Interested in this AI/ML Engineer role at Suddath?
Apply Now →Skills & Technologies
About This Role
Why Choose Suddath to “Move” your Career to the Next Level?
At Suddath, you can be part of something special and inclusive! Join a team that has a 100\+ year reputation for excellence as an innovative, growing and financially stable company that is dedicated to promoting a culture that thrives on inclusion and diversity. From numerous awards to being recognized as one of the best places to work, Suddath offers a caring, family environment while providing relocation and logistics services to people and companies all around the world.
What We Offer!
- A competitive wage with a comprehensive benefits package, including a 401(k) plan with company matching
- Weekly pay for hourly\-paid employees. Biweekly pay for salaried employees.
- Paid Time Off (PTO) and paid company holidays
- A tuition reimbursement plan where employees are encouraged to continue their education and development
- For more information on our benefit offerings, please visit https://suddath.com/about/careers/ and scroll down to view our employee benefits.
SUMMARY
The Business Line Sales Director (Player‑Coach Role) is responsible for leading a team of Sales Executives within a defined business line while also personally generating revenue. This role combines strategic sales leadership with direct selling responsibilities, ensuring both individual and team performance. The leader will drive new business growth, oversee sales activity disciplines, guide solution development, and collaborate cross‑functionally to deliver high‑quality, executable logistics solutions. This position requires a seasoned commercial professional who thrives in a hands‑on leadership model within a fast\-paced, operationally driven logistics environment.
ESSENTIAL DUTIES AND RESPONSIBILITIES
- Lead, mentor, and develop a team of Sales Executives responsible for selling services within the assigned business line.
- Hold accountability for team sales performance, including revenue attainment, activity expectations, pipeline development, and forecast accuracy.
- Conduct regular 1:1s, pipeline reviews, and performance coaching sessions to drive execution and improve sales effectiveness.
- Collaborate closely with Operations, Pricing, and Solutions Engineering to ensure solutions are aligned with operational capabilities and customer requirements.
- Provide support during customer meetings, discovery sessions, solution presentations, and facility tours to help advance and close strategic opportunities.
- Reinforce a high\-performance culture centered on accountability, collaboration, and continuous improvement.
- Own a personal revenue quota, actively managing a pipeline of new business opportunities.
- Proactively identify, pursue, and close opportunities within the assigned business line, contributing directly to overall revenue growth.
- Manage the full sales cycle, including prospecting, discovery, RFP/RFQ responses, pricing presentations, and negotiations.
- Build and maintain strong relationships with prospects and customers across relevant industry verticals.
- Maintain thorough CRM documentation covering activity, opportunity progression, and forecasting to ensure reporting accuracy and business visibility.
- Serve as a senior representative in market\-facing activities, industry events, and client engagements.
QUALIFICATONS
*To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.*
Education \& Experience:
Minimum 7 years of progressive sales experience in logistics, supply chain, transportation, contract logistics, or final mile (relevant to dedicated line of business), to include a minimum 3 years of sales leadership, player‑coach responsibility, or team development experience. Demonstrated success in winning complex logistics solutions and leading cross‑functional RFP processes. Proven ability to manage both individual selling responsibilities and team performance simultaneously.
Travel:
Travels to support marketplace activity and company requirements – may be frequent and could include overnights.
Knowledge, Skills, and abilities:
- Demonstrated ability to lead sales teams \& initiatives, drive revenue, and manage strategic client relationships.
- Ability to read, analyze, and interpret client relocation policies, contracts, and procedural documents.
- Strong verbal and written communication skills for engaging with prospects, senior leadership, and public audiences.
- Proficiency in delivering presentations and leading negotiations with internal and external stakeholders.
- Customer service orientation with interpersonal skills to build and maintain client trust and satisfaction.
- Ability to prioritize tasks, adapt to changing needs, and manage multiple responsibilities in a fast\-paced environment.
- Proficiency in Microsoft Office Suite, CRM platforms such as Hubspot, and sales enablement tools.
- Analytical and problem\-solving skills to resolve issues using sound judgment and standardized procedures.
- Numerical proficiency to calculate and interpret figures including commissions, discounts, and percentages.
PHYSICAL/ENVIRONMENTAL DEMANDS
*The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.*
Physical Activity Level:
While performing the duties of this Job, the employee is regularly required to stand, walk, sit, use hands to finger, handle, or feel, see clearly and talk or hear. The employee must occasionally lift and/or move up to 10 pounds unassisted.
Working Conditions:
Noise level in the work environment is usually moderate. Work is performed climate\-controlled environment in an office setting with adequate ventilation.
*Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.*
The Suddath Companies is a multifaceted group of companies that specialize in worldwide corporate employee relocations, household moving, warehouse and logistics management and specialized transportation services.
The Suddath Companies provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
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 Suddath, 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. Director-level AI roles across all categories have a median of $244,288.
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.
Suddath AI Hiring
Suddath has 8 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Columbia, SC, US, Nashville, TN, US, Richmond, VA, US.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.