GEICO
Distinguished Engineer, AI Applications
Palo Alto, CA · Senior
Sponsorship not specified$210k-$350kDetected 2 days ago
PythonJavaAlgorithmsMongoDBElasticsearchSnowflakeAWSAzureMachine LearningSparkAirflowdbtData EngineeringStatisticsComplianceLeadershipMentoring
Stay score
odds of building a lasting career here
61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
Level I$152,7971 entry
Level II$187,0752 entries
Level III$221,3743 entries
Level IV$255,6534 entries
$11,374 more — $221,374 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $221,374 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- When you join our company, we want you to feel valued, supported, and proud to work here.
- As a Distinguished Machine Learning Engineer, you will be a senior technical leader responsible for informing the company's strategic machine learning initiatives.
- Annual Salary $210,000.00 - $350,000.00 The above annual salary range is a general guideline.
Responsibilities
- Frameworks for Interpretability & Fairness: Develop and implement frameworks for model interpretability, fairness, and explainability, ensuring compliance with ethical standards, regulatory requirements, and industry best practices.
Requirements
- Experience with data governance, security, and regulatory compliance in AI systems, including ensuring fairness, transparency, and ethical considerations in ML models.
- 10+ years of proficiency in Python, Java, or similar programming languages.
- 10+ years of experience with data orchestration workflow tools (e.g., DBT, Airflow)
- 8+ years of experience with big-data technologies (e.g., Spark, MongoDB, ElasticSearch, Snowflake, Neo4j).
Compensation
- $210,000.00 - $350,000.00 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.
- Great Rewards: Competitive pay, benefits, and flexibility to support your well-being and future.
Benefits
- Drive Innovation: Explore and integrate new machine learning techniques into the company's portfolio to drive innovation and stay at the forefront of ML technology.
- Assist in setting the vision and strategy for machine learning and AI initiatives within the organization.
- Architect ML Solutions: Lead the architecture design for the company's key machine learning initiatives, ensuring systems are highly scalable, efficient, and aligned with industry best practices.
- Model Monitoring & Maintenance: Design robust systems for monitoring and maintaining machine learning models in production, including setting up alerting mechanisms, retraining pipelines, and model governance structures.
- Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most.
- In this role, you will architect scalable machine learning systems, partner with leadership to align ML efforts with business objectives and oversee the entire lifecycle of machine learning models.
- You will lead cross-functional teams, explore cutting-edge techniques, and ensure that machine learning systems are stable, reliable, robust, interpretable, and compliant with industry standards.
- 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.
Company info
- Protecting customers through life's twists and turns with innovation and integrity.
- Great Careers: Personalized development programs, mentorship, and certification assistance.
- Great Culture: Inclusive and collaborative culture rooted in shared success.
- Great Rewards: Competitive pay, benefits, and flexibility to support your well-being and future.
- 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.
- At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
This listing is sourced directly from GEICO's careers page and normalized into a canonical job model.