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Remote Machine Learning Jobs in Englewood, NJ (NOW HIRING)

Senior Machine Learning Engineer

New York, NY · On-site +1

$134K - $176K/yr

We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and ...

Senior Machine Learning Engineer

New York, NY · On-site +1

$134K - $176K/yr

We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and ...

Senior Machine Learning Engineer

New York, NY · On-site +1

$145K - $209K/yr

You enjoy working with a diverse group of people with different experiences and take pride in mentoring and learning from others Our stack You do not need experience with all of these, but we thought ...

Showing results 41-60

Remote Machine Learning information

See Englewood, NJ salary details

$26.8K

$44.7K

$92.3K

How much do remote machine learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote machine learning in Englewood, NJ is $44,688.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,100.00 and $48,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

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

The top searched job categories for Remote Machine Learning jobs in Englewood, NJ are:

What cities near Englewood, NJ are hiring for Remote Machine Learning jobs?

Cities near Englewood, NJ with the most Remote Machine Learning job openings:

Infographic showing various Remote Machine Learning job openings in Englewood, NJ as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $44,688 per year, or $21.5 per hour.

Staff Machine Learning Scientist - Personalization (Open to Remote)

Bertelsmann-Jobs

Manhattan, NY • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted just now


Job description

Company Description
Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. In publishing the best books in every genre and subject for all ages, we are committed to quality, excellence in execution, and innovation throughout the entire publishing process: editorial, design, marketing, publicity, sales, production, and distribution. Our vibrant and diverse international community of nearly 300 publishing brands and imprints include Ballantine Bantam Dell, Berkley, Clarkson Potter, Crown, DK, Doubleday, Dutton, Grosset & Dunlap, Little Golden Books, Knopf, Modern Library, Pantheon, Penguin Books, Penguin Press, Penguin Random House Audio, Penguin Young Readers, Portfolio, Puffin, Putnam, Random House, Random House Children's Books, Riverhead, Ten Speed Press, Viking, and Vintage, among others. More information can be found at http://www.penguinrandomhouse.com/.
Job Description
Penguin Random House is the largest trade publishing company in the world. The Data Science team is seeking a Staff Machine Learning Scientist to lead and advance the development of personalization products, including recommender systems for our websites, email programs, and online marketing. Personalization is a core growth lever for book discovery and customer engagement, directly improving how readers find the right books across every digital touchpoint. Improving recommendation quality and relevance has a direct downstream impact on customer experience and business outcomes.
We are investing in expanding our portfolio of business-critical personalization products and further improving our existing models. This role will own personalization and recommender system work end-to-end, from model development to deployment to output monitoring, in close partnership with business stakeholders, platform engineers, and the rest of the personalization group.
We have a mature machine learning practice and strong infrastructure, supported by strong data warehouse and DevOps partners. We are transitioning to AI-accelerated development and use modern agentic coding tools like Claude Code to speed up how we build and maintain personalization systems, with rigorous quality gates including tests, reproducible workflows, and measurable improvements in model performance and reliability. Experience with Claude Code or agentic workflows is a plus, but we prioritize strong fundamentals and the ability and willingness to learn new workflows effectively.
Specific responsibilities include:
  • Define and drive the technical roadmap for personalization and recommender systems, prioritizing roadmap items to meet business goals and defining short-term vision for the team.
  • Propose and deliver R&D that directly shapes roadmaps, multiple projects, and long-term deliverables. Models are used over the long term by multiple products and teams.
  • Design and lead the development of software used by multiple teams, ensuring long-term maintainability, scalability, and adaptability.
  • Ensure complex, multi-service personalization products meet SLAs and provide correct results over time. Adapt systems to changing business needs and resolve multi-product, multi-team service incidents.
  • Establish and enforce experimentation best practices, including A/B testing frameworks, offline evaluation methodology, and metrics design across personalization surfaces.
  • Lead team meetings, ensure the team's progress on the roadmap, and make technical decisions that unblock projects.
  • Manage stakeholders' expectations with data-driven narratives and communicate effectively with senior leadership to align on strategy and track progress.
  • Drive organizational efficiency and business impact by implementing new technologies and processes. Foster a collaborative and high-performance team culture.
  • Mentor senior and mid-level scientists, setting high code quality standards and best practices for the team.
  • Stay current with advances in recommender systems, LLMs for personalization, and representation learning, bringing relevant advances into production when they deliver measurable improvement.

Qualifications
Basic qualifications:
  • PhD in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or a related quantitative field, OR Master's with 8+ years of applied ML experience.
  • Deep expertise in recommender systems, personalization, ranking/retrieval, or computational advertising, with a track record of shipping systems that operate at scale.
  • Expert-level Python and deep proficiency with modern ML frameworks (PyTorch or TensorFlow) and recommendation-specific tooling (e.g., NVTabular, Merlin, Triton).
  • Strong experience with cloud-based ML infrastructure (AWS, Kubernetes, Databricks), containerization (Docker), and model serving at low latency.
  • Advanced SQL skills and experience architecting large-scale data pipelines and feature stores.
  • Demonstrated ability to define technical roadmaps, influence direction across teams, and make architectural decisions that hold up over time.
  • Excellent communication skills with the ability to present complex technical work to executive and non-technical audiences.
  • Be cutting edge. Use the latest AI tools to develop well-designed and robust software.

Preferred qualifications:
  • Experience building and scaling real-time recommendation services handling millions of requests.
  • Expertise in A/B testing methodology, causal inference, or experimentation platforms.
  • Familiarity with LLM-based approaches to recommendation and content understanding.
  • Experience with MLOps practices: model monitoring, feature stores, CI/CD for ML, and automated retraining pipelines.
  • Prior experience technically leading a team of ML practitioners and setting standards adopted by others.

Additional Information
The salary range for this position is $210,000 - $250,000. All positions are currently eligible for an annual profit award or bonus, subject to company results.
Applications for this role will be accepted through September 6, 2026 or until the role is filled. We encourage you to apply early, as we review applications on a rolling basis. Please include your resume and cover letter for consideration. Before applying for any role at Penguin Random House, we recommend you review our applicant resources page and our FAQs page.
Penguin Random House job postings include a good faith compensation range for each open position. The salary range listed is specific to each particular open position and takes into account various factors including the specifics of the individual role, and candidate's relevant experience and qualifications.
Full-time employees are eligible for our comprehensive benefits program. Our range of benefits include, but are not limited to, Medical/Prescription drug insurance, Dental, Vision, Health Care/Dependent Care Flexible Spending Account, Health Savings Account, Pre-Tax and Roth 401(k), Short and Long-Term Disability Insurance, Life/AD&D Insurance, Commuter Benefits, Student Loan Repayment Program, Educational Assistance & generous paid time off.
Penguin Random House values the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status.
All your information will be kept confidential according to EEO guidelines.
Disclosure requirements pertaining to the collection of your personal data:
Responsible for processing the information provided in your application is the company specified in the job advertisement, with its registered office as indicated. The company processes your data for the purpose of establishing an employment relationship on the basis of Art. 6 (1) b GDPR / Section 26 (1) sentence 1 BDSG.
The retention period for your data is determined by the statutory time limits applicable in the respective country, beginning upon completion of the recruitment process. You can find these here.
You can contact the company's Data Protection Officer at the above-mentioned postal address.
Further information on data protection and your rights can be found here.
We value the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, age, genetic information, or pregnancy.
All your information will be kept confidential according to EEO guidelines.
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