Software Engineer Machine Learning

About the position

GEICO AI platform and Infrastructure team is looking for a Software Engineer responsible for designing, building, and maintaining Machine Learning platform to support data science modelling initiatives. This responsibility is exciting and opens the opportunity to support Machine Learning Development Lifecycle (MDLC) at GEICO. We are looking for a highly motivated individual with the ability to collaborate with cross-functional teams to ensure seamless integration of various inter-related systems and hybrid (on-prem and/or cloud) technologies. The candidate must have excellent verbal and written communication skills with a proven ability to work independently and in a team environment.

Responsibilities

• Scope, design, and build systems with high scalability, reliability, and resilience
• Support platform initiatives geared toward model deployment, serving, inferencing, and/or monitoring solutions
• Research and implement variety of cloud and/or open-source tools and services across the Model development life cycle ranging from IaC (Infrastructure as code) to self-hosted infrastructure implementation.
• Engage with partner teams to debug production issues, pipeline failures, and system latencies
• Engage in cross-functional collaboration with teams of developers, data scientists, product managers, network and security, and other areas throughout the entire MDLC lifecycle
• Lead in design sessions and code reviews with peers
• Collaborate with Engineering teammates to deploy models into production
• Collaborate with regulatory team to develop intended use and regulatory strategy
• Participate in product discussions and roadmap exercises to understand business use cases
• Author technical documentation and reports to communicate process and results

Requirements

• Proficiency in Python for data processing, automation, and ML workflows
• Strong SQL skills for data querying, manipulation, and pipeline development
• Hands-on experience with MLOps platforms
• Experience with machine learning model serving frameworks and machine learning platforms such as Jupyter notebooks, MLFlow, Azure Machine Learning, Large Language Model serving and optimizations etc.
• Experience with MLOps practices such as model versioning, model monitoring, and model governance
• Docker for containerization
• Experience with Azure ML, AWS SageMaker, or Google Cloud AI Platform
• Proficiency with Git for version control
• Experience with GitHub Actions or similar CI/CD tools
• Understanding of automated testing and deployment processes

Nice-to-haves

• Experience with Kubernetes for container orchestration
• Familiarity with infrastructure as code tools (Terraform, CloudFormation)
• Knowledge of data workflow orchestration tools (Airflow, Prefect, Argo)
• Experience with monitoring and observability tools (Prometheus, Grafana)
• Understanding of machine learning frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with stream processing technologies (Kafka, Kinesis)
• Knowledge of data security and compliance requirements
• Working knowledge of networking concepts (DNS/DHCP/Firewalls/Sub-netting, etc.)
• Knowledge of Big Data platforms such as Snowflake, ADLS, Databricks, Cosmos DB
• Knowledge of Big Data processing frameworks and languages such as Spark, Scala
• Experience with at least one IaC (Infrastructure as code) provider, preferably Terraform
• Experience with implementing monitoring and alerting systems to ensure performance and reliability of deployed models
• Experience with infrastructure optimization for cost efficiency, scalability, and reliability
• Knowledge of microservice architecture and distributed systems
• Experience performing Root Cause Analysis (RCA) for application and infrastructure related issues

Benefits

• Opportunity to work on cutting-edge ML infrastructure and tools
• Mentorship from senior engineers and data scientists
• Professional development budget for conferences, courses, and certifications
• Collaborative environment with cross-functional ML teams
• Competitive salary and benefits package
• Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family's overall well-being.
• Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
• Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
• Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.