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Entry Level Machine Learning Engineer Jobs in New York, NY

Arlo

Machine Learning Engineer

New York, NY · On-site

$180K - $230K/yr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring ML Engineer to build and own the infrastructure that powers it - from training models ...

Neutral Street

Machine Learning Engineer

Manhattan, NY · On-site

$120 - $180/hr

Bridge the gap between research and production by building scalable machine learning pipelines and optimizing model inference engines. Responsibilities * Optimize inference engines for sub ...

New

Socket.dev

Machine Learning Engineer

Manhattan, NY · On-site

$180 - $230/hr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring ML Engineer to build and own the infrastructure that powers it -- from training models ...

New

Shaped

Senior Machine Learning Engineer

Brooklyn, NY · On-site

$130K - $200K/yr

We are looking for a machine learning engineer to design, build, experiment and optimize Shaped's AI discovery engine. You will be a founding engineer that works on cutting-edge technologies and ...

Shaped

Senior Machine Learning Engineer

Brooklyn, NY · On-site +1

$130K - $200K/yr

We are looking for a machine learning engineer to design, build, experiment and optimize Shaped's AI discovery engine. You will be a founding engineer that works on cutting-edge technologies and ...

NxT Level

Senior Machine Learning Engineer

Manhattan, NY

$133K - $176K/yr

Our client is a public safety product that's looking to add a machine learning engineer to their team. This particular role is focused on NLP/NLU for their real-time audio translation team. If you're ...

NxT Level

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

Our client is a public safety product that's looking to add a machine learning engineer to their team. This particular role is focused on NLP/NLU for their real-time audio translation team. If you're ...

Clearview AI

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

Senior Machine Learning Engineer Department: Engineering Employment Type: Full Time Location: New York, NY Description Clearview AI is the leading provider of facial recognition technologies to US ...

Qualcomm

Machine Learning Compiler

New York, NY · On-site

$140K - $211K/yr

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

exacare ai

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

About the Role We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the ...

Comcast

Machine Learning Engineer 2

New York, NY · On-site

$126K - $189K/yr

Innovating by contributing to the creation of patents, Application Programming Interfaces (APIs), and other intellectual property * Testing and evaluating machine learning solutions from internal and ...

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 ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in New York, NY

Entry Level Machine Learning Engineer information

See New York, NY salary details

$32.9K

$76K

$129.3K

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

As of Aug 8, 2026, the average yearly pay for entry level machine learning engineer in New York, NY is $76,001.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,400.00 and $86,000.00 per year, depending on experience, location, and employer.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in New York, NY? The most popular types of Machine Learning Engineer jobs in New York, NY are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in New York, NY? For Entry Level Machine Learning Engineer jobs in New York, NY, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in New York, NY look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in New York, NY are:
What cities near New York, NY are hiring for Entry Level Machine Learning Engineer jobs? Cities near New York, NY with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in New York, NY as of August 2026, with employment types broken down into 33% Internship, and 67% Full Time. Highlights an 33% In-person, 34% Hybrid, and 33% Remote job distribution, with an average salary of $76,001 per year, or $36.5 per hour.

Machine Learning Engineer

Arlo

New York, NY • On-site

$180K - $230K/yr

Full-time

Posted 10 days ago

Job description

Most of what makes American healthcare expensive isn't medical care. It's the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial.
Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut.
AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves.
We're already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators.
Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring ML Engineer to build and own the infrastructure that powers it - from training models on tens of millions of patients and hundreds of millions of rows of claims data, to serving real-time quotes in seconds against inference-time datasets that run into the trillions of rows. You'll also build the tooling that lets our data scientists and actuaries iterate faster than ever.
This is an ML infrastructure role with real room to do ML and data science. You'll own the platform, but you'll also have the opportunity to work alongside our data scientists and actuaries to test and evaluate your own ideas - not just support theirs.
What You'll Work On
Training infrastructure for underwriting
  • Build and own the infrastructure layer that powers our underwriting model, trained on tens of millions of patients and hundreds of millions of rows of claims data.
  • Make training reliable, reproducible, and scalable as data volume and model complexity grow.

Real-time inference for quoting
  • Build and own the API layer that produces quotes in seconds - serving a trained model against a much larger inference-time dataset, on the order of trillions of rows of claims across hundreds of millions of people.
  • Own the latency, reliability, and scalability of the serving path the quoting product depends on.

Accelerate data science iteration
  • Make it as easy as possible for data scientists and actuaries to test new features and ideas.
  • Build backtesting and validation infrastructure so model performance can be measured quickly and trustworthily.
  • Remove friction from the path between an idea and a validated, production-ready model - make experimentation simpler than it's ever been.

What We're Looking For
  • A strong track record building ML or data infrastructure in production at scale.
  • Deep proficiency in Python, with comfort in processing large datasets (Spark, Databricks, or equivalent).
  • Experience with model training pipelines and/or low-latency model serving in production.
  • Experience building tooling that makes other people faster - feature testing, experiment tracking, backtesting, or similar developer/researcher-facing infrastructure.
  • The ability to own systems end-to-end, set standards, and operate reliable production infrastructure (SLAs, monitoring, on-call).
  • Genuine interest in the modeling itself - you want to occasionally get your hands into the data science, not only the infrastructure.

Nice to Have
  • Prior experience in a regulated space like healthcare or insurance.
  • Experience with MLOps tooling (MLflow or similar), feature stores, or experimentation platforms.
  • Experience supporting data science or actuarial teams in production environments.

Compensation
$180,000 - $230,000 + equity
Why Join Arlo:
  • High ownership: You'll get real responsibility from day one-our high-trust team empowers you to run with big problems and shape core parts of the company.
  • Join an important mission: Your work directly influences how people access care and improves lives at scale.
  • Growth & expansion: We're moving fast, and as we grow, your scope will grow with us-new challenges, bigger opportunities, and rapid career velocity.
  • Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you'll use AI to fundamentally reimagine how people get healthcare.
  • High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition.

Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process.
Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law.
Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via an @joinarlo.com email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: recruiting@joinarlo.com.

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