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Mobile Machine Learning Jobs (NOW HIRING)

Magnopus

Machine Learning Engineer II

Los Angeles, CA · On-site

$100K - $150K/yr

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product ... Experience optimizing models for performance on constrained hardware (mobile, console, etc.

NxT Level

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133.70K - $176.30K/yr

Mobile Video Streaming: The app is designed to ingest high-quality, low-latency video, transcode ... A degree in Computer Science, Machine Learning, or a related field, or equivalent professional ...

Magnopus

Machine Learning Engineer II

Los Angeles, CA

$100K - $150K/yr

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product ... Experience optimizing models for performance on constrained hardware (mobile, console, etc.

NxT Level

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133.70K - $176.30K/yr

Mobile Video Streaming: The app is designed to ingest high-quality, low-latency video, transcode ... A degree in Computer Science, Machine Learning, or a related field, or equivalent professional ...

Attentive

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115.10K - $158K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115.10K - $158K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

$107K - $146.90K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123.10K - $169.10K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123.10K - $169.10K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

$107K - $146.90K/yr

As a Senior Machine Learning Engineer, you will be responsible for building, scaling, and operating ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

$107K - $146.90K/yr

As a Senior Machine Learning Engineer, you will build and operate production-grade ML systems that ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

$107K - $146.90K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

Attentive

Senior Machine Learning Engineer

$107K - $146.90K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Attentive is a personalized mobile messaging platform that facilitates businesses with AI powered ...

FastTek

Machine Learning Engineer

Dearborn, MI

$105.20K - $126.30K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... mobile application and backend microservices. Skills Preferred: Google Cloud Platform * Google ...

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All JobsMobile Machine Learning Jobs

Mobile Machine Learning information

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$12

$25

$119

How much do mobile machine learning jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for mobile machine learning in the United States is $25.32, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $20.19 per hour, depending on experience, location, and employer.

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.

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 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.

More about Mobile Machine Learning jobs
What cities are hiring for Mobile Machine Learning jobs? Cities with the most Mobile Machine Learning job openings:
What are the most commonly searched types of Machine Learning jobs? The most popular types of Machine Learning jobs are:
What states have the most Mobile Machine Learning jobs? States with the most job openings for Mobile Machine Learning jobs include:
What job categories do people searching Mobile Machine Learning jobs look for? The top searched job categories for Mobile Machine Learning jobs are:
Mobile Machine Learning jobs near you
Infographic showing various Mobile Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 38% Full Time, 57% Part Time, 3% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $52,676 per year, or $25.3 per hour.
Machine Learning Engineer II

Machine Learning Engineer II

Magnopus

Los Angeles, CA • On-site

$100K - $150K/yr

Other

Posted 24 days ago

Job description

Magnopus is looking for a Machine Learning Engineer who thrives at the intersection of product innovation, real-time systems, and creative collaboration. In this role, you won't just build models, you'll help define how machine learning transforms our projects and unlocks entirely new experiences.
You'll partner closely with product, project, engineering, and creative teams to identify high-impact opportunities for ML, rapidly prototype solutions, and bring them into production at scale. This is a hands-on role where strategic thinking meets deep technical execution.
Responsibilities
  • Work with teams and projects to develop and implement a machine learning (ML) strategy to enhance our workflows and content generation capabilities.
  • Educate the team on what is possible with ML.
  • Build pipelines and prepare data for tuning, training, and deployment of models optimized for targeted inference.
  • Partner with teams to prototype and test ML-powered features.
  • Develop internal tools using ML to streamline workflows for production, art, animation, or audio pipelines.
  • Define, deploy, and operate agentic solutions, including integrations with MCP servers, tool definitions, and swarms of agents.
  • Create agent friendly interfaces for our tools and processes.
  • Implement models and pipelines from academic publications.
  • Remain current with ML and real-time AI trends and ensure performance scalability across platforms.

Required Qualifications
  • 4+ years full time work experience in Machine Learning, Data Engineering or related quantitative field with a track record of delivering end-to-end ML products
  • Experience building training sets, fine tuning models, building agentic systems and building and operating ML pipelines
  • Strong communication skills, and able to give clear direction and provide constructive feedback
  • Professional experience working on live-service platforms/applications

Nice to Haves
  • Experience with near real-time inference systems in games or interactive applications
  • Familiarity with generative AI (e.g., text, image, audio, or animation models)
  • Background in game development or creative tooling
  • Experience optimizing models for performance on constrained hardware (mobile, console, etc.)
  • Knowledge of MLOps best practices, including CI/CD for ML systems
  • Experience implementing solutions contemplated in academic publications

$100,000 - $150,000 a year
Magnopus is an experience focused technology company founded by a team of Oscar-winning artists, designers, and engineers from games, films, and other unusual places. We're passionate about creating rich experiences that unite the physical and digital worlds.
Because we're building the future, we endeavor to create a diverse, creative workplace where people from many perspectives collaborate across disciplines to create amazing things together. We invest in our employee's progression with ongoing education and mentorship opportunities through their guilds, and support their happiness and productivity through generous health care, time off, and other benefits.
We try to foster a safe environment where we can take risks, and learn from our failures. While we value individual talents, we favor collaboration more. We believe that the leadership of the company works for the employees, not the other way around. We feel strongly that our employees guide who we are as a company and the work we create, so we look for characteristics of curiosity, empathy, respect, honesty, and courage in every candidate.
Though we've delivered a lot of crazy stuff, here are a few you can check out at home:
Mission: ISS
Disney Pixar Coco VR
Blade Runner 2049: Memory Lab
The Lion King - Virtual Production
Elixir
We may use artificial intelligence (AI) tools to support parts of the hiring process - for example, to transcribe interviews and generate summaries. These tools are not used to review applications or analyse resumes, and they do not replace human judgement. All hiring decisions are made by people. If you would like more information about how your data is processed, please contact us.

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