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Hourly Remote Machine Learning Engineer Jobs in Princeton, NJ

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 ...

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Hourly Remote Machine Learning Engineer information

See Princeton, NJ salary details

$26.7K

$44.6K

$92.2K

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

As of Sep 15, 2026, the average yearly pay for hourly remote machine learning engineer in Princeton, NJ is $44,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,100.00 and $48,200.00 per year, depending on experience, location, and employer.

What does an hourly remote machine learning engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What are the key skills and qualifications needed to thrive as an hourly remote machine learning engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.

What are popular job titles related to Hourly Remote Machine Learning Engineer jobs in Princeton, NJ?

For Hourly Remote Machine Learning Engineer jobs in Princeton, NJ, the most frequently searched job titles are:

What job categories do people searching Hourly Remote Machine Learning Engineer jobs in Princeton, NJ look for?

The top searched job categories for Hourly Remote Machine Learning Engineer jobs in Princeton, NJ are:

What cities near Princeton, NJ are hiring for Hourly Remote Machine Learning Engineer jobs?

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Hourly Remote Machine Learning Engineer jobs near you
Infographic showing various Hourly Remote Machine Learning Engineer job openings in Princeton, NJ as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 72% Full Time, 25% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $44,639 per year, or $21.5 per hour.

Staff Machine Learning Engineer, Home Surfaces

New York, NY • On-site, Remote

Spotify
See more jobs at Spotifyexternal

$227K - $324K/yr

Other

Medical, Retirement, PTO

Posted 5 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 Staff 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, driving technical direction in ambiguous problem spaces, 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.
  • Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of personalization systems.
  • Mentor and support other machine learning engineers, helping raise the bar across the team.

Who You Are
  • You have 8+ 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 you influence technical decisions beyond your immediate team
  • 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 $227,495- $324,993 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

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