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Mobile Machine Learning Jobs in Albuquerque, NM (NOW HIRING)

Computational neuroscience, neuro-informatics, and machine learning Researchers working in related areas that leverage advanced neuroimaging, computational methods, mobile MRI, or multidisciplinary ...

Computational neuroscience, neuro-informatics, and machine learning Researchers working in related areas that leverage advanced neuroimaging, computational methods, mobile MRI, or multidisciplinary ...

Welder 1st Shift

Albuquerque, NM

$19 - $25/hr

... mobile equipment * Utilize bridge cranes to position parts and assemblies during production ... Basic knowledge of learning and numeral ability * Must have the ability to understand blueprints ...

Welder 1st Shift

Albuquerque, NM

$19 - $25/hr

... mobile equipment * Utilize bridge cranes to position parts and assemblies during production ... Basic knowledge of learning and numeral ability * Must have the ability to understand blueprints ...

Mobile Machine Learning information

See Albuquerque, NM salary details

$11

$24

$115

How much do mobile machine learning jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for mobile machine learning in Albuquerque, NM is $24.55, according to ZipRecruiter salary data. Most workers in this role earn between $13.99 and $19.57 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 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.

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 Albuquerque, NM? The most popular types of Machine Learning jobs in Albuquerque, NM are:
What are popular job titles related to Mobile Machine Learning jobs in Albuquerque, NM? For Mobile Machine Learning jobs in Albuquerque, NM, the most frequently searched job titles are:
What job categories do people searching Mobile Machine Learning jobs in Albuquerque, NM look for? The top searched job categories for Mobile Machine Learning jobs in Albuquerque, NM are:
What cities near Albuquerque, NM are hiring for Mobile Machine Learning jobs? Cities near Albuquerque, NM with the most Mobile Machine Learning job openings:

Full-time

Posted 25 days ago


Lovelace Biomedical rating

8.7

Company rating: 8.7 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

11th of 73 rated research


Job description

Overview
The Mind Research Network (MRN), in partnership with Lovelace Biomedical Research Institute (LBRI), invites applications for a faculty position in translational neuroscience. The successful candidate will join a team of outstanding investigators who are eager to shape the future of translational neuroscience through collaborative, high-impact research that advances the understanding, diagnosis, prevention, and treatment of brain and behavioral disorders.
Recruitment is focused on exceptional investigators at the advanced assistant professor or associate professor level, although appointment and rank will be commensurate with qualifications and experience.
This recruitment coincides with the installation of a new MEGIN TRIUX™ neo magnetoencephalography (MEG) system, further expanding MRN's world-class neuroimaging capabilities. The TRIUX™ neo complements MRN's research-dedicated Siemens Prisma 3T MRI, research-dedicated mobile MRI program, and advanced neuro-informatics resources, creating an exceptional environment for innovative, multimodal translational neuroscience research.
We seek an innovative, collaborative investigator with an established or emerging independent research program who will leverage MRN's advanced neuroimaging infrastructure, multidisciplinary research community, and strategic partnerships to build a nationally recognized translational neuroscience program.
The successful candidate will join a highly collaborative scientific community where research spans advanced neuroimaging, computational neuroscience, biomarker discovery, mechanistic neuroscience, clinical investigation, and nonclinical model systems. Close collaborations across MRN, Lovelace Biomedical Research Institute, and the University of New Mexico create unique opportunities to integrate human neuroimaging with mechanistic studies, biomarker discovery, and clinical research while developing innovative, high-impact collaborative programs.
Research Areas of Interest
Candidates research should use multimodal neuroimaging-including MEG and/or MRI to investigate:
  • Neurodevelopment and brain maturation
  • Sleep, circadian rhythms, and brain health
  • Psychiatric and behavioral neuroscience
  • Translational neuroscience, including human neuroimaging, clinical investigation, and mechanistic or nonclinical model systems
  • Predictive biomarkers and precision neuroscience
  • Computational neuroscience, neuro-informatics, and machine learning

Researchers working in related areas that leverage advanced neuroimaging, computational methods, mobile MRI, or multidisciplinary collaborations are also encouraged to apply.
A Unique Research Setting
Albuquerque offers access to diverse urban, rural, tribal, and underserved populations, supporting innovative community-engaged, longitudinal, and translational neuroscience research while providing an exceptional quality of life.
Qualifications
  • Ph.D., M.D., or equivalent doctoral degree in Neuroscience, Psychology, Psychiatry, Neurology, Developmental Neurobiology, Biomedical Engineering, Cognitive Science, Public Health, or a related field and 12+ years of experience or an equivalent combination of education, training and/or experience from which comparable knowledge, skills and abilities have been attained. Must have 4 to 7 years of experience at the Associate Professor level as well as experience with external grant funding, publishing and national recognition.
  • Demonstrated success obtaining competitive extramural funding with a strong trajectory toward sustained federal support. Active federal funding is preferred.

Preferred/Additional Qualifications
  • Experience conducting multimodal neuroimaging research utilizing MRI, MEG, EEG, or related methodologies
  • Experience with longitudinal cohorts, developmental or clinical populations, community-based research, or large-scale datasets
  • Expertise in computational modeling, machine learning, predictive analytics, biomarker development, or translational neuroscience

Physical Requirements
Work is performed in a dry laboratory environment. Will operate standard office equipment and will frequently stand, walk, sit, perform desk-based computer tasks, use a telephone, perform repetitive motions and occasionally lift objects that weigh up to 20 pounds. May interact with research participants.
The above is intended to describe the general requirements for the position and should not be interpreted as an exhaustive statement of physical requirements. The Institute will provide reasonable accommodation to any employee with a disability who requires an accommodation to perform the essential functions of the position.
Salary
Salary is commensurate with experience.
Lovelace Biomedical is an Equal Opportunity Employer

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