Posted:
10/29/2024, 5:00:00 PM
Location(s):
Texas, United States ⋅ Seattle, Washington, United States ⋅ San Francisco, California, United States ⋅ Washington, United States ⋅ Maryland, United States ⋅ California, United States ⋅ Austin, Texas, United States ⋅ New York, New York, United States ⋅ Chevy Chase, Maryland, United States ⋅ New York, United States
Experience Level(s):
Senior
Field(s):
AI & Machine Learning
GEICO is seeking an experienced senior machine learning engineer to join our AI department. In this role, you will be a key contributor in building GenAI services & systems that connect complex data ecosystems and AI/ML models to solve real-world challenges. You will be collaborating with a dynamic team of data scientists and ML engineers to build platforms that not only enhance our operational efficiencies but also set new benchmarks in industry innovation.
Responsibilities:
AI Systems & Platforms: your foremost responsibility will be platform and system building. Work with Data Scientists and ML Engineers to gather requirements, architect, design, and implement a variety of AI/ML platforms ensuring scalability, efficiency, and robustness. Leverage open-source technologies for rapid prototyping & experimentation. Be creative with design, with a laser focus towards business value creation and/or enablement.
The focus of this specific position will be GenAI platforms and capabilities including but not limited to semantic search, prompt & tooling library, workflow management & orchestration, LLM gateway, real-time/proactive response generation, etc.
System Integration: Collaborate with Product, Data Science and Engineering teams to ensure seamless integration of AIML systems with the rest of the engineering systems & channels such as IVR, CRM, Claims, Sales, Mobile on tight SLA and future-proof designs. Come up with integration designs and project plans and work towards on-time releases.
MLOPs: establish SDLC and SRE best practices to ensure stable operations of production AI systems. Lead the evaluation, procurement, and deployment of specialized AI infrastructure components such as GPU clusters and vector databases, balancing cost effectiveness, reliability, scalability, extensibility, etc.
Data Engineering: Develop and maintain data pipelines that source structured and unstructured data from various locations, ensuring data availability and integrity.
Communication: Translate complex findings into understandable insights and present them to peers, leadership, and business stakeholders.
Technical Leadership: Collaborate with cross-functional teams to ensure alignment, efficacy, and timeliness. Define project roadmaps, establish feature backlogs, and lead a small team of ML engineers for implementation.
Qualifications
Track record (4+ years) of key/principal contributor roles in designing and implementing production-grade high SLA data-intensive applications & platforms on both CPU and GPU-based infrastructures, preferably related to AIML use cases
4+ years’ experience building training, finetuning and evaluation pipelines for AI/ML models (including LLMs) and related training/inferencing infrastructure
4+ years’ experience working with a wide variety of backend data systems components such as search engine (e.g. elastic search, vectordbs), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. mysql/postgresql), ETL (spark), workflow management (e.g. Airflow), etc.
4+ years in Python, Java or equivalent programming languages
3+ years’ experience with cloud providers such as AWS, Azure and GCP
3+ years of experience building GenAI services & platforms
A master’s/PhD degree in Computer Science, Engineering, Statistics or a related field and at least 3 years of relevant work experience or a bachelor’s degree in similar fields with at least 5 years of relevant work experience
Annual Salary
$105,000.00 - $230,000.00The 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.
Benefits:
As an Associate, you’ll enjoy our Total Rewards Program* to help secure your financial future and preserve your health and well-being, including:
*Benefits may be different by location. Benefit eligibility requirements vary and may include length of service.
**Coverage begins on the date of hire. Must enroll in New Hire Benefits within 30 days of the date of hire for coverage to take effect.
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.
Website: http://www.geico.com/
Headquarter Location: Chase, Maryland, United States
Employee Count: 10001+
Year Founded: 1936
IPO Status: Private
Industries: Auto Insurance ⋅ Financial Services ⋅ Government ⋅ Insurance ⋅ Internet ⋅ Mobile