Staff Machine Learning Engineer Document Intelligence

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. Thats why we offer The GEICO Pledge: Great Company Great Culture Great Rewards and Great Careers.

Overview
As a Senior Machine Learning Engineer you will be a tech lead through design development and deployment of advanced machine learning models across the business. This role focuses on building scalable machine learning models mentoring junior engineers and driving the full lifecycle of machine learning model development. You will be the tech lead for a team of Machine Learning Engineers and/or Data Scientists focused on ensuring that machine learning models are robust high-performing and seamlessly integrated into production systems. This position involves both hands-on engineering work and leadership responsibilities in a dynamic environment.
Responsibilities:
Design and implement machine learning models & components that solve real-world business problems in close collaboration with the Product Business units & Data Science teams.
Write production-grade code for ML models as services and APIs
Collaborate with cross-functional teams including data engineering and software development to integrate machine learning models into production systems.
Build and maintain scalable data processing workflows and model deployment infrastructure.
Debug and resolve model performance issues track relevant metrics and implement continuous improvements to ensure model accuracy and reliability.
Keep up with the latest ML tooling and communities
Lead the design and implementation of complex machine learning models across various business units.
Architect and develop scalable infrastructure for automated model training hyperparameter tuning and deployment.
Mentor and guide junior engineers collaborating closely with machine learning engineers to optimize and refine models.
Own the end-to-end systems for model monitoring maintenance and retraining to ensure high availability and performance.
Minimum Qualifications
. in Machine Learning Computer Science Statistics Mathematics or related quantitative field
6 year of experience applying machine learning techniques (e.g. Ensemble learning deep learning reinforcement learning NLP etc.)
6 years of experience with SQL Spark and scripting languages like Python
6 years of experience with machine learning frameworks such as TensorFlow PyTorch and Scikit-learn.
4 years of experience working with cloud platforms and environments like AWS Microsoft Azure Databricks and Kubernetes.
4 years of experience applying machine learning techniques in a production environment for business solutions.

Required Skills & knowledge
Machine Learning Algorithms: Strong foundation in and deep understanding of advanced machine learning algorithms including supervised and unsupervised learning techniques as well as familiarity generative models.
Statistical Modeling: Proficiency in statistical modeling including probability theory & hypothesis testing to be able to interrogate analyze and interpret data effectively.
Programming Skills: Strong programming skills such as proficiency in Python and experience with machine learning frameworks such as TensorFlow Keras and PyTorch. Familiarity with software development best practices including CI/CD pipelines containerization (e.g. Docker) and orchestration (e.g. Kubernetes). Deep understanding of MLOps practices including model versioning A/B testing and continuous deployment.
Cloud Computing Platforms: A deep understanding of cloud computing platforms such as Azure AWS or GCP a deep understanding distributed systems and familiarity with large-scale data processing technologies (e.g. Spark Kafka).
Leadership: Proven experience in leading machine learning projects managing stakeholders and scaling machine learning solutions in production environments
Communication: Excellent communication skills capable of presenting complex technical topics to both technical and non-technical audiences.
Analytical: Exceptional problem-solving and analytical skills with a focus on continuous improvement and innovation.

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 candidates 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 lifes twists and turns. Our mission is to protect people when they need it most and were constantly evolving to stay ahead of their needs.

Were an iconic brand that thrives on innovation exceeding our customers expectations and enabling our collective success. From day one youll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on peoples 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. Youll 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 familys 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.