Machine Learning Engineer - Chevy Chase, United States - GEICO

GEICO Chevy Chase, United States

3 weeks ago

Full time

Description

If you are an ML Engineer looking to work on some of the latest and most interesting projects while utilizing the most cutting-edge technologies, then continue reading. GEICO's AI & ML Engineering team is responsible for building and enabling GEICO to build AI/ML products and services for the future. Our team is also responsible for designing, building, testing and maintaining the Machine Learning platform supporting Data Science initiatives across many groups. We are looking for a highly motivated individual with the ability to solve difficult problems, learn new technologies and push the boundaries of what is possible. A successful candidate must have excellent verbal and written communication skills. The candidate must also be able to work independently and in a team environment.

Required Qualifications

4+ years of development experience
Experience with end-to-end Machine Learning Engineering lifecycle
Experience with Cloud Platforms such as MS 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
Monitoring pipelines for issues or errors and diagnosing/resolving problems

Desired Qualifications

Master's degree in computer science or related field
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, and/or Splunk
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

Benefits:

As a full time 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 Assistance including Direct Billing and Reimbursement payment plan options
Paid Training, Licensures, and Certificates

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

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

GEICO is proud to be an equal opportunity employer. We are committed to cultivating an environment where equal employment opportunities are available to 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 celebrates diversity and believes it is critical to our success. As such, we are committed to recruit, develop and retain the most talented individuals to join our team

#LI-AP1

Annual Salary

$60, $204,500.00

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.

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