Interested in this AI/ML Engineer role at Nova-Tech Engineering?
Apply Now →Skills & Technologies
About This Role
BI \& AI Analyst
Pay Range: $75,000 \- $115,000 /Year
The work arrangement for this position will be determined based on the candidate's location, with onsite and remote options available.
Who is Nova\-Tech Engineering?
Headquartered in Willmar, MN, Nova\-Tech Engineering is a growing, dynamic company founded in 1992 that began as one person’s passion to benefit the agricultural industry. Through innovative process automation technology, the company engineers and manufactures products that serve over 500 commercial poultry hatcheries in over 65 countries worldwide.
Nova\-Tech houses every aspect of its business on the MinnWest Technology Campus, including a manufacturing facility located just steps away from our engineering and drafting teams. Walking from building to building, you can observe our whole process, from concept to final product.
What we’re looking for:* Design, develop, and maintain dashboards, reports, and data visualizations to support business decision\-making.
- Analyze complex datasets to identify trends, risks, opportunities, and actionable insights.
- Build and optimize data pipelines, ETL processes, SQL queries, and system integrations.
- Develop scalable data models while ensuring data accuracy, integrity, and governance standards.
- Serve as the subject matter expert for Microsoft Dynamics 365 Finance \& Operations and CRM data.
- Partner cross\-functionally with Sales, Marketing, Operations, Finance, and IT to define KPIs and reporting needs.
- Automate reporting processes and improve stakeholder access to timely, accurate data.
- Lead AI strategy and implementation, including governance, workflow integration, and user adoption initiatives.
- Contribute as an engaged team member aligned with company values, vision, and strategic goals.
What you’ll do:
The BI \& AI Analyst is responsible for designing, developing, and maintaining business intelligence solutions that drive data\-informed decision\-making across the organization. This role also leads the evaluation, implementation, and governance of Artificial Intelligence technologies in an enterprise business context.
Other key areas include:* Bachelor’s degree in Computer Science, Information Systems, Analytics, Statistics, or related field.
- 5\+ years of experience in business intelligence, data analytics, or a related role; prior technical lead experience preferred.
- Strong SQL skills with expertise in relational databases and data modeling.
- Experience with BI and data visualization tools such as Power BI, Tableau, or Looker.
- Proficiency in data\-focused programming languages such as Python or R.
- Experience working with ERP/CRM systems, preferably Microsoft Dynamics 365\.
- Strong analytical, problem\-solving, and data storytelling skills with the ability to communicate insights to technical and non\-technical audiences.
- Knowledge of AI/ML concepts and hands\-on experience with AI tools, automation platforms, APIs, or enterprise AI solutions.
- Ability to translate business needs into scalable analytics and AI\-driven solutions.
- Strong organizational, communication, and multitasking skills with the ability to manage priorities in a fast\-paced environment.
- Professional, collaborative, and ethical approach with a commitment to continuous learning and teamwork.
Our location:
In 2005, Nova\-Tech partnered with Life\-Science Innovations to buy a 37\-building, 110\-acre historic hospital facility in Willmar from the State of Minnesota. Since that time, we have developed the resulting MinnWest Technology Campus into the largest privately owned technology park in the country. Willmar, MN is a bustling community located less than two hours from Minneapolis and one hour from St. Cloud known for its lakes and vibrant entertainment.
Things to check out: Willmar Stingers, Willmar WarHawks, Little Crow Ski Team, Green Lake and boat cruises, Glacial Lakes State Trail, Dorothy A. Olson Aquatic Center, The Barn Theatre, Sibley State Park, Robbins Island, Destination Playground, YMCA, Ridgewater College, area golf courses and simulators, local breweries, restaurants, and shopping.
Why join our team?
Nova\-Tech Engineering offers a flexible, collaborative, and productive work environment focusing on culture and strengths. We’ve worked hard to create our unique culture and seek team members who match our core values so we can continue to create revolutionary solutions that advance our customers’ ability to feed the world.
The MinnWest Technology Campus offers a wide array of on\-site amenities including a cafeteria, pool, fitness center, gymnasium, meeting spaces, daycare center, and more! We offer competitive wages with generous paid time off and benefits starting day one! Learn more at www.nteglobal.com.
To Apply or Further Inquire Contact:
Rachel Weiss \| Talent Acquisition
(320\) 222\-9790
qJVRG9oWDS
Salary Context
This $75K-$115K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Nova-Tech Engineering, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($95K) sits 48% below the category median. Disclosed range: $75K to $115K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Nova-Tech Engineering AI Hiring
Nova-Tech Engineering has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Willmar, MN, US. Compensation range: $115K - $115K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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.