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About This Role
Who We Are
About The Black Tux
The Black Tux is reinventing the formal wear industry so people can show up at their best on the days that matter most. The company designs and manufactures modern suits and tuxedos that actually fit—made of 100% wool, ordered online, and delivered for free. Using a combination of machine learning, tailor-trained fit specialists, and industry-leading customer service, The Black Tux guarantees a perfect fit every time.
About the Team
In this role, you'll be joining the Retail team. The Retail team spans across 7 brick and mortar showrooms and over 45 Nordstrom locations, all crucial to supporting our customers. This team specializes in looking at the diverse needs of our customers and uses their expertise to meet people where they are, guide them where they want to be, and seamlessly solve problems along the way. Our retail team ensures our customers have the support they need to become the best version of themselves.
What You’ll Do
To further this important mission, we are looking for an engaging Retail Area Manager to help us build our retail presence in Atlanta, GA and surrounding areas. The team member will partner with the VP and Director of Retail to develop the foundation for our retail business and community presence in multiple cities throughout the Southern states. We are looking for an individual who can work in a fast paced environment and has great interpersonal skills. In this role, you will focus on executing processes and procedures that help us consistently provide an exceptional customer experience and ensure that the showroom exceeds performance targets, and maintains brand consistency. This role will be based out of our Atlanta Showroom.
### Who You Are
- 5-10+ years of retail or related industry management experience
- Proven record hiring, managing, developing, and retaining a team
- Excellent interdepartmental communicator who can share feedback to improve company performance and customer experience
- Independent work ethic, highly organized in time management skills, and personal accountability
- Innovative, positive, proactive team player
- Ability to adapt to changing priorities
- Proficient in technology and a quick learner for new platforms
- Strong analytical and problem-solving skills
- Willingness to travel to stores throughout the South or other areas as needed
- Experience as a vendor or partner within a department store is a plus
- Previous remote or satellite leadership is a plus
- A bachelor's degree is a plus
You describe yourself as kind, collaborative, and creative. You know ownership is more than responsibility; it's about taking pride in your work and accountability for any success or failure. Customer experience is at the heart of everything you do, it inspires and motivates you to hold a high expectation of yourself and your teammates. You are humble, inclusive, and respectful.
### Perks & Benefits
- Competitive medical, dental, vision, and disability plans
- Option to participate in a 401(k) plan through Betterment
- Generous paid time off
- Paid holidays
- No Black Friday adjusted hours
- Monthly cell phone reimbursement
- Monthly wellness stipend
- 6 weeks paid parental leave; an additional 6-8 weeks disability leave for eligible birthing parents
- One Medical and Wellhub (Gympass) membership
- Employee engagement, cultural events, and trainings
- Discounts on garment rental and purchases for you, your partner, and friends & family
- Annual compensation review process
The base salary range for this position will be $75,000-$82,000. Compensation may vary based on the candidate’s skills, qualifications, and location. The Black Tux defines compensation plans using market data aligned with comparable companies at a similar stage and size as ours.
How we work at The Black Tux
At The Black Tux, we have 3 different ways we work (onsite, remote, and hybrid) to support the multi-faceted needs of our team. We encourage you to apply for roles that match the work-type and location where you currently or plan to live.
Onsite TBT team members need to be in person working full-time (40 hours per week) from an office, warehouse, or showroom. The reason being is that these roles have a requirement for a physical presence to do their job with customers, team members, or at one of our locations. We host a number of onsite events where all our team members are welcome!
Diversity Equity & Inclusion
We believe our people are our most important asset. The Black Tux is committed to bringing people together from various backgrounds and perspectives, providing employees with a safe and welcoming work environment free of discrimination and harassment. We strive to create a diverse & inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together. We are an equal-opportunity employer to all.
The Black Tux Participates in E-Verify. E-Verify is an internet-based system operated by the Department of Homeland Security and the Social Security Administration. It allows employers to confirm an individual's employment eligibility to work in the United States.
Privacy Policy Notice disclosed here.
Salary Context
This $75K-$82K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $170K across 1414 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 The Black Tux, 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 $210,000 based on 1,345 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $202,000. This role's midpoint ($78K) sits 63% below the category median. Disclosed range: $75K to $82K.
Across all AI roles, the market median is $220,000. Top-quartile compensation starts at $260,000. The 90th percentile reaches $311,800. For comparison, the highest-paying categories include Research Scientist ($260,000) and AI Architect ($251,680). By seniority level: Entry: $125,000; Mid: $202,000; Senior: $240,000; Director: $255,600; VP: $225,000.
The Black Tux AI Hiring
The Black Tux has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Atlanta, GA, US. Compensation range: $82K - $82K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: New York (228 roles, $223,400 median); San Francisco (216 roles, $255,750 median); Los Angeles (172 roles, $204,300 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 $220,000. Top-quartile compensation starts at $260,000. The 90th percentile reaches $311,800. Highest-paying categories: Research Scientist ($260,000 median, 48 roles); AI Architect ($251,680 median, 9 roles); Research Engineer ($250,200 median, 8 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 $220,000. Top-quartile roles start at $260,000, and the 90th percentile reaches $311,800. 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. Research Scientist roles lead at $260,000 median, while AI/ML Engineer roles sit at $210,000. 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: 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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