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Senior Software Engineer

2 months ago

Chevy Chase, Maryland, United States GEICO Full time
About the Role

GEICO is seeking an experienced Senior Software Engineer to join our team as a Platform Architect - Data Science. As a key member of our capacity management platform team, you will be responsible for designing and implementing high-performance, low-maintenance platforms and applications that drive our insurance business transformation.

Key Responsibilities
  • Provide technical leadership and expertise in the design and implementation of platform development and event-driven microservices.
  • Work closely with product leaders, engineers, and partner teams to understand product requirements, build a technical backlog, and develop solutions that align with product vision.
  • Architect and develop learning models and their services using Python, Kafka, and related open ML frameworks like TensorFlow and Keras.
  • Define and drive data capture and storage mechanisms using event-driven architecture to gather infrastructure utilization data from various sources and ensure the data is fed into the learning model environment.
  • Own and drive one to two machine learning service areas, being accountable for their successful delivery, from design through to production, and ensuring they meet performance, scalability, and reliability standards.
  • Act as a role model and mentor to senior and junior ML engineers, guiding them in understanding the architecture, design, and implementation of systems.
  • Maintain excellent communication with partner teams and leads, articulating technical implementations for various stakeholders, ensuring alignment across teams.
  • Proactively explore unknown product requirements and design solutions that meet evolving needs, contributing to the continuous improvement of our platform.
Requirements
  • Deep knowledge of machine learning techniques, particularly in natural language processing (NLP) and predictive modeling with hands-on experience in building, training, and deploying language learning models.
  • Experience working with machine learning frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks and ability to implement and optimize complex models in these environments.
  • Experience working with machine learning, ranking infrastructures, and system design.
  • Experience with large-scale data processing. Proven ability to handle and process large volumes of data and ability to utilize big data frameworks and tools such as Apache Spark, Hadoop, or Kafka for real-time data ingestion and processing.
  • Strong programming skills in Python with experience using libraries like NumPy, Pandas, and TensorFlow or PyTorch for machine learning and data manipulation.
  • Understand open-source databases like MySQL, PostgreSQL, etc., familiar with No-SQL databases like Cassandra, MongoDB, Elasticsearch, etc.
  • Strong understanding of web service integration (REST/SOAP) and enterprise middleware integration tiers.
  • Experience with continuous delivery (CI/CD) and Infrastructure as Code. Knowledge of MLOps practices including the automation of machine learning workflows, build pipelines, and model monitoring in production.
  • Strong background in data engineering, including experience with ETL pipelines, data lakes, and data warehouses, to ensure the seamless flow of data into ML models.
  • Background in using and contributing to open-source machine learning and data processing tools, promoting best practices and innovations within the team.
  • Excellent communication skills - needs to be able to lead projects from the front and interact with clients and sponsors on a regular basis.
  • Experience partnering with engineering teams and transferring research to production.
  • In-depth knowledge of CS data structures and algorithms.
  • Experience solving analytical problems with quantitative approaches.
  • Ability to excel in a fast-paced, startup-like environment.
  • Willing to work on both fast development and operation environment.
Qualifications
  • 6+ years of professional experience in software development focusing on machine learning, platform architecture, data science, pipeline development, and maintenance of big data platforms, software, and network systems.
  • 4+ years of experience in using open-source frameworks.
  • 3+ years of experience with architecture and design.
  • 3+ years of experience with AWS, GCP, Azure, or hybrid data center.
Education
  • Bachelor's degree in computer science, Information Systems, or equivalent education or work experience.