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About This Role
Working at Envision means having a job that’s more than just a way to make money. It's a job that makes a difference.
We offer team members:
- Careers with purpose
- Teamwork environment
- Amazing 401K Retirement Plan
- Envision Paid Life Insurance
- Medical, Dental, Vision, FSA Plans
- 10 Paid Holidays
- PTO \& Vacation
- Tuition Reimbursement
POSITION SUMMARY
The Senior Director of Supply Chain is responsible for leading and developing the Supply Chain across the entire organization, while creating and implementing a vision for continual improvement of procurement processes. Success will be measured on cost to serve, order performance, and working capital performance. Senior Director is responsible for sourcing direct and indirect materials, strategic alliance partnerships, vendor risk management and assessment, supply planning, master production scheduling, distribution, transportation and inventory. Senior Director is responsible for leading an environment that utilizes best practices for inventory planning, control, sourcing, scheduling and supply planning. Additional responsibilities include participating as a key member of the Leadership Team in the development, communication and delivery of the strategic business plan.
This position may be based in Wichita, KS or Dallas, TX and requires up to 50% travel between locations.RESPONSIBILITIES/ESSENTIAL FUNCTIONS INCLUDE
- Directs and coordinates the day\-to\-day and long\-term strategic activities of the supply chain team to ensure timely planning and procurement of goods and services to meet business demand.
- Evaluates the internal performance for all aspects of supply chain and drives continuous improvement of supply system operations with effective leadership.
- Develops and implements planning and procurement systems, including policies and procedures that drive a rigorous supplier selection process, supplier development, performance and establishes timely supplier evaluation and feedback to ensure continuous improvement throughout the supply chain.
- Develops and manages all Key Performance Indicators related to supply chain performance.
- Ensures supplier competition is balanced and fair, ensuring the best price, delivery and quality while reducing overall supply chain costs and risks to the organization.
- Conducts at least annual in\-person Vendor Summits. Identifies, recommends, and implements key new suppliers. Performs new and existing supplier technical evaluations, conducts ongoing supplier audits, and leads the negotiation/restructuring process of current and future business relationships.
- Prepares and shares reports for Leadership regarding supplier performance, and merchandise costs. Develops metrics for assessing and reporting program and/or commodity progress, productivity and variance analysis.
- Partners with key stakeholders, including Manufacturing, Engineering, Sales and Marketing. Drives continuous improvement to ensure on\-time, complete, and compliant deliveries to our customers.
- Ensures suppliers are aligned with technical and commercial requirements by working closely with Engineering, Quality, and Production.
- Ensures supply chain is engaged to support customer orders, creates and/or maintains optimum lead times and inventory levels while anticipating risks and issues in the supply chain.
- Determines material and merchandise cost trends, then formulates and coordinates policies and activities to maintain appropriate margins.
- Prepares and reviews requisitions and purchase orders for direct materials and equipment.
- Analyzes market conditions/trends, geopolitical conditions, and delivery systems to determine present and future material availability, and mitigate risks.
- Understands key production processes to better support the organization.
- Manage TMS provider relationship to ensure adherence to contract and continual cost reduction. Conduct quarterly meetings with TMS to review KPI’s.
- Travel required up to 50% splitting time in Dallas, TX and Wichita, KS.
- Performs other duties as deemed necessary or as required.
JOB REQUIREMENTS INCLUDE
Education: Bachelor’s degree in Supply Chain Management or Business Administration field required; Master’s degree preferred.
Experience: Minimum of 8 years of Supply Chain experience in a manufacturing environment, with the responsibilities of production, purchasing, inventory, production control, warehouse/shipping and receiving. A minimum of 5 years in a supervisory role required.
Knowledge/Skills:
- General working knowledge of manufacturing processes.
- Ability to lead people and get results through others.
- Solid problem\-solving skills and excellent management skills.
- Ability to maintain customer confidentiality.
- Ability to communicate effectively with all levels of personnel.
- Very Good working knowledge of Microsoft applications – Access, Excel, Word and Power Point.
- Microsoft Dynamics AX experience preferred.
- Ability to manage multiple concurrent projects.
- Proven track record involving complex global supply services.
- Demonstrated leadership skills in attracting and developing talent, and leading cross\-functional teams.
- Demonstrated ability to manage cost performance and drive improvement.
- Extensive experience in the development, negotiation and implementation of contracts, including the management of large multi\-national/global suppliers.
- Experience in developing and utilizing metrics, both internally and externally, to drive performance.
Licenses/Certifications:
- Institute for Supply Management Certification (C.P.M, C.P.S.M) or ASCM certification (CPIM or CSCP) preferred
SUPERVISORY RESPONSIBILITIES
Total Number of Employees Directly Supervising: 1
Number of Subordinate Supervisors Reporting to Position: 2
VISION REQUIREMENTS INCLUDE
*Can be performed with or without assistive technology**:*
X Required to perform activities such as: preparing/analyzing data/figures; viewing a computer screen; reading; inspecting small objects for defects; using measuring devices; and/or assembling parts with close eye contact.
\_\_\_Required to perform activities such as: operating machinery and/or power tools at or within arm’s reach; performing non\-repetitive tasks such as carpentry work or repairing machinery.
XRequired to review/inspect own assigned work, the work of others, or facilities or structures.
*Requires normal (or corrected to normal) vision/acuity**:*
\_\_\_ Required to operate motor vehicles and/or heavy equipment such as forklifts.
COMMENTS
*Envision, Inc. is an Equal Opportunity Employer and does not discriminate on the basis of any legally protected status or characteristic. Protected veterans and individuals with disabilities are encouraged to apply.*
*Envision, Inc. employs and advances in employment individuals with disabilities and protected veterans, and does not discriminate on the basis of disability or veteran status in its hiring or employment practices.*
*Reasonable accommodations are available to enable individuals with disabilities to perform the essential functions of a position.*
*“To improve the quality of life and provide inspiration and opportunity for people who are blind or visually impaired through employment, outreach, rehabilitation, education and research.”*
Integrity Curiosity Passion Initiative Teamwork Excellence
PHYSICAL REQUIREMENTS INCLUDE
*In an average workday, employee must:*
Task
None
Occasional
Frequent
Constant
Stand
x
Walk
x
Sit
x
Bend/stoop
x
Climb
x
Reach above shoulders
x
Squat/crouch/kneel
x
Push/pull
x
Lift
x
Usual amount
11\-25 lbs.
Carry
x
Usual amount
11\-25 lbs.
*Employee must use hands for repetitive action such as:*
Task
Right
Hand
Left
Hand
Simple grasping
Yes
Yes
Firm grasping
No
No
Fine manipulation
Yes
Yes
WORKING CONDITIONS INCLUDE
In an average workday, employee is exposed to:
Task
None
Occasional
Frequent
Constant
General shop or store conditions
x
General office environment
x
Humid, extreme hot/cold temps (non\-weather)
x
Outdoor weather conditions
x
Fumes or airborne particles
x
Fluorescent lights
x
Moving, mechanical parts
x
Toxic chemicals
x
Loud noise intensity levels
x
Risk of electrical shock
x
Travel for job
x
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 ENVISION INDUSTRIES, 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.
ENVISION INDUSTRIES AI Hiring
ENVISION INDUSTRIES has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Farmers Branch, TX, US, Wichita, KS, 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
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