutions and collaborate across departments to ensure our systems are robust, scalable, and innovative.

Key Responsibilities:

Design and implement Elastic solutions for data ingestion, storage, application performance management, dashboards, Kibana, anomaly detection, Gen AI and analytics, ensuring high performance and scalability
Optimize Elastic stack components, including Elasticsearch, Logstash, Kibana, agents, etc.
Monitor and troubleshoot Elastic stack performance, addressing any bottlenecks or issues
Develop automated solutions for maintaining the Elastic cluster while following best practices for development, deployment, and monitoring
Stay updated on industry trends and advancements in the enterprise logging and monitoring space

Qualifications:

Bachelor’s degree in computer science, Information Technology, or related field (or equivalent experience)
5 – 7 years of hands-on experience with Elastic
Strong expertise in system design, data architecture, automation and scalability
Strong knowledge of Machine learning concepts and hands-on experience implementing Anomaly Detection ML jobs in Elastic
Strong proficiency in scripting and programming languages (e.g., Python, NodeJS, Java, etc.)
Hands-on experience with DevOps practices, CI/CD pipelines, and infrastructure automation tools.
Working experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes).
Familiarity with logging and monitoring tools integrated with Elastic.
Experience using Gen AI tools for code development

Keys to Success in this Role:

Coordinating the team for maximum efficiency
Serving as the initial technical contact for internal users and helping other junior team members to grow and succeed
Ability to build trust with coworkers and customers
Ability to display transparency is a must

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 www.BountyJobs.com 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 $122,000 - $184,000 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.

Apply Now

Refine Your Search

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Senior Elastic Engineer

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Research Engineer

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Mechanical Engineer

AI Engineer

Software Engineer, NLP/Machine Learning

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AI Engineer

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AI Engineer

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