Interested in this AI/ML Engineer role at Samsung Electronics?
Apply Now →Skills & Technologies
About This Role
Position Summary
Headquartered in Englewood Cliffs, N.J., Samsung Electronics America, Inc. (SEA), the U.S. Sales and Marketing subsidiary, is a leader in mobile technologies, consumer electronics, home appliances, enterprise solutions and networks systems. For more than four decades, Samsung has driven innovation, economic growth and workforce opportunity across the United States—investing over $100 billion and employing more than 20,000 people nationwide. By integrating our large portfolio of products, services and AI technology, we’re creating smarter, sustainable and more connected experiences that empower people to live better. SEA is a wholly owned subsidiary of Samsung Electronics Co., Ltd. To learn more, visit Samsung.com. For the latest news, visit news.samsung.com/us.Role and ResponsibilitiesPosition Overview \& Why You’ll Excel
Our Retail Operations team rewrites the rules of traditional retail with immersive, tech\-driven experiences—ideal for a proven leader who excels at developing people, driving results, and ensuring operational excellence.
As a Store Lead, you are part of the store’s management team, responsible for leading associates, overseeing operational areas, and driving sales performance. With at least three years of retail leadership experience (and ideally one year in big\-box leadership), you will play a critical role in building team capability, delivering a best\-in\-class customer experience, and ensuring the store is always ready for both customers and executives. In the absence of higher leadership, you are expected to seamlessly assume full operational and sales management responsibilities.What You’ll Own* Sales\-First Culture
Champion a revenue\-driven environment by modeling selling behaviors, coaching associates, and driving sales performance to meet and exceed targets.
- Customer Experience Excellence
Deliver engaging demos, workshops, and events, ensuring every customer interaction reflects Samsung’s premium brand experience.
- Operational Leadership
Partner with the Store Manager, General Manager, and ASM to execute store priorities, uphold SOP compliance, and maintain operational readiness.
- Team Coaching \& Development
Mentor and coach associates with feedback, training, and recognition programs, fostering accountability and confidence.
- Onboarding \& Training
Lead new\-hire orientation and ongoing associate development, ensuring mastery of Galaxy product knowledge and operational standards.
- Floor Leadership
Manage the sales floor during assigned shifts, driving customer flow, maintaining merchandising standards, and ensuring smooth daily operations.
- Cross\-Functional Collaboration
Coordinate with Store Technology, Repairs, Visual Merchandising, and Corporate Support to resolve issues and deliver flawless execution.
- Acting Store Management
Assume full operational and sales management responsibilities when the ASM, Store Manager, or General Manager are not present.
- Opening \& Closing Procedures
Oversee daily opening and closing routines and provide coverage during holidays, launches, and peak business periods
What You Bring* Retail Leader – 3\+ years of retail leadership experience, with at least 1 year in big\-box or specialty retail.
- People\-First Coach – Proven ability to mentor, motivate, and develop associates while fostering a high\-performance team culture.
- Operationally Skilled – Experienced in executing SOPs, managing store readiness, and leading day\-to\-day retail operations.
- Analytical \& Action\-Oriented – Skilled at using data and performance metrics to guide decisions and improve results.
- Adaptable \& Collaborative – Thrives in fast\-paced, dynamic environments and partners seamlessly across functions and teams.
- Preferred: Consumer Electronics Savvy – Knowledge of smartphones, wearables, and connected ecosystems, with the ability to translate features into customer benefits.
What We Offer* Competitive salary plus MBO bonus tied to store and individual performance
- Medical, Dental \& Vision insurance
- Life Insurance and 401(k) retirement plan
- Employee Purchase Program for Samsung products
- Tuition Assistance and Student Loan Program (after 6 months)
- Paid Time Off and Wellness Incentives
- A chance to grow your leadership career in a cutting\-edge retail environment
- Be part of a culture that celebrates innovation and relentless pioneer spirit
Apply today and elevate your career as a leader in Samsung’s retail revolution.Skills and Qualifications
Life @ Samsung \- https://www.samsung.com/us/careers/life\-at\-samsung/
Benefits @ Samsung \- https://www.samsung.com/us/careers/benefits/
\#LI\-SW1
The salary range for this role is expected to be between $32 and $35 hourly. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.
Regular full\-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more. In addition, regular full\-time employees (salaried or hourly) are eligible for MBO bonus compensation, based on company, division, and individual performance.
At Samsung, we believe that innovation and growth are driven by an inclusive culture and a diverse workforce. We aim to create a global team where everyone belongs and has equal opportunities, inspiring our talent to be their true selves. Together, we are building a better tomorrow for our customers, partners, and communities.* Samsung Electronics America, Inc. and its subsidiaries are committed to employing a diverse workforce, and provide Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.
Reasonable Accommodations for Qualified Individuals with Disabilities During the Application Process
Samsung Electronics America is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. If you have a disability and require a reasonable accommodation in order to participate in the application process, please contact our Reasonable Accommodation Team (855\-557\-3247\) or SEA\_Accommodations\_Ext@sea.samsung.com for assistance. This number is for accommodation requests only and is not intended for general employment inquiries.
Salary Context
This $66K-$72K 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 Samsung Electronics, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($69K) sits 58% below the category median. Disclosed range: $66K to $72K.
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.
Samsung Electronics AI Hiring
Samsung Electronics has 6 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Mountain View, CA, US, Plano, TX, US, New York, NY, US. Compensation range: $72K - $329K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.