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About This Role
Description
INTERNSHIP OPPORTUNITY: We are seeking two skilled and motivated Unmanned Aircraft Systems (UAS) Remote Pilots to lead aerial operations using large\-scale UAS and sUAS drones for agricultural applications, including crop spraying, mapping, and imagery collection. This is a hands\-on, field\-based internship out of our Daytona Beach, FL location. Your primary responsibility will be the safe, efficient, and effective flight testing of advanced drone systems in support of aircraft production from Central UAS Technologies manufacturing. You will build strong relationships with both our software and hardware engineering teams.
Central UAS Technologies, a vertical of Central Life Sciences, is dedicated to the creation of uncrewed aerial systems which have a direct positive impact on agriculture, forestry, noxious weed and public health. Our parent company is Central Garden \& Pet (NASDAQ: CENT and CENTA). Please visit our websites at www.centraluastech.com; www.centrallifesciences.com; www.central.com
KEY RESPONSIBILITIES
As a Remote Pilot in Command (RPIC) test pilot, you will be responsible for all tasks associated with performing UAS Missions/Flights \- such as:* Primary focus on flight testing production units
- Working with software and hardware engineers to perform flight tests on new feature releases
- Provide regression testing on new software releases
- Maintain detailed notes and reporting on software “bugs”
- Coordinate flight testing with R\&D team
- When available, provide application services assistance for contract application services
- Provide Visual Observer services to other RPICs
- Loading UAS with water/payload for flight testing
- Understand and provide manufacturing assembly when available, building large scale UAS from documented processes
- Diagnose, repair, and test UAS that are received for service
- Field work to support UAS application operations
QUALIFICATIONS* FAA CFR Part 107 UAS pilot certificate
- Drone piloting proficiencies with 50\-100 hours of experience in verifiable flight time \- fixed wing, rotor, or multirotor
- Ability to operate and handle a truck and trailer
- A valid U.S. state Driver’s License
- Be able to attain the required aerial applicator license and any other license required by Federal and State of Florida legislation
MINIMUM EXPERIENCE \& EDUCATION* 3\+ years of related experience
- Prior experience operating sUAS
- Knowledge of Geographic Information Systems (GIS) such as QGIS
- Be able to lift 100 pounds with teammate assistance
WORK ENVIRONMENT* This position is based primarily outside in all types of weather and uneven terrain
- Applicants must be able to work around and safely handle pesticides according to product labeling
- Physical requirements: Standing, sitting, walking and climbing on unlevel or grassy terrain, reaching. Must be able to lift up to 100 lbs. on a frequent basis with co\-worker assistance
- Knowledge of Microsoft Suite applications and software
- Strong teamworking skills through collaborative problem solving
Central Garden \& Pet Company (NASDAQ: CENT) (NASDAQ: CENTA) understands that home is central to life and has proudly nurtured happy and healthy homes for over 40 years. With fiscal 2024 net sales of $3\.2 billion, Central is on a mission to lead the future of the Pet and Garden industries. The Company’s innovative and trusted products are dedicated to helping lawns grow greener, gardens bloom bigger, pets live healthier and communities grow stronger. Central is home to a leading portfolio of more than 65 high\-quality brands including Amdro®, Aqueon®, Cadet®, Farnam®, Ferry\-Morse®, Four Paws®, Kaytee®, K\&H®, Nylabone® and Pennington®, strong manufacturing and distribution capabilities and a passionate, entrepreneurial growth culture. Central is based in Walnut Creek, California and has 6,400 employees across North America and Europe. Visit www.central.com to learn more.
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation, gender identity, or any other characteristic protected by law.
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 Central Garden & Pet, 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.
Central Garden & Pet AI Hiring
Central Garden & Pet has 11 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Township of Monroe, NJ, US, Neptune City, NJ, US, Covington, GA, US. Compensation range: $35K - $83K.
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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