Remote Deep Learning Engineer Jobs in Washington

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose.

When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers

GEICO is seeking a Senior Staff Machine Learning Engineer to help shape how Generative AI enhances customer and associate experiences across the enterprise. This is a hands-on technical role who will be leading the strategy, architecture, and delivery of ML systems for the Claims organization-designing predictive models, robust data/feature pipelines, and production-grade MLOps to drive measurable business outcomes.
You will work alongside engineering teams, data scientists, and product leaders to design, build, and integrate AI-powered capabilities that automate workflows, improve decision-making, and elevate user experience. You will contribute to a culture of learning, curiosity, and innovation while growing your expertise in cutting-edge AI technologies

About the role

• Staff+ individual contributor role focused on end-to-end ML: data and feature engineering, modeling, deployment, monitoring, and continuous improvement.
• Partner with Claims Operations, Product, and Engineering to deliver ML capabilities such as severity/triage predictions, claim outcome forecasting, and automation accelerators.
• GenAI (e.g., LLMs and agentic workflows) may be leveraged where it augments ML systems; strong ML depth is primary.

What you'll do

• Own 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 across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant).
• Translate business goals into measurable ML objectives and experiment plans; ensure 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 postmortems.
• 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 (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles.
• 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 to internal documentation and promote enterprise-wide ML standards.
• Where 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: ElasticSearch, Qdrant (as applicable to ML features and retrieval)
  • Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg
  • Streaming: Kafka; plus Flink/Spark Streaming experience
  • Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra)
  • Distributed compute: Spark, Ray
  • Workflow orchestration: Airflow, Temporal
• 6+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.
• 6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.

Preferred qualifications (GenAI as a plus)

• 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: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management.
• Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; 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.

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Annual Salary

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.

The GEICO Pledge:

Great Company:At GEICO, we help our customers through life's twists and turns. Our mission is to protect people when they need it most and we're constantly evolving to stay ahead of their needs.

We're an iconic brand that thrives on innovation, exceeding our customers' expectations and enabling our collective success. From day one, you'll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people's lives.

Great Careers:We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career - and your potential - in mind. You'll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.

Great Culture:We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards:We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

• 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.

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 their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.