MLOps Engineer I

Overview

Position Summary:

As an MLOps Engineer I, you'll be a member of a team dedicated to productionizing machine learning models and systems, including the implementation of data science pipeline orchestration and automation. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging state-of-the-art technology platforms. You’ll serve as a major technical contributor, writing and reviewing model and application code, as well as ensuring high availability and performance of our batch, API, and streaming machine learning applications. You'll have the opportunity to continuously learn & apply the latest innovations and best practices in machine learning engineering.

Geo-Salary Information

State specific pay scales for this role are as follows:

$92,154 to $174,681  (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA)

$83,776 to $158,801 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME)

$75,399 to $142,921 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV)

The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location.

Responsibilities

Essential Job Functions:

• Develop and use modern software engineering practices to deploy ML solutions at scale, including building CI/CD pipelines and automated testing.
• Work with Data Scientists and Data Engineers to build automated pipelines that train, run and monitor ML Models for business applications in an agile and elegantly orchestrated manner
• Enhance and improve the code deployment and model monitoring frameworks and project operations documentation
• Support life cycle management of deployed ML model life cycle management (e.g. new releases, change management, monitoring and troubleshooting) 
• Support the MLOps Platform, including model registry, model deployment, and feature store.
• Knowledge of cloud-based infrastructure and demonstrated ability to architect scalable and extensible services.
• Collaborate with expert vendors and IT application teams for integrating ML models including defining SLAs and designing highly automated end-to-end testing
• Other functions may be assigned

Qualifications

Education:

• Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, Information Systems, or related technical field
• Master’s degree preferred.
• Or equivalent combination of education and/or experience

Experience:

• 2 or more years of experience in MLOps engineering, data engineering, data science, and/or software engineering
• 2 or more years experience in writing SQL
• 2 or more years experience in writing Python

Preferred: Experience in P&C insurance or broader financial services industry

• AWS Ecosystem:
• Sagemaker endpoints
• API Gateway
• ECR
• Lambda
• Experience building Docker Images
• Experience building APIs
• Flask or FastAPI
• Experience orchestration ML workflows
• Dagster / Airflow/MLflow
• Passion for CI/CD 

                    

Knowledge and Skills:

• Experience working with various stakeholders from different backgrounds
• Experience at analyzing data, systems, and processes to identify gaps and inconsistencies
• Able to multitask, prioritize, and manage time effectively
• The ability to think conceptually, analytically and creatively; comfortable with ambiguity
• Experience managing and communicating plans to peers and with internal partners
• Demonstrated solid understanding, and passion for, multiple areas of MLOps engineering best practices
• Experience in SQL programming
• Experience in Python
• Experience with cloud-based advanced data and analytics environment (e.g., AWS)
• Experience with GitHub and/or GitLab
• Proficient data skills and the ability to work with large structured and unstructured data sources
• Excellent problem-solving skills required
• Excellent analytical and critical thinking required
• Excellent written and verbal communication skills required
• Demonstrate Company’s Core Values

 

About the Company

Why choose a career at Mercury?

At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it.

Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life.

We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals.

 

Learn more about us here: https://www.mercuryinsurance.com/about/careers

Perks and Benefits

We offer many great benefits, including:

• Competitive compensation
• Flexibility to work from anywhere in the United States for most positions
• Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours)
• Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus)
• Medical, dental, vision, life, and pet insurance
• 401 (k) retirement savings plan with company match
• Engaging work environment
• Promotional opportunities
• Education assistance
• Professional and personal development opportunities
• Company recognition program
• Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more

Mercury Insurance is an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law.

Pay Range

USD $92,153.73 - USD $174,681.00 /Yr.