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Mobile Machine Learning Jobs in Greenwich, CT (NOW HIRING)

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users ... As a Senior Machine Learning Engineer, you'll design and scale the ML systems behind ad ranking ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users ... As a Senior Machine Learning Engineer, you'll design and scale the ML systems behind ad ranking ...

... a mobile-first, real-time payments world. With $100M in annual revenue, $1B in annualized GMV, and $140M+ raised in equity and debt, Nelo is one of the most capital-efficient consumer fintech ...

... mobile devices and web applications. Our teams are constantly pushing the boundaries of user ... Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ...

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Mobile Machine Learning information

See Greenwich, CT salary details

$13

$28

$134

How much do mobile machine learning jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for mobile machine learning in Greenwich, CT is $28.44, according to ZipRecruiter salary data. Most workers in this role earn between $16.20 and $22.69 per hour, depending on experience, location, and employer.

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 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 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 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.

What are the most commonly searched types of Machine Learning jobs in Greenwich, CT?

The most popular types of Machine Learning jobs in Greenwich, CT are:

What cities near Greenwich, CT are hiring for Mobile Machine Learning jobs?

Cities near Greenwich, CT with the most Mobile Machine Learning job openings:

Senior Machine Learning Engineer - News

5014 Disney Entertainment & Sports LLC

Manhattan, NY • On-site

$148.70 - $199.40/hr

Other

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


Job description

Senior Machine Learning Engineer - News Req ID: 10147760

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world‑class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Why You’ll Love Working Here
  • Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
  • Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans’ connections with the company’s brands and stories. Disney+, Hulu, ESPN, ABC, ABC News and many more.
  • Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.
Role Overview

The News ML team is responsible for building robust data pipelines and advanced machine learning platforms that deliver personalized experiences to users across ABC News, Good Morning America, and local news stations. Our services leverage machine learning models to enable real‑time content personalization and targeted distribution across web, mobile, and connected TV platforms, ensuring that users receive the most relevant and engaging news content tailored to their interests.

Our mission is to drive seamless, resilient, and low‑latency personalized content delivery at scale, while continuously advancing our ML infrastructure and recommendation algorithms.

Responsibilities
  • Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence.
  • Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries.
  • Drive data and ML‑driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, RAGs.
  • Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions.
  • Strategically prioritize initiatives and technical workstreams to deliver the highest‑impact and most time‑sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution.
  • Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response.
  • Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement.
  • Contribute to technical documentation and promote knowledge sharing across teams.
Qualifications
  • Bachelor’s degree in Computer Science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience.
  • 5+ years of experience building and operating ML engineering systems in production environments.
  • Expertise in data science, deep learning algorithms, or statistical methods to solve real‑world engineering problems.
  • Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low‑latency online serving.
  • Experience designing and developing backend microservices for large‑scale distributed systems using REST.
  • Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize).
  • Familiarity with developing and deploying Spark and ML pipelines.
  • Hands‑on experience with big data technologies such as Databricks, Kinesis, Kafka.
  • Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals.
  • Experience with observability tools for metrics, logging, and monitoring such as Datadog.
  • Experience working in Agile/Scrum development environments.
  • Excellent communication skills and a commitment to collaboration in a fast‑paced, guest‑focused environment.
Compensation

The hiring range for this position in New York, NY is $148,700 - $199,400 per year and in Glendale, CA is $141,900 - $190,300 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

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