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Senior Machine Learning Engineer

Remote / Online - Candidates ideally in
Chevy Chase, Montgomery County, Maryland, 20815, USA
Listing for: Government Employees Insurance Company
Remote/Work from Home position
Listed on 2026-05-30
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Senior Staff Machine Learning Engineer

Job Summary

GEICO seeks a Senior Staff Machine Learning Engineer to lead the strategy, architecture, and delivery of ML systems for the Claims organization. This hands‑on role focuses on end‑to‑end machine learning—from data and feature engineering to model deployment and continuous improvement—to automate workflows, improve decision‑making, and elevate user experience.

Key Responsibilities
  • Own the ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability.
  • Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services.
  • Lead design and implementation of models (classical & deep learning) such as gradient‑boosted trees, sequence models, and Transformers for tabular, time‑series, and NLP tasks where relevant.
  • Translate business goals into measurable ML objectives, experiment plans, robust offline metrics, and real‑world impact.
  • Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies.
  • Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and post‑mortems.
  • Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs.
  • Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence; own build‑vs‑buy decisions and tooling/service selection.
  • Lead experienced engineers through complex platform implementations; drive system‑wide architectural improvements and reliability practices.
  • Mentor engineers and junior tech leads; codify best practices; contribute internal documentation and promote enterprise‑wide ML standards.
  • When appropriate, collaborate on retrieval‑augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems.
Minimum Qualifications
  • Bachelor’s degree or above in Computer Science, Engineering, Statistics, or related field.
  • 10+ years of professional software development experience using at least two general‑purpose languages (e.g., Java, C++, Python, C#).
  • 10+ years architecting, designing, and building multi‑component ML platforms leveraging open‑source/cloud‑agnostic components:
    Search/vector (Elastic Search, Qdrant), Snowflake, Parquet/Delta/Iceberg, Kafka, Flink/Spark, Postgre

    SQL, Mongo

    DB, Cassandra, Spark, Ray, Airflow, Temporal.
  • 6+ years managing end‑to‑end SDLC for ML systems: version control, CI/CD, Kubernetes, testing, monitoring, alerting, production support.
  • 6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.
Preferred Qualifications
  • Experience leveraging or fine‑tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims‑facing tooling.
  • Hands‑on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing, and online evaluation frameworks.
  • Observability with Prometheus/Grafana, Open Telemetry; SLO‑driven operations and incident management.
  • Model safety, fairness, and explainability (e.g., SHAP/LIME); familiarity with model risk management practices.
  • Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship.
  • Experience with high‑throughput, low‑latency inference and real‑time feature pipelines.
Compensation

Annual salary range: $ – $ (subject to scope, experience, education, location, and market considerations).

Benefits
  • Competitive Total Rewards program including medical, dental, vision, and other covered benefits.
  • 401(k) plan with company match up to 6%.
  • Performance and recognition‑based incentives.
  • Tuition assistance and certification assistance.
  • Support for mental health, fertility, and adoption assistance.
  • Flexible work options and GEICO Flex program (work from anywhere in the US for up to four weeks per year).
EEO Statement

GEICO is an equal opportunity employer. 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 qualifications for the job to be filled.

Job

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Position Requirements
10+ Years work experience
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