Interested in this AI/ML Engineer role at ZT Systems?
Apply Now →Skills & Technologies
About This Role
About The Role
ZT Systems, a wholly owned subsidiary of Sanmina,, is seeking AI/ML Engineer to help build, deploy, and operate AI applications. You will work closely with software engineers, data scientists, and platform engineers to develop scalable ML solutions, automate training and deployment workflows, and support production AI infrastructure. This role is ideal for someone with a strong software engineering foundation who has some knowledge of Machine Learning/AI fundamentals and on-prem cloud-native infrastructure.
Minimum Requirements
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
- 2–5+ years of professional experience in Machine Learning, AI, Software Engineering, or related fields
- Strong programming skills in Python including FastAPI, async, and production-grade code
- Good understanding of Machine Learning fundamentals
- Familiarity with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
- Experience working with Linux environments
- Basic experience with Docker and containerized applications
- Working knowledge of Kubernetes fundamentals (deployments, services, pods, jobs)
- Understanding of version control using Git
- Strong problem-solving skills and ability to work in a collaborative engineering environment
Preferred Qualifications
- Familiarity with LLMs and prompt engineering
- Experience building RAG pipelines end-to-end (chunking, embedding, retrieval, reranking)
- Experience with LLM serving frameworks such as vLLM or Ollama
- Knowledge of vector databases such as Qdrant
- Some frontend experience with TypeScript and Next.js
- Experience with Orchestration tools such as Kubeflow, Kuberay etc
ZT Systems assesses market data to ensure a competitive compensation package is created for all our employees. The typical base salary for this position is expected to be between $105,000 and $154,000 per year. If hired, the final base salary will be determined on an individual basis taking into consideration experience, skills, knowledge, education and/or certifications.
Base salary is just one component of ZT Systems total rewards philosophy. We take pride in offering a wide range of benefits and perks that appeal to the variety of needs across our diverse employee base. Other rewards may include bonus, paid time off, 401k, tuition reimbursement, wellbeing resources, and more.
We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this opportunity but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
About ZT Systems
At ZT Systems, a Sanmina Company, you’ll get to do work you are proud of alongside smart, passionate people. Every day, there are opportunities to collaborate with the best in the industry to design, build, and deliver impactful solutions to world-class customers. Along the way, you will gain hands-on experience in a fast-paced environment that’s challenging, rewarding, and career-defining.
A culture built around our values we work hard and think fast. We view challenges as opportunities—to do better, push harder, and be faster than we were the day before. When we fail, we learn from it and move on together. And when we succeed, we use the momentum to go even further. We create value with everything we do, building the foundation of today—and transforming the future of tomorrow.
Join ZT Systems and help us build technology infrastructure that connects the world.
What We Offer
At ZT Systems, a Sanmina Company, we believe that investing in our people is key to our continued growth and innovation. When you join our team, you’ll gain access to a comprehensive and inclusive benefits package designed to support your well-being, financial security, and professional development—both now and in the future.
Compensation & Financial Security
- Competitive base salary
- Performance-based annual bonus eligibility
- 401(k) retirement savings plan
- Tuition reimbursement for eligible education programs
Health & Wellness
- Comprehensive medical, dental, and vision coverage with access to leading providers
-Mental health resources and employee wellness support programs-
- Company-paid life and disability insurance
Time Away & Work-Life Balance
- Paid time off (PTO) and company-paid holidays
- Parental leave and family care support programs
Growth & Purpose
- Structured training programs and on-the-job learning opportunities
- Matching gifts and volunteer programs to support causes you care about
These benefits are available to eligible employees and are designed to grow with you as your career evolves. Full benefits and eligibility varies by work location.
ZT Group Int’l. is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. ZT Systems provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
Please be aware that certain positions may require the applicant to either 1) be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or 2) be eligible to obtain an export control license or license exception from the Bureau of Industry and Science & U.S. Department of Commerce. All offers of employment will be conditional subject to the foregoing.
Salary Context
This $105K-$154K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At ZT Systems, 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 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($129K) sits 39% below the category median. Disclosed range: $105K to $154K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
ZT Systems AI Hiring
ZT Systems has 4 open AI roles right now. They're hiring across AI/ML Engineer. Based in Secaucus, NJ, US. Compensation range: $154K - $210K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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.