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Entry Level Apple Machine Learning Engineer Jobs in Emerson, NJ

Fluidstack

Machine Learning Engineer

Manhattan, NY · On-site

$130 - $180/hr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

Prudential

Lead, Machine Learning Engineer

Newark, NJ · On-site

$107K - $141K/yr

As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability ...

Warnerbros

Machine Learning Engineer I

New York, NY · On-site

$106K - $146K/yr

CNN is seeking a Machine Learning Engineer I to build and deploy ML systems that power personalization, search, recommendations, and content understanding for millions of users across CNN's digital ...

Nutanix

Machine Learning Compiler

Manhattan, NY · On-site

$141 - $211/hr

Engineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

Sunsets HQ Corp.

Machine Learning Engineer

New York, NY · On-site

$61 - $80.75/hr

You have 3+ years of professional machine learning or software engineering experience, including improving models in production * You have startup experience, enjoy broad ownership, and thrive when ...

Kepler

Machine Learning Engineer

Manhattan, NY · On-site

$180 - $260/hr

Our founding engineers led Foundry's core systems - Ontology, Fusion, Workshop, FoundryML - and ... Learning budget - attend any conference, course, or program that makes you better at what we're ...

Career Renew

Senior Machine Learning Engineer

New York, NY · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Grailed

Staff Machine Learning Engineer

New York, NY · On-site

$187K - $233K/yr

ROLE OVERVIEW Grailed is looking for a Staff Machine Learning Engineer to help us build the models and systems that connect buyers to the inventory they're looking for -- and surface things they didn ...

SeatGeek

Senior Machine Learning Engineer

Manhattan, NY · On-site

$145K - $209K/yr

We are looking for Software Engineers with varying levels of experience to join SeatGeek's R&D team ... Annual subscription to Spotify, Apple Music, or Amazon music The salary range for this role is $145 ...

SeatGeek

Senior Machine Learning Engineer

New York, NY · On-site +1

$145K - $209K/yr

We are looking for Software Engineers with varying levels of experience to join SeatGeek's R&D team ... Annual subscription to Spotify, Apple Music, or Amazon music The salary range for this role is $145 ...

SeatGeek

Senior Machine Learning Engineer

New York, NY · On-site

$145K - $209K/yr

We are looking for Software Engineers with varying levels of experience to join SeatGeek's R&D team ... Annual subscription to Spotify, Apple Music, or Amazon music The salary range for this role is $145 ...

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All JobsApple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer Jobs in Emerson, NJ

Entry Level Apple Machine Learning Engineer information

See Emerson, NJ salary details

$30.7K

$70.9K

$120.7K

How much do entry level apple machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for entry level apple machine learning engineer in Emerson, NJ is $70,932.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,700.00 and $80,300.00 per year, depending on experience, location, and employer.

What does an entry level Apple machine learning engineer do?

An Entry Level Apple Machine Learning Engineer helps design, develop, and implement machine learning models and algorithms for Apple products and services. They work closely with senior engineers and data scientists to collect and analyze data, build prototypes, and improve the performance of machine learning systems. Responsibilities often include coding, model evaluation, and collaborating with cross-functional teams to integrate ML solutions into Apple’s ecosystem. This role is ideal for those with a strong foundation in programming, statistics, and a passion for innovative technology.

What are the key skills and qualifications needed to thrive as an entry level Apple machine learning engineer?

To thrive as an Entry Level Apple Machine Learning Engineer, you generally need a solid background in computer science, mathematics, and statistics, often supported by a relevant degree and coursework in machine learning. Familiarity with programming languages such as Python or Swift, experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of Apple's development tools like Core ML are typically required. Strong problem-solving abilities, teamwork, and effective communication skills help you collaborate and contribute innovative solutions in a dynamic tech environment. These competencies are crucial for developing and optimizing machine learning models that power Apple's products and services.

What are some common challenges faced by entry level Apple machine learning engineers, and how can they overcome them?

Entry-level Machine Learning Engineers at Apple often encounter challenges such as adapting to the company's fast-paced innovation cycle, understanding large and complex codebases, and collaborating with cross-functional teams. To overcome these hurdles, it's important to proactively seek mentorship, participate in code reviews, and familiarize oneself with Apple's internal tools and documentation. Regular communication with peers and senior engineers can also help accelerate the learning curve and foster a collaborative environment that encourages innovation and knowledge sharing.

What is the difference between Entry Level Apple Machine Learning Engineer vs Entry Level Data Scientist?

AspectEntry Level Apple Machine Learning EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, ML, or related; knowledge of ML frameworksBachelor's in CS, Statistics, or related; strong analytical skills
Work EnvironmentTech company, R&D, product developmentData analysis, research, business insights
Employer & Industry UsageApple, consumer electronics, softwareVarious industries including tech, finance, healthcare
Common Search & ComparisonYesYes

Entry Level Apple Machine Learning Engineers focus on developing ML models for Apple products, requiring knowledge of ML frameworks and programming. Entry Level Data Scientists analyze data to derive insights, often with statistical expertise. While both roles involve data and programming, ML Engineers emphasize model deployment, whereas Data Scientists focus on data analysis and reporting.

Entry Level Apple Machine Learning Engineer jobs near you
Infographic showing various Entry Level Apple Machine Learning Engineer job openings in Emerson, NJ as of June 2026, with employment types broken down into 1% Internship, 2% As Needed, 68% Full Time, 9% Part Time, 19% Contract, and 1% Nights. Highlights an 55% Physical, 1% Hybrid, and 44% Remote job distribution, with an average salary of $70,932 per year, or $34.1 per hour.

Machine Learning Engineer

Fluidstack

Manhattan, NY • On-site

$130 - $180/hr

Other

Re-posted 5 days ago

Job description

About Fluidstack

We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.

We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.

We hire people who care deeply about this problem space. If that is you, please apply!

How We Operate
  • Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
  • Velocity. We drive everything forward as fast as possible.
  • First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
  • Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.
Role Scope
  • Build ML and LLM systems that run inside the company's operations: forecasting build timelines, flagging schedule risk, and extracting structure from vendor documents.
  • Own models end to end, from problem framing and data through deployment, evaluation, and iteration in production.
  • Ship agentic systems with real guardrails, authorization, audit, and evals, so agents act on company systems instead of just advising.
  • Partner with data engineering and product pods to put predictions in the tools people already use.
What We're Looking For
  • The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.
  • You've shipped ML or LLM features to production and owned them after launch.
  • You've built evaluation harnesses that told you the truth about model quality before users did.
  • You reach for the simplest model that works and can defend the choice.
  • You've worked hands-on with LLM APIs, fine-tuning, or retrieval systems on real business problems.
  • You write production-quality code and work fluently with AI coding tools.
  • Bonus: Forecasting or scheduling problems. Document extraction at scale. Agentic frameworks and MCP. Temporal or workflow engines.

We are committed to pay equity and transparency.

Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

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