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Remote Machine Learning Engineer Jobs in Long Branch, NJ

Quantiphi, Inc.

Senior Machine Learning Engineer

New York, NY · On-site +1

$134K - $176K/yr

... learning and growth. If working in an environment that encourages you to innovate and excel, not ... Quantiphi is an award-winning, AI-First global digital engineering company that helps the world ...

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 ... learning from others Our stack You do not need experience with all of these, but we thought you ...

Autodesk

Senior Machine Learning Test Engineer

New York, NY · On-site +1

$120K - $157K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

C the Signs

AI Data Engineer

New York, NY · On-site +1

$125K - $150K/yr

Collaborate with data scientists and machine learning engineers to understand data requirements for ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

C the Signs

AI Data Engineer

New York, NY · Remote

$117K - $140K/yr

Collaborate with data scientists and machine learning engineers to understand data requirements for ... Flexible working arrangements (remote or hybrid options available). * The opportunity to work on ...

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All JobsMachine Learning Engineer JobsRemote Machine Learning Engineer JobsRemote Machine Learning Engineer Jobs in Long Branch, NJ

Remote Machine Learning Engineer information

See Long Branch, NJ salary details

$31.1K

$127.3K

$191.2K

How much do remote machine learning engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for remote machine learning engineer in Long Branch, NJ is $127,253.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,300.00 and $153,200.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by remote machine learning engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What are the key skills and qualifications needed to thrive as a remote machine learning engineer?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a remote machine learning engineer?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

What cities near Long Branch, NJ are hiring for Remote Machine Learning Engineer jobs? Cities near Long Branch, NJ with the most Remote Machine Learning Engineer job openings:
Remote Machine Learning Engineer jobs near you
Infographic showing various Remote Machine Learning Engineer job openings in Long Branch, NJ as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $127,253 per year, or $61.2 per hour.

Senior Machine Learning Engineer, Surfaces Moments

Spotify

New York, NY • Remote

$184K - $262K/yr

Full-time

Posted 16 days ago

Job description

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

Surfaces Moments is a ML team within the Personalization Mission focused on creating moment-based experiences across Spotify surfaces. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it. By combining cutting-edge machine learning, recommendation systems, and product thinking, the team delivers highly relevant, personalized experiences to millions of listeners around the world.

As a Senior Machine Learning Engineer, you will help shape the future of personalized discovery and engagement at Spotify. You’ll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences that delight users and drive meaningful impact. This role is ideal for someone who enjoys taking models from research to production, collaborating across disciplines, and solving complex personalization challenges at global scale.

What You'll Do
  • Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience.
  • Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally.
  • Build content recommendation systems for emerging agentic and AI-powered user experiences.
  • Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches.
  • Partner closely with product managers, engineers, data scientists, and designers to define and execute experimentation strategies.
  • Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency.
  • Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale.
Who You Are
  • You have 5+ years of experience building and deploying machine learning systems in production environments.
  • You have deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.
  • You have strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.
  • You are experienced with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA.
  • You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization.
  • You care deeply about creating high-quality user experiences through thoughtful application of machine learning.
  • You communicate effectively across technical and non-technical audiences and enjoy working in highly collaborative environments.
  • You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
  • You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.
  • You are experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.
Where You'll Be
  • We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.
  • This team operates within the Eastern Standard time zone for collaboration.

The United States base range for this position is $184,050 $262,928 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.


Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
 
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice