GEICO Logo

GEICO

Senior Staff Machine Learning Engineer

Reposted 9 Days Ago
Be an Early Applicant
In-Office
5 Locations
140K-300K Annually
Senior level
In-Office
5 Locations
140K-300K Annually
Senior level
The Senior Staff Machine Learning Engineer will lead the design and implementation of ML systems, leveraging Generative AI and guiding teams to enhance customer experiences and improve decision-making in the Claims organization.
The summary above was generated by AI

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.

#LI-JK1


 

Annual Salary

$140,000.00 - $300,000.00

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.


 

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.


 

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.

Top Skills

Airflow
C++
Cassandra
Delta
Elasticsearch
Flink
Grafana
Iceberg
Java
Kafka
Kubeflow
Mlflow
MongoDB
Opentelemetry
Parquet
Postgres
Prometheus
Python
Qdrant
Ray
Snowflake
Spark
Spark Streaming
Temporal

Similar Jobs

6 Hours Ago
In-Office
4 Locations
173K-314K Annually
Senior level
173K-314K Annually
Senior level
Cloud • Software
Design and develop scalable ML infrastructure to support training and inference, optimizing distributed systems, and maintaining operational excellence. Collaborate with various teams to enhance AI capabilities and ensure reliability and performance.
Top Skills: AirflowAWSAzureGCPKuberayKubernetesRaySparkVllm
12 Days Ago
Easy Apply
Remote or Hybrid
2 Locations
Easy Apply
160K-200K Annually
Senior level
160K-200K Annually
Senior level
Artificial Intelligence • Big Data • Computer Vision • Information Technology • Machine Learning • Analytics • Defense
As a Senior Machine Learning Engineer, you will develop machine learning models, automate data pipelines, and collaborate with teams to meet customer needs.
Top Skills: AngularC++DockerGoGraphQLJavaKubernetesPythonPyTorchReactRestRustScalaScikit-LearnTensorFlowVue
12 Days Ago
Easy Apply
In-Office
Austin, TX, USA
Easy Apply
Mid level
Mid level
Information Technology • Robotics
The Machine Learning Engineer will develop and optimize models, manage datasets, enhance training pipelines, and collaborate across teams to innovate in autonomous vehicle technology.
Top Skills: C++JaxNumpyPysparkPythonPyTorchScipySQLTensorFlow

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account