Senior Machine Learning Engineer

GEICO is seeking an experienced Senior Engineer with a passion for building high performance, low-latency platforms, and applications.

You will help drive our insurance business transformation as we redefine experiences for our customers.

Our Senior Engineer is a key member of the engineering staff working across the organization to provide a friction-less experience to our customers and maintain the highest standards of protection and availability.

Our team thrives and succeeds in delivering high quality technology products and services in a hyper-growth environment where priorities shift quickly.

The ideal candidate has broad and deep technical knowledge, typically ranging from front-end UIs through back-end systems and all points in between.

Position Responsibilities

As a Senior Engineer , you will :

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

Design, build, test and maintain the Machine Learning platform supporting Data Science initiatives

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

Work independently and in a team environment

Scope, design, and build scalable, resilient distributed systems

Engage in cross-functional collaboration throughout the entire software lifecycle

Participate in design sessions and code reviews with peers to elevate the quality of engineering across the organization

Consistently share best practices and improve processes within and across teams

Mentor other engineers

Qualifications

Experience with end-to-end Machine Learning Engineering lifecycle

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

Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML

Experience with Big Data platforms such as Databricks or Apache Spark

Experience writing Production quality code in Scala, PySpark, Python and / or Java

Experience with SQL

Experience with the Azure Ecosystem (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Machine Learning (AML), Azure Cognitive Services, Azure Storage)

Experience with CI / CD pipelines

Experience with Azure DevOps (ADO)

Experience developing ADO tasks, variable groups, and pipelines

Experience with telemetry, alerts, and monitoring

Experience with Azure Monitor, AppInsights, Dynatrace, Splunk or equivalents

Knowledge of Kubernetes or Azure Kubernetes Service (AKS)

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

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 with Load Testing and Quality Assurance

Experience

4+ years of experience developing machine learning solutions

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

$66,000.00 - $185,000.00

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

• 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.