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About This Role
### Description
Franklin Electric is seeking an exceptional AI Application Developer to help shape the next generation of intelligent business solutions. This is an opportunity for a high\-caliber builder who combines strong software engineering fundamentals with practical AI and machine learning expertise to deliver modern, scalable, production\-ready solutions. The ideal candidate brings hands\-on experience in Python, React, JavaScript, C\#, SQL, and Git, along with a strong working knowledge of frameworks such as PyTorch, TensorFlow, and scikit\-learn. Experience with Azure cloud technologies, DevOps practices, CI/CD pipelines, and deploying AI\-enabled applications into production is highly valued.
You will contribute across the full solution lifecycle, from opportunity identification and technical design to application development, model implementation, testing, deployment, monitoring, and continuous improvement. This role is focused on delivering AI\-enabled applications, machine learning capabilities, and data\-driven features that create measurable business value. You will help translate promising ideas into reliable, maintainable, production\-ready solutions with a strong emphasis on quality, performance, and long\-term impact.
You will work alongside talented software developers, data and analytics partners, Business Analysts, Product Owners, and business stakeholders to build high\-quality applications and AI\-driven capabilities that solve meaningful business problems and advance enterprise innovation.
If you are energized by building modern AI\-powered solutions, thrive in a collaborative engineering environment, and want to deliver technology that drives real\-world impact, this is a compelling opportunity to do meaningful work at scale.### MOVE FORWARD WITH US
Your Responsibilities:
*Software Development*
- Designs, develops, and supports modern business applications, integrations, and AI\-enabled solutions that address high\-value operational and strategic needs.
- Builds and maintains machine learning, predictive, or generative AI capabilities where appropriate, including model training, evaluation, and production integration.
- Develops intelligent application features using modern AI techniques such as supervised learning, prompt\-driven workflows, retrieval\-augmented patterns, or other model\-assisted experiences as appropriate for the business use case.
- Completes testing and validation to ensure software and AI/ML components are accurate, reliable, secure, maintainable, and ready for production use.
- Documents application, integration, and model behavior from a technical perspective, including assumptions, limitations, and operational considerations where needed.
- Partners with stakeholders to identify opportunities for automation, analytics, and AI adoption that create measurable business value and long\-term advantage.
- Supports deployment, monitoring, troubleshooting, and continuous improvement of intelligent solutions in collaboration with technical teams and business owners.
- Follows established standards for application development, responsible AI, model governance, and quality practices, and contributes input toward improving those standards over time.
- Occasionally provides off\-hours support on evenings and weekends and participates in on\-call responsibilities as needed.
*Request and Change Management** Ensure all changes and requests are entered into ServiceNow
- Ensures the fulfillment of end user requests for custom applications and integrations
- Ensure changes are completed with proper documentation
- Reviews the forward schedule of changes for potential conflicts
*Project Management** Participates as a resource on project led by others.
- Completes assigned project tasks on time and with high quality.
- May lead small projects related to custom applications and integrations.
Who We Want:
- Dedicated achievers. People who thrive in a fast\-paced environment and will stop at nothing to ensure a project is complete and meets regulations and expectations.
- Collaborative partners. People who build and leverage cross\-functional relationships to bring together ideas, information, use cases, and industry analyses to develop best practices.
- Effective communicators. People who can interpret information clearly and accurately to concisely communicate results and recommendations to stakeholders.
What You Need:
- Bachelor’s degree in computer science, software engineering, data science, artificial intelligence, computer information systems, or a related discipline is preferred; equivalent practical experience with modern software and AI development will also be considered.
- 0\-2 years of related experience in software development, AI/ML solution development, data\-driven application development, or similar technical work is required.
- Experience with machine learning concepts such as supervised learning, feature engineering, model evaluation, model deployment, or generative AI application development is preferred.
### COMPANY VALUES \& BENEFITS
FE provides many opportunities to learn and grow through development opportunities such as training, certifications, mentorship, leadership programs, tuition reimbursement, one\-on\-one coaching and more! We offer competitive salaries, comprehensive benefits, and amenities such as:* Hybrid remote work arrangements
- Generous paid time off \& holidays
- Paid parental leave \& on\-site motherhood rooms
- On site café \& complimentary beverage stations
- Indoor fitness facility \& outdoor walking paths
- 401(k) with matching \& service contributions
- Health, dental, vision, life insurance
- Short \& long\-term disability
- Fertility \& adoption support
- Undergraduate \& graduate tuition reimbursement
- Professional development assistance
- Health \& wellness programs
### Why Work at Franklin Electric?
Becoming a part of the Franklin Electric team not only provides outstanding benefits, it also opens doors to opportunities for future growth. Enjoy peace of mind with a world\-class company. But more importantly, be satisfied in knowing you make a difference.
Take a look at this video to see our Global Headquarters here in Fort Wayne, Indiana.### About Franklin Electric
Franklin Electric is a global leader in water and energy systems, committed to continuous improvement and innovation to meet the diverse needs of our customers. Our founders in 1944 named the company after America’s pioneer electrical engineer, Benjamin Franklin, which lives on today in our culture to drive us to push boundaries and create meaningful change. We offer a comprehensive range of pumps, motors, drives, and controls for residential, commercial, agricultural, industrial, and municipal applications.
More than just a workplace, Franklin Electric is a vibrant and inclusive community of forward\-thinkers, united by our mission to drive positive impact worldwide. Our culture fosters career growth and personal development, with a focus on promoting from within and nurturing talent. Our recent awards in “America's Most Responsible Companies”, “Most Trusted Companies” by Newsweek, “America’s Climate Leaders” and “Indiana’s Best Places to Work” attest, we're dedicated to upholding the highest standards of corporate responsibility.
At Franklin Electric, we believe that everyone deserves to be treated fairly and respectfully, and that our diversity of thought, culture and experience makes us a stronger company. Our commitment to social responsibility is evident in programs like the Franklin Women's Network and our philanthropic efforts through the Franklin Wells for the World Foundation. Through these endeavors, we've provided clean water to over 284,000 people in 12 countries, addressing the global water crisis head\-on,
Locally in our communities, the Franklin Electric Charitable and Educational Foundation (FECEF) supports causes close to our hearts, such as United Way, Boys \& Girls Club, and Big Brothers Big Sisters. Our dedication to excellence extends beyond our products and services, shaping a brighter future for both our employees and the communities we serve. Join us in driving meaningful change and making a difference with Franklin Electric.
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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Franklin Electric, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Franklin Electric AI Hiring
Franklin Electric has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Fort Wayne, IN, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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