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About This Role
Behavioral Framework – a leading provider of ABA therapy to children diagnosed with autism - is looking for a Provider Liaison!
Position Overview
The Provider Liaison will be responsible for developing and managing provider relations within Behavioral Framework’s Tennessee service areas. This position will be key to the development of new and existing provider and client relations, while supporting the overall marketing strategy. This individual will act as a liaison between Behavioral Framework and local providers to communicate available services and improve provider relationships.
Behavioral Framework Highlights:
- Behavioral Framework is devoted to the pursuit of providing excellent, honest, and compassionate care within the autism community.
- We believe in the dedication and passion of our professional team and the science behind ABA.
Job Responsibilities
- Act as provider liaison for Behavioral Framework’s ABA Therapy services and Pathways Diagnostic Services.
- Educate providers on Behavioral Framework’s clinical care model.
- Cultivate community and provider relationships to position Behavioral Framework as a trusted source for superior care.
- Conduct calls and office visits with pediatricians, psychologists, psychiatrists, hospitals, insurers, daycares, schools, community organizations, and other care providers to build relationships and educate their staff on available services and accurate wait times.
- Attend and local non-profit partner events in the Tennessee region.
- Increase Behavioral Framework’s brand awareness within local communities.
- Profile each provider based on location, services, staff size, etc.
- Develop a basic understanding of regional business conditions relating to the industry, competition, and relevant business trends.
- Relay client and provider feedback to the VP of Client Experience to improve outreach strategy. Establish a positive and collaborate working relationship with Behavioral Framework and Pathways team members.
- Work in collaboration with Marketing, Operations and Intake teams to provide continuous improvements in client referral processing methods.
- Demonstrated ability to operate as a team player and able to work independently and collaboratively with others.
- Ability to manage multiple projects and perform duties with minimal supervision. Responsible for administrative duties including timely completion of expense reports, updating CRM with provider information, and creating detailed analysis and reports. Responsible for managing travel expenses.
- Perform other related duties as assigned.
Required Skills and Abilities
- Excellent verbal and written communication skills.
- Strong time management, problem-solving, and interpersonal skills. Results driven self-starter with a passion for helping children.
- Detail oriented with the ability to follow directions. Competency in computer skills.
- Strong ability to work independently.
- Must have a valid driver’s license and access to personal transportation in the service area(s). A valid driver’s license and auto liability insurance is required.
- Ability to perform all duties with a high professional standard.
Experience and Education
- Bachelor's degree in business, marketing, or health-related field required.
- Five years of experience in provider relations, business, sales or related field required.
- Knowledge of the ABA and the behavioral health industry is a plus.
Work environment, Physical Conditions
- Ability to work in a fast-paced environment.
- Ability to work 40 hours per week.
- Ability to work cooperatively with others.
- Must comply with practice policies and procedures.
- Ability to travel throughout the state of Tennessee.
- Access to personal transportation in the service area(s) with valid driver’s license and auto liability insurance.
- Physical activities include sitting for long periods of time, walking, bending, kneeling. Must be able to reach, pull, and push.
- Requires manual dexterity, auditory and visual skills.
- Ability to lift up to 15 lbs.
- Total compensation up to $95,000 (including base salary and performance bonus)
EOE
*Behavioral Framework is committed to equitable treatment for all employees, clients, and their families. We welcome and respect the diversity of the families we serve, and we focus our organizational efforts to build a culture of respect, dignity, fairness, caring, equality, and self-esteem.*
*We believe our strength comes from the shared experiences of our employees, clients, and community. We pride ourselves on serving a diverse population and always seeking to hire, retain, and promote from a wide variety of backgrounds.*
*#BFADMIN*
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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Behavioral Framework, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Behavioral Framework AI Hiring
Behavioral Framework has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Nashville, TN, US.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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