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About This Role
Job Posting
BUILD THE FUTURE OF PERFORMANCE \- LEAD, DEVELOP, \& TRANSFORM TRAINING INTO A STRATEGIC ADVANTAGE
Job Title: Training Manager Department: Training
Reports To: Director, Sustainability, Quality \& Training FLSA Status: Exempt
Shifts: Days\-Onsite Wage Range: $75,000\-95,000
*\*Base pay is based on job\-related skills, experience, credentials, role scope, and location. Candidates outside the posted range are encouraged to apply, as qualifications and market factors may influence compensation. \**
Job Summary:
A Training Manager oversees the planning, execution, and continuous improvement of all training activities within the production environment. This role provides leadership to the training team, ensuring employees are properly trained in equipment, operational processes, safety standards, quality requirements, and customer specifications. The Training Manager develops training strategies, evaluates training effectiveness, and partners with manufacturing leadership to ensure a highly skilled, compliant, and efficient workforce.
Essential Duties and Responsibilities:
Training Program Leadership
- Develop implement, and maintain training programs for production staff, including new\-hire onboarding, job specific technical training, cross\-training, and refresher programs.
- Ensuring training content supports operations efficiency, quality standards, postal requirements, and safety compliance.
Supervision and Team Development
- Supervise, coach and mentor Production Trainers and subject matter experts (SMEs).
- Provide regular performance feedback and promote professional development within the training team.
- Assign training responsibilities, manage workloads, and ensure coverage across shifts as needed.
Evaluation and Quality Assurance
- Evaluate training effectiveness using observations, assessments, performance metrics, and operator competency.
- Ensure Standard Operating Procedures (SOPs), work instructions and training documentation are accurate, current, and easily accessible.
- Collaborate with Quality Assurance to integrate QA checkpoints, verification steps and process controls into training program.
Operational and Customer Support
- Partner with production leadership to address skill gaps, process inconsistencies, and workforce readiness issues.
- Assist in resolving customer concerns related to raining, quality or compliance, ensuring timely corrective action.
- Support and champion continuous improvement initiatives including Lean, Kaizen and 6S methodologies.
Administrative and Compliance Responsibilities
- Oversee scheduling of training sessions, certification renewals, and competency evaluation across multiple shifts.
- Maintain accurate training records and documentation to support audits, compliance requirements, and customer reviews.
- Ensure all training practices align with company policies, industry standards, and safety regulations.
- Follow all Nahan Safety and Quality policies and procedures.
- Support 6S initiatives as required.
- Perform other duties as assigned.
Skills and Abilities Required:
- Strong leadership and coaching skills with the ability to motivate, develop and evaluate trainers and production employees.
- Excellent communication skills\-written, verbal, interpersonal and active listening\-with the ability to convey complex processes clearly.
- Skilled in adapting training strategies to diverse learning styles and varying experience levels.
- Strong organizational and time\-management skills with the ability to manage multiple priorities in an entrepreneurial environment.
- Proficiency in Microsoft Office and training management systems/LMS tools.
- Solid understanding of production workflows, equipment operations and lettershop processes.
- Strong ability to assess situations quickly, identify root causes, and develop practical solutions that support safe, efficient, and high\-quality production operations and communicate those problems/causes and solutions to others in a clear way.
- Demonstrated ability to work independently, exercise sound judgment, and make training decisions that support operational objectives.
- Proficiency/fluent with English language, both written and verbal.
+ Secondary language in Spanish or others, value added.
Education and Experience:
- High School Diploma or equivalent required,
- Post\-secondary education in Operations, Training \& Development, or related fields strongly preferred.
- Minimum of three (3\) years of experience in production training, manufacturing supervision, or related leadership roles.
- Prior experience in printing, direct mail, or lettershop operations strongly preferred.
Benefits
- Medical
- Dental
- Vision
- 100% Employer Paid Life Insurance
- 100% Employe Paid Short Term \& Long\-Term Disability Insurance
- Other Voluntary Employee Benefits i.e. (Accident \& Critical Illness)
- 401K \& Profit Sharing with Employer Match
- Vacation/Holiday/Sick \& Safe Time
Work Environment and Physical Demands
The work environmental characteristics and physical demands described here are representative of those an employee encounters while performing essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
This job operates in a Manufacturing environment. While performing the duties of this job inside the manufacturing facility, the employee is frequently exposed to normal to moderate working conditions for a manufacturing facility with a noise level that is usually moderate to loud. The role routinely uses printing equipment and machines.
While performing the duties of this job, the employee is regularly required to talk or hear. The employee may be required to stand for long periods of time as well as use hands or fingers to reach or handle, and to reach with hands and arms. The employee is regularly required to stand, walk, climb, balance, stoop, kneel, crouch, or crawl. The employee will regularly lift 70lbs or more at a time. All vision abilities are required to encompass close\-up work. Employees must be able to tolerate and endure extended seasonal hours and maintain alertness to meet deadlines.
Occasionally while performing duties of this job, the employee may be exposed to machinery and moving parts, airborne particles including paper dust and hazardous materials or fumes, which may require the use of PPE. The employee may be exposed to adverse weather conditions, extended seasonal hours, high precarious places, and confined spaces. The nose level in some of the work environments may require the use of hearing protection.
About the Company
Nahan was founded 60 plus years ago by a local family in the heart of Minnesota. It is a deeply human company from how we work with each other, how we serve our clients, to how we reach customers. We provide full service direct marketing with award winning results. Innovation and insight inform everything we do. Our success is rooted in putting people first, doing the right thing for our clients and associates and delivering the highest levels of quality. In a world where personalization and customization are valued above all, we make messages feel personal while keeping the process simple. We’re here to listen to, create and deliver results to our clients. Our winning track record is based on proof, not promises. We consistently deliver big wins, better performance and continual growth for marketers. We’re Nahan\-real people making real connections.
Disclaimer
This job description is not a complete description of responsibility but reflects the general qualifications, duties and/or responsibilities necessary to perform this position. All candidates who receive a written offer of employment will be required to successfully complete and pass a background check, a physical test, as well as test for commonly abused controlled substances in accordance with the Company’s Drug Free Workplace Policy. Nahan reserves the right to revise the job description as a circumstance warrant. Nahan is an at\-will employer, which means that either the employee or the company may terminate the relationship at any time, with or without notice, and with or without cause.
Base pay is based on job\-related skills, experience, credentials, role scope, and location. Candidates outside the posted range are encouraged to apply, as qualifications and market factors may influence compensation.
Nahan is proud to be an equal opportunity employer committed to fostering a diverse and inclusive workplace. We do not discriminate based on race, color, religion, sex, national origin, age, disability or any other characteristic projected by law.
Salary Context
This $75K-$95K 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 Nahan Printing, 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 ($85K) sits 49% below the category median. Disclosed range: $75K to $95K.
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.
Nahan Printing AI Hiring
Nahan Printing has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Saint Cloud, MN, US. Compensation range: $95K - $95K.
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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