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About This Role
JOB
The Farmers Branch Fire Department is excited to announce we will be opening a promotional process for the rank of Fire Captain. The promotional process for Fire Captain will include the following (subject to change): NeoGov application period opensNeoGov application period closesOfficer Review PanelWritten ExaminationAssessment CenterRequired attachments, must be attached to your application to be considered for the position: ResumeRequired CertificationsCollege Transcript(s)Please refer to the Fire Department memorandum regarding the Promotional Process for additional details.The purpose of this position is to provide supervision of fire personnel, maintain the station and assigned apparatus under their command, and to safely coordinate fire and emergency medical service delivery at the scene of emergencies.
EXAMPLE OF DUTIES
A Fire Captain shall be in\-charge of each fire station.The Fire Chief shall appoint all Fire Captains.The Fire Captain reports to their assigned Battalion Chief.Fire Captain \- Authority: To act as the Incident Commander at the scene of an emergency until relieved by a superior officer.To enforce the policies, rules, regulations, and procedures of the Fire Department when necessary reprimands, prefer written charges, and/or temporarily suspend any officer or member under the rank of Captain.Fire Captain \- Responsibilities: Ensures the care and cleanliness of apparatus, equipment, station, and station furnishings, including staff cars assigned to their station.Answers assigned alarms; directly responsible for ensuring prompt, courteous, and professional service delivery to our customers.Maintains the discipline and morale of assigned personnel. Promptly reports to the Fire Chief through the chain of command all violations of the rules and regulations, and Standard Operating Procedures.Acquires and retains all fire and EMS certifications and other credentials required by the Fire Chief.Ensures the safe utilization of personnel and equipment at the scene of an emergency; at all times, ensures the health and welfare of the firefighters assigned to his/her supervision.Initiates and receives all necessary reports associated with the position; manages maintenance checks of equipment and any associated mechanical problems.Instructs all personnel under their supervision of their job responsibilities and expected performance standards.Informs the fire investigators of the possible causes of fire, and the preservation of any evidence at the scene of the emergency that appears suspicious.Communicates information to and from relief personnel pertaining to the activities and happenings that occur on their tour of duty.Seeks suggestions and information received from their subordinates and relays the information onto their superiors.Acquires and retains all fire and EMS certifications, licenses, and other credentials as required by the Fire Chief.Keeps superiors advised of progress, issues, and happenings brought to their attention that might affect the image, efficiency, or morale of the Fire Department.Practices good business economics in the use of Fire Department personnel, utilities, supplies, and equipment.Manages and verifies that all personnel under his/her supervision complete their required training, inspections, and reports.Serves as an Administrative Captain when required.As necessary, serves as acting Battalion Chief; assumes all responsibilities and authority of that position when acting as Battalion Chief.
SUPPLEMENTAL INFORMATION
Knowledge of principles, practices, methods and techniques of modern fire and life safety, fire suppression and emergency medical service activities.Ability to effectively communicate with coworkers and general public; ability to prepare, present, and evaluate trainings and seminars; ability to analyze problems and offer effective solutions; ability to supervise and motivate personnel; ability to prepare and maintain reports; skill in the use of automated office equipment.Knowledge of principles and practices of budget preparation and administration; knowledge of pertinent federal, state and local laws, codes and regulations.Special RequirementsThis position is subject to call back to duty.This position must be able to meet the Fire Department's Fit for Duty Standard, including the NFPA 1582 medical standard requirements.This position is classified as a safety\-sensitive position and is subject to random drug and alcohol testing during the course of employment.Incumbent cannot be on a performance improvement plan (PIP) on the date of the written exam.Licenses and CertificatesValid Class "B" commercial driver's license with good driving record and ability to maintain while employed, required.Must possess the following certifications: TCFP Fire Officer IIDSHS Paramedic\*\* Candidates are exempt from possessing a DSHS Paramedic certification if they were previously allowed to downgrade their EMS certification by Farmers Branch Fire Department prior to February 1, 2022\.Work EnvironmentExposure to dust, flames and smoke in the suppression of fires; physical demands require considerable physical effort with heavy lifting (over 100 lbs.) carrying, pushing, reaching crawling. The position requires heavy muscular effort with resulting fatigue of arms, legs, back or sensory facilities.
Salary Context
This $97K-$101K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →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 City of Farmers Branch, 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. This role's midpoint ($99K) sits 40% below the category median. Disclosed range: $97K to $101K.
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.
City of Farmers Branch AI Hiring
City of Farmers Branch has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Dallas, TX, US. Compensation range: $101K - $101K.
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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