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Mobile Machine Learning Jobs in Massachusetts (NOW HIRING)

Lila Sciences

Scientist I / II, Robotics

Cambridge, MA · On-site

Experience with dual-arm mobile manipulation systems or other high-DOF robotic platforms * Familiarity with simulation tools such as Gazebo, Isaac Sim, or PyBullet * Background in machine learning ...

STR

Lead Software Engineer / Back-End Developer

Woburn, MA

$180K - $220K/yr

... machine learning-based solutions to solve challenging problems related to national security. Our ... Knowledge of Mobile Operating System (iOS/Android) and mobile based applications * Expertise in OOP ...

New

Telus Digital

$185K - $224K/yr

From mobile apps and websites to voice UI, chatbots, AI, customer service, and in-store solutions ... Drawing on your deep knowledge of data ecosystems, machine learning, and AI technologies, you'll ...

ICONSTAFF

Principal Software Engineer

Cambridge, MA

$190K - $210K/yr

We are looking for a collaborative, customer-focused, and creative principal software engineer to develop a high-performance mobile application framework that powers on-device machine learning models ...

Apply Early

Aquila Technology

Software Developer

Lexington, MA

Machine Learning/AI * Implementing machine learning models and knowledge of ML training * C/C ... Mobile user interface design principles * Mobile user analytics * Relational Databases (e.g ...

Aquila Technology

Software Developer

Lexington, MA

Machine Learning/AI * Implementing machine learning models and knowledge of ML training * C/C ... Mobile user interface design principles * Mobile user analytics * Relational Databases (e.g ...

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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 4, 2026, the average hourly pay for mobile machine learning in Massachusetts is $27.66, 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 Massachusetts? The most popular types of Machine Learning jobs in Massachusetts are:
What are popular job titles related to Mobile Machine Learning jobs in Massachusetts? For Mobile Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Mobile Machine Learning jobs in Massachusetts look for? The top searched job categories for Mobile Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Mobile Machine Learning jobs? Cities in Massachusetts with the most Mobile Machine Learning job openings:
Mobile Machine Learning jobs near you

Scientist I / II, Robotics

Lila Sciences

Cambridge, MA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You'll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

  • Design and develop autonomous robotic systems for transport and workcell operations, integrating advanced path planning, navigation, and motion planning algorithms
  • Build production-grade mobile manipulation platforms leveraging ROS/ROS2 and modular robotic architectures
  • Advance robotic perception by integrating sensing modalities such as 3D vision, LIDAR, and tactile sensors to enable robust, adaptable task execution
  • Use simulation environments to model, test, and optimize task planning, scheduling, and robot behaviors in diverse lab scenarios
  • Collaborate with AI, mechanical, and software engineering teams to translate theoretical robotics research into real-world autonomous systems

What You'll Need to Succeed

  • Ph.D. in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field, or equivalent research experience
  • Expertise in motion planning, path planning, and navigation for manipulation and mobile robotics
  • Proficiency with ROS/ROS2, C++, and Python, with hands-on experience building robotic systems in real-world environments
  • Deep understanding of perception systems and sensor integration (e.g., camera, LIDAR, tactile sensors)
  • Proven ability to take robotic systems from concept through to deployment

Bonus Points For

  • Experience with dual-arm mobile manipulation systems or other high-DOF robotic platforms
  • Familiarity with simulation tools such as Gazebo, Isaac Sim, or PyBullet
  • Background in machine learning for perception, control, or adaptive planning
  • Experience with real-time decision-making in human-robot collaboration scenarios
  • Strong publication or patent record in robotics, autonomy, or perception

Apply