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Entry Level Machine Learning Engineer Jobs in Far Hills, NJ

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

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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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Far Hills, NJ

Entry Level Machine Learning Engineer information

See Far Hills, NJ salary details

$30.6K

$70.8K

$120.4K

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

As of Aug 12, 2026, the average yearly pay for entry level machine learning engineer in Far Hills, NJ is $70,763.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,500.00 and $80,100.00 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 cities near Far Hills, NJ are hiring for Entry Level Machine Learning Engineer jobs? Cities near Far Hills, NJ 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 Far Hills, NJ as of August 2026, with employment types broken down into 15% Internship, and 85% Full Time. Highlights an 66% In-person, 17% Hybrid, and 17% Remote job distribution, with an average salary of $70,763 per year, or $34 per hour.

Staff Machine Learning Engineer - Policy & Safety

Spotify

New York, NY • On-site

$227K - $324K/yr

Other

Medical, Retirement, PTO

Re-posted 8 days ago

Job description

We design Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
About the Team
The Policy & Safety team sits within the Content Platform domain and builds the systems that keep Spotify safe and trustworthy at scale. We own the infrastructure behind content moderation, including detection models, policy enforcement systems, compliance pipelines, and the safety-by-default platform.
Our work sits on the critical path of every new content type and product experience-from messaging and comments to collaborative and agentic features. We partner closely with Trust & Safety, Legal, and Public Affairs to ensure that as Spotify evolves, safety is built in from the start-not added later.
What You Will Do
  • Build and scale machine learning systems for proactive content detection, classification, and pre-publish safety scanning
  • Design and implement policy evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops
  • Develop multimodal models that combine text, audio, image, and video signals for safety and policy enforcement
  • Architect feedback loops that turn human reviewer input into structured training data for continuous model improvement
  • Translate regulatory requirements (e.g., precision/recall obligations, compliance reporting) into scalable ML system designs
  • Partner with cross-functional teams across Trust & Safety, Legal, Public Affairs, and Product to deliver safe user experiences
  • Drive technical direction in ambiguous problem spaces and contribute to long-term platform architecture
  • Mentor and support other machine learning engineers, helping raise the bar across the team

Who You Are
  • You have experience building and shipping production-grade machine learning systems at scale
  • You have strong expertise in ML evaluation, including dataset design, metrics, and model performance monitoring
  • You have worked with multimodal machine learning systems across text, audio, image, or video domains
  • You are experienced with human-in-the-loop systems, active learning, or feedback-driven model improvement
  • You are comfortable translating complex requirements into technical solutions, including regulatory or policy constraints
  • You have experience working across teams and influencing technical direction in large-scale systems
  • You are comfortable navigating ambiguity and making thoughtful decisions that balance speed, quality, and risk
  • You communicate clearly and collaborate effectively with both technical and non-technical stakeholders

Where You Will Be
  • This role is based in New York, NY
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States base range for this position is $227,495-$324,993 USD, 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, and paid sick leave. These ranges may be modified in the future.
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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