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About This Role
We are Farmers – where ambition meets opportunity.
At Farmers, we’re not just known for unforgettable jingle – we’re a team with a passion for purpose and making a real difference in people’s lives. We deliver peace of mind when it matters most. Our results\-driven, high\-performance culture thrives on creativity, accountability and bold solutions. Here, growth isn’t just a goal – it’s a way of life for both the organization and every individual on our team. We tackle challenges head\-on, learn from every experience and measure our impact on the customers who trust us.
Join an award\-winning, equal opportunity employer, where you’ll find more than a job – you’ll find a supportive community. Enjoy competitive benefits, take part in meaningful volunteer projects, and help shape the future alongside talented colleagues across all backgrounds. At Farmers, helping others is at the heart of what we do.
Ready to make your mark? Discover our vibrant culture and explore career opportunities at www.Farmers.com/careers/corporate. Connect with us on Instagram, LinkedIn and TikTok, and let’s build something incredible together!
Workplace: Hybrid ( \#LI\-Hybrid )
Farmers believes in a culture of collaboration, creativity, and innovation, which thrives when we have the ability to work flexibly in a virtual setting as well as the opportunity to be together in person. Our hybrid work environment combines the best of both worlds with at least three (3\) days in office and up to two (2\) days virtual for employees who live within fifty (50\) miles of a Farmers corporate office. Applicants beyond fifty (50\) miles may still be considered.
Job Summary
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- Through the use of statistical modeling, data mining, and other best practices, the Marketing Analytics Specialist will provide quantitative analysis of marketing campaigns and initiatives. By leveraging a broad analytical skillset, the analyst helps to report Marketing results to the business.
- Email and Landing Page Development. Collaborate with Design Team to develop targeted, responsive email campaigns within Salesforce Marketing Cloud platform or/and various email platforms, using coding language like AMPScript, HTML and CSS to create email templates and dynamic content which is visually appealing, brand appropriate and ensuring cross\-browser and email client compatibility and deliverability.
- This role will collaborate closely with business until teams to transform campaign objectives into technical email solutions and monitor performance metrics to optimize email strategies.
- Campaign Automation, API Integrations \& Customizations: Creation of automated Journeys using tools like Journey Builder and Automation Studio. Configure triggers, personalize experiences and integrate with external systems (Salesforce CRM, external databases or other marketing tools). Build custom integrations to streamline data exchange and automate workflows.
Essential Job Functions
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- Maintain and develop appropriate analysis and statistical models for marketing evaluation.
- Maintain and create performance reports to guide continuous improvement on direct mail and digital performance digital campaigns.
- Ensure consistent testing and analysis with proper test design on performance marketing campaigns (i.e. direct/digital marketing).
- Performs queries and stored procedures against databases, DB2, SQL Server and MS Access.
- Delivers ad\-hoc data requests Understand internal clients' objectives (direct marketing and performance digital), processes, and products in order to make educated recommendations on changes to campaign approaches.
- Perform data mining/exploration of internal and external data sources to be used in statistical modeling Maintain project tracker for communication with clients
Education Requirements
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- High school diploma or equivalent required.
- Bachelor’s degree preferred in marketing, business, statistics, or related field, or equivalent combination of education and experience.
Experience Requirements
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- Minimum 2 years experience developing reports and analyzing information for presentation Professional Statistical/mathematical modeling experience preferred
Special Skill Requirement
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- Experience with Salesforce Marketing Cloud using Email Studio and proficient in AMPScript required. HTML and CSS proficiency preferred. Proficiency in SQL preferred.
- API integration, Journey Builder, Automation Studio, Distributed Marketing and Marketing Cloud Connect familiarity preferred.
Benefits
- Farmers offers a competitive salary commensurate with experience, qualifications and location.
- Bonus Opportunity (based on Company and Individual Performance)
- 401(k)
- Medical
- Dental
- Vision
- Health Savings and Flexible Spending Accounts
- Life Insurance
- Paid Time Off
- Paid Parental Leave
- Tuition Assistance
Job Location(s): US \- AZ \- Phoenix, US \- MI \- Grand Rapids
Anticipated application deadline: At Farmers, the recruitment process is designed to ensure that we find the best talent to join our team. As part of this process, we typically close open positions within 8 to 21 days after posting. If you are interested in any of our open positions, we encourage you to submit your application promptly.
Farmers will consider for employment all qualified applicants, including those with criminal histories, in accordance with the Los Angeles Fair Chance Initiative for Hiring Ordinance or other applicable law. Pursuant to 18 U.S.C. Section 1033, Farmers is prohibited from employing any individual who has been convicted of any criminal felony involving dishonesty or a breach of trust without prior written consent from the state Department of Insurance.
*It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.*
*Farmers is an Equal Opportunity Employer and does not discriminate in any employer/employee relations based on race, color, religion, gender, sexual orientation, gender expression, genetic information, national origin, age, disability, marital status, military and veteran's status, or any other basis protected by applicable discrimination laws.*
Spokane, WA only: Residents who prefer not to provide their address click here to submit your resume via email: careers@farmers.com
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Farmers Insurance Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Farmers Insurance Group AI Hiring
Farmers Insurance Group has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Bangor, ME, US, Phoenix, AZ, US, Remote, US. Compensation range: $137K - $249K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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