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Mobile Machine Learning Jobs in New York (NOW HIRING)

Nelo Mobile

Data Scientist (Machine Learning)

New York, NY · On-site

$180K - $230K/yr

About Nelo Nelo is a leading consumer fintech and e-commerce platform in Mexico, with >$500MM in annualized GMV and >$70MM in annualized revenue. Our mission is to increase the buying power of ...

KARGO

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

... and mobile can do to deliver unique ad experiences across the world's most premium platforms ... multimodal learning into scalable, reliable systems that creative and product teams build on.

Kargo

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

... and mobile can do to deliver unique ad experiences across the world's most premium platforms ... multimodal learning into scalable, reliable systems that creative and product teams build on.

Square Peg Hires

[QA] - Mobile Developer

New York, NY · On-site

Familiarity with AI and machine learning integration in mobile apps. User-Centered Design: * Strong understanding of user experience (UX) and user interface (UI) design principles. * Collaboration ...

Capital One

Distinguished Mobile Engineer

New York, NY

Distinguished Mobile Engineer As a Distinguished Mobile Engineer at Capital One, you will be a part ... You will work alongside our talented team of developers, machine learning experts, product managers ...

New

Nelo Mobile

Data Scientist (NYC, L5/L6)

New York, NY · On-site

$180K - $230K/yr

Develop machine learning and causality models upon which Nelo will make underwriting and portfolio management decisions * Create credit, personalization, ranking, and pricing algorithms * Design and ...

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Mobile Machine Learning information

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$13

$27

$130

How much do mobile machine learning jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for mobile machine learning in New York is $27.71, according to ZipRecruiter salary data. Most workers in this role earn between $15.77 and $22.07 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership responsibilities, specialized knowledge, and may be found in large tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Mobile Machine Learning Engineer, and why are they important?

To thrive as a Mobile Machine Learning Engineer, you need a solid background in computer science, machine learning, and mobile application development, often supported by a relevant degree and experience. Proficiency with ML frameworks (like TensorFlow Lite or Core ML), mobile platforms (Android/iOS), and deployment tools is typically required. Strong problem-solving skills, adaptability, and effective communication set standout professionals apart in this field. These skills are crucial for successfully developing, optimizing, and integrating machine learning models into efficient and user-friendly mobile applications.

Will MLE be replaced by AI?

Mobile Machine Learning Engineers (MLEs) develop and optimize machine learning models for mobile devices. While AI technologies continue to advance, MLEs focus on implementing efficient, lightweight models suitable for mobile hardware, and their role is expected to evolve rather than be fully replaced by AI itself. Skills in model optimization, deployment, and understanding mobile constraints remain essential for MLEs.

What engineer makes $500,000 a year?

Senior machine learning engineers, including those working on mobile applications, can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning and AI, and roles in high-paying industries or companies. Achieving this level often requires advanced degrees, specialized expertise, and leadership responsibilities.

What is mobile machine learning?

Mobile machine learning refers to the development and deployment of machine learning models on mobile devices such as smartphones and tablets. It enables apps to perform tasks like image recognition, language translation, and speech processing directly on the device without needing to send data to the cloud. This approach improves privacy, reduces latency, and can work even without an internet connection. Developers use frameworks like TensorFlow Lite, Core ML, and PyTorch Mobile to optimize models for the limited resources of mobile hardware.

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

AspectMobile Machine LearningData Scientist
Required CredentialsBachelor's in CS, ML, or related; experience with mobile platformsBachelor's or higher in CS, Statistics, or related; data analysis skills
Work EnvironmentMobile app development teams, on-device processingData analysis teams, research environments
Industry UsageMobile app companies, tech startupsFinance, healthcare, tech firms
Common Search/ComparisonYesYes

Mobile Machine Learning focuses on developing ML models optimized for mobile devices and integrating them into mobile apps. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming and ML knowledge, Mobile Machine Learning emphasizes on-device deployment and mobile platform expertise, whereas Data Scientists focus on data analysis and model development for broader applications.

Which 3 jobs will survive AI?

Mobile Machine Learning professionals, data scientists, and AI system engineers are likely to continue thriving as AI advances, due to their expertise in developing, managing, and interpreting complex models. These roles require specialized skills in programming, statistics, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with AI tools and frameworks are essential for long-term job security in this field.

What are some common challenges faced by Mobile Machine Learning engineers when deploying models on mobile devices?

Mobile Machine Learning engineers often encounter challenges related to limited computational resources and memory constraints on mobile devices. Optimizing models for efficient inference without significant loss in accuracy is a key hurdle, as is ensuring compatibility across different devices and operating systems. Additionally, balancing power consumption and real-time performance is critical, so engineers frequently collaborate with mobile app developers and hardware specialists to deliver seamless user experiences while maintaining model integrity.
What are the most commonly searched types of Machine Learning jobs in New York? The most popular types of Machine Learning jobs in New York are:
What are popular job titles related to Mobile Machine Learning jobs in New York? For Mobile Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Mobile Machine Learning jobs in New York look for? The top searched job categories for Mobile Machine Learning jobs in New York are:
What cities in New York are hiring for Mobile Machine Learning jobs? Cities in New York with the most Mobile Machine Learning job openings:
Mobile Machine Learning jobs near you

Staff Machine Learning Engineer - Policy & Safety

Spotify

New York, NY • On-site

$227K - $324K/yr

Other

Medical, Retirement, PTO

Re-posted 11 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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