GEICO is seeking an experienced Senior Engineer with a passion for building high-performance, low maintenance, zero-downtime platforms, and applications. You will help drive our insurance business transformation as we transition from a traditional IT model to a tech organization with engineering excellence as its mission, while co-creating the culture of psychological safety and continuous improvement.

We are seeking a highly motivated and skilled ML Senior Engineer within our performance, efficiency and capacity organization. This role is within the capacity management platform team, and its goal is to build a full stack platform to address the infrastructure demand, capacity and quota needs of a hybrid cloud environment. The role focusses on developing sophisticated learning models to analyze infrastructure usage data enabling predictive insights for application infrastructure management. The successful candidate would be involved in building a large language learning model (LLM) that captures the data from various sources leveraging event driven architecture offering proactive suggestions to service providers fulfilling infrastructure demands.

As a Senior Engineer - ML , you will:

· Build product definition and leverage your technical skills to drive towards the right solution

· Design, build, test and maintain machine learning models to analyze infrastructure utilization data consumed from various sources.

· Collaborate closely with other Staff and Senior Staff Engineers to ensure seamless integration of machine learning models into the larger platform.

· Utilize event driven architecture to capture and process large volumes of both structured and unstructured data.

· Implement practices for model training, validation and deployment ensuring high performance and scalability.

· Contribute to continuous improvement of our machine learning pipeline, including data preprocessing, feature engineering and model optimization.

· Solve difficult problems, learn recent technologies, and push the boundaries of what is possible

· Ability to work independently and in a team environment

· Mentor other engineers and provide guidance on machine learning best practices.

· Stay updated with the latest advancements in machine learning and AIU. Particularly in the areas of infrastructure management and incorporate relevant innovations in our platform.

Qualifications

· Proficiency in Python programming, with extensive experience in developing machine learning models using frameworks such as PyTorch,TensorFlow or similar.

· Proven ability to design, implement and deploy large-scale machine learning models in production environments.

· Experience with Cloud Platforms such as Azure, AWS, or Google Cloud

· Experience with SQL and Big Data platforms such as Databricks or Apache Spark

· Experience with DevOps principles and knowledge of CI/CD pipelines. Proficient with Azure DevOps (ADO)

· Experience with telemetry, alerts, and monitoring

· Experience with data streaming infrastructure deployment (e.g., Spark Streaming, Kafka, Azure EventHub, or Event Bridge)

· Experience with performance tuning with applications processing large amounts of data

· Experience working with Hadoop, SQL, No-SQL platforms

· Experience with various file formats such as AVRO, JSON, and PARQUET

Experience

· 5+ years of experience in machine learning engineering, with a focus on developing predictive models and analytics for infrastructure management

· 3+ years of experience with architecture and design

· 3+ years of experience with AWS, GCP, Azure, or another cloud service

· 2+ years of experience in open-source frameworks

Education

· Bachelor's degree in computer science, Information Systems, or equivalent education or work experience

 

Annual Salary

$80,000.00 - $215,000.00

The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.

 

At this time, GEICO will not sponsor a new applicant for employment authorization for this position.

 

Benefits:

As an Associate, you’ll enjoy our Total Rewards Program* to help secure your financial future and preserve your health and well-being, including:

• Premier Medical, Dental and Vision Insurance with no waiting period**
• Paid Vacation, Sick and Parental Leave
• 401(k) Plan
• Tuition Reimbursement
• Paid Training and Licensures

*Benefits may be different by location.  Benefit eligibility requirements vary and may include length of service.

**Coverage begins on the date of hire. Must enroll in New Hire Benefits within 30 days of the date of hire for coverage to take effect.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.