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About This Role
AI Solutions Engineer (Early Career)Location: Rochester Hills, MI or Lisle, IL
Your Job
We are seeking an early-career AI Solutions Engineer who is passionate about applying artificial intelligence, analytics, and data-driven problem solving to real-world business challenges. In this role, you'll work alongside business leaders, engineers, and AI specialists to develop solutions that improve decision-making, accelerate product development, and create measurable business value.
You'll gain hands-on experience across the full AI solution lifecycle, from identifying opportunities and building prototypes to deploying scalable solutions and measuring impact. Working closely with Molex's corporate AI Digital Team and cross-functional stakeholders, you'll help shape how AI is applied across engineering, manufacturing, and business processes.
As part of Molex, a Koch company, you'll join an organization investing in AI, digital transformation, advanced manufacturing, and innovation. You'll have the autonomy to solve meaningful business challenges, take ownership of your work, continuously build new capabilities, and create value through your contributions.
This role is ideal for someone looking to accelerate their career at the intersection of AI, engineering, and business while gaining exposure to leaders, global teams, and growth opportunities across Molex and Koch companies.
Our Team
This role is part of the Project Management team within our Transportation Solutions Business Unit. The team collaborates across product management, engineering, manufacturing, quality, and other disciplines focused on developing and bringing innovative products to the automotive market. Working across functions, you'll help solve meaningful business and technical challenges while supporting initiatives that influence product development, operational excellence, and customer value.
What You Will Do
- Design, develop, test, and deploy AI-powered solutions that improve engineering productivity, accelerate product development, enhance manufacturing performance, and create measurable business value.
- Partner with business stakeholders to understand challenges and translate them into data-driven opportunities and scalable solutions.
- Develop and maintain analytical models, data pipelines, dashboards, applications, and reporting tools.
- Collaborate with product owners, software engineers, data engineers, and business leaders to deliver scalable AI and analytics solutions.
- Assist with project execution, including requirements gathering, solution validation, testing, deployment, and continuous improvement activities.
- Apply modern development practices, AI-assisted tools, and emerging technologies to improve productivity and solution quality.
- Communicate insights, recommendations, and project outcomes to both technical and non-technical audiences.
- Work with diverse datasets spanning engineering, manufacturing, quality, operations, and product management to solve complex business problems.
- Continuously learn new technologies and business domains while contributing across high-impact AI initiatives .
Who You Are (Basic Qualifications)
- Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Information Systems, or a related field.
- 0-3 years of professional, internship, co-op, or academic project experience in data science, analytics, AI engineering, or software development.
- In-depth experience with any programming language (e.g. Python)
- Understanding of machine learning, statistics, and AI engineering concepts through coursework, projects, or work experience.
- Strong analytical, problem-solving, and communication skills.
- Demonstrated curiosity, learning agility, and a desire to create value through technology.
What Will Put You Ahead
- Internship, project, or coursework experience in manufacturing, engineering, product development, project management, operations, or business analytics.
- Familiarity with cloud platforms, MLOps concepts, or model deployment methodologies.
- Experience developing end-to-end data science / AI solutions.
- Experience with AI-assisted development tools and software engineering best practices (e.g. version control, DevOps, etc.)
- Experience collaborating with global teams, participating in international projects, or working across multiple regions, cultures, or time zones.
What Will Help You Succeed
- Curiosity, learning agility, and a passion for applying AI and technology to solve business challenges.
- Strong collaboration and communication skills with the ability to work effectively across technical, business, and global teams.
- Initiative and ownership to identify opportunities, challenge assumptions, and drive solutions from concept through implementation.
- Adaptability and enthusiasm for learning new technologies, working across diverse business functions, and contributing to a variety of projects.
For this role, we anticipate paying $90,000 - $110,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.
At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.
Sponsorship: This position is open to candidates who require current or future employment sponsorship in the United States.
Hiring Philosophy
All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here .
Who We Are
As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before.
At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company.
Our Benefits
Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter.
Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.
Equal Opportunities
Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here , aquí , or tu ).
Salary Context
This $90K-$110K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $176K across 1540 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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Molex, 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 $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($100K) sits 53% below the category median. Disclosed range: $90K to $110K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Molex AI Hiring
Molex has 4 open AI roles right now. They're hiring across AI/ML Engineer, MLOps Engineer, LLM Engineer. Positions span Lisle, IL, US, Austin, TX, Fremont, CA. Compensation range: $110K - $110K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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