Senior Machine Learning Scientist/Engineer - AI Engineering (geico)

Job Description

Responsibilities:

• AI Systems: Work with Data Scientists and ML Engineers to gather requirements, architect, design, and implement a variety of AI/ML capabilities and platforms ensuring scalability, efficiency, and robustness. Leverage open-source technologies for rapid prototyping & experimentation. Be creative with design but also hands-on with practical concerns.
  • Examples of systems that we develop/enhance include Semantic search, GenAI/LLM-based virtual agent services, image/document understanding, Model orchestration, AB testing, Feature store etc.
• Service Integration: Collaborate with Data Scientists and engineering teams to ensure seamless integration and deployment of AI/ML models into production applications. Work with Product/Engineering leaders to come up with integration designs and project plans and ensure on-time releases.    
• Data Engineering: Develop and maintain efficient data pipelines that source structured and unstructured data from various locations, ensuring data availability and integrity.
• 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, architectural simplicity, scalability, extensibility, etc.
• 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 scientists for implementation. 

Minimum Qualifications

• A master’s/PhD degree in data science, Computer Science, Statistics, Mathematics, or a related field and at least 3 years of relevant work experience or a bachelor’s degree in these fields with at least 5 years of relevant work experience
• High proficiency (3+ years) in Python, Java or equivalent programming languages   
• Track record (2+ years) of key/principal contributor roles in design and implementation of production AI/ML systems, preferably customer-facing
• 2+ years’ experience working with big-data technologies/databases, e.g. Spark, Mongodb, Elastic search, Snowflake, Neo4j, etc.
• 2+ years’ experience working with cloud providers such as AWS and Azure, esp. AI/ML related capabilities such as Aure ML, AWS Sage Maker, Azure OpenAI, AWS Bedrock, etc.
• Experience with building GenAI services & platforms

Preferred Qualifications

• 3+ years’ experience training, finetuning and evaluating AI/ML models (traditional ML, Deep learning and LLMs)
• 3+ years’ experience in building, deploying, and maintaining AI-ML pipelines and API services on both CPU and GPU-based infrastructure.
• 3+ years’ experience in processing unstructured data.
• Experience in designing and building metrics dashboard and UI applications for AI/ML systems, using frameworks such as Streamlit, Dash, Shiny, etc.
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• Domain knowledge on insurance or financial service/fintech sectors.

Key Competencies

• Creativity: Able to think outside the box to find innovative solutions to complex problems.
• Intellectual Curiosity: Passionate about learning and staying updated with the latest developments in the field.
• Strategic Thinking: Can envision long-term strategies and align day-to-day activities towards achieving them.
• Decision-Making: Makes sound decisions based on data, analysis, and experience.
• Adaptability: Thrives in a fast-paced environment, adapting to changing business needs. Make bold experiments and not be afraid of some failures  
• Attention to Detail: Ensures precision and accuracy in all tasks and projects.
• Interpersonal Sensitivity: Works effectively in team settings, valuing and respecting the views and roles of others.  

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.

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:

• Premier Medical, Dental and Vision Insurance with no waiting period**
• Paid Vacation, Sick and Parental Leave
• 401(k) Plan
• Tuition Reimbursement
• Paid Training and Licensures

*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.