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Senior Embedded Machine Learning Jobs in Utah (NOW HIRING)

Senior Data Scientist

Lehi, UT · On-site +1

$133K - $213K/yr

We are seeking a Senior Data Scientist to help improve the quality and performance of Entrata's AI ... Partner with machine learning engineers to move successful experiments into production. * Develop ...

New

Job Summary : nCino is a leader in cloud banking, seeking a Senior Data Scientist to join their ... building large-scale machine learning, predictive modeling, and advanced analytics tools ...

Senior AI/ML Engineer

Draper, UT · On-site

$100 - $130/hr

You'll be a Senior AI/ML Engineer, designing and building AI-powered features like chatbots and ... Expertise in AI, machine learning, and natural language processing (NLP). * Strong communication ...

Senior Data Scientist

Lehi, UT · On-site

$107.90 - $183.40/hr

Senior Data Scientist - Overview nCino's Data & AI team is seeking a Senior Data Scientist to build ... Proficiently create machine learning models tailored to solve business problems. * Work with large ...

They are seeking an experienced Data Scientist to solve healthcare-related problems using data-driven methods and collaborate with various teams to enhance machine learning and predictive modeling ...

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems. * Mentor and guide junior data ...

Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems. * Mentor and guide junior data ...

Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems. * Mentor and guide junior data ...

Senior Data Scientist

Lehi, UT · On-site

$180 - $250/hr

Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems. * Mentor and guide junior data ...

Perception Engineer IV

Mendon, UT · On-site

$128K - $169K/yr

... machine learning, sensor-fusion, or autonomous-system softwareAdvanced proficiency in C++ and ... embedded or constrained computing platformsAdvanced experience working in Linux-based software ...

Perception Engineer IV

Mendon, UT · On-site

$128K - $169K/yr

Experience developing machine-learning solutions for detection, segmentation, classification, depth ... Experience optimizing software for GPUs, embedded computers, or real-time systems * Experience with ...

Showing results 21-40

Senior Embedded Machine Learning information

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

What are the key skills and qualifications needed to thrive as a senior embedded machine learning engineer?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are the most commonly searched types of Embedded Machine Learning jobs in Utah?

The most popular types of Embedded Machine Learning jobs in Utah are:

What cities in Utah are hiring for Senior Embedded Machine Learning jobs?

Cities in Utah with the most Senior Embedded Machine Learning job openings:

Senior Data Scientist

Entrata

Lehi, UT • On-site, Remote

$133K - $213K/yr

Full-time

Posted 2 days ago

New


Entrata rating

7.9

Company rating: 7.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

130th of 245 rated software companies


Job description

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology. Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI. With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy. At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions.

We are seeking a Senior Data Scientist to help improve the quality and performance of Entrata’s AI models and applications. This role will focus on fine-tuning strategy, training data, experimentation, evaluation, and identifying the approaches that produce the best outcomes for complex property management workflows.

Responsibilities:
  • Fine-tune and evaluate foundation models for Entrata-specific use cases using supervised fine-tuning and other post-training methods.
  • Design and curate high-quality training datasets, including instruction data, preference data, and synthetic data.
  • Develop evaluation frameworks and benchmarks to measure model accuracy, reasoning, reliability, and task performance.
  • Conduct experiments to determine which models, datasets, prompts, and training approaches perform best for specific use cases.
  • Perform model error analysis and identify opportunities to improve model behavior and output quality.
  • Partner with machine learning engineers to move successful experiments into production.
  • Develop approaches for measuring and improving model safety, consistency, and enterprise readiness.
  • Translate business and product problems into measurable machine learning objectives.
Minimum Qualifications:
  • 5+ years of experience in data science, machine learning, applied AI, or a related field.
  • Hands-on experience working with large language models, including fine-tuning, evaluation, or model adaptation.
  • Strong proficiency in Python and common machine learning frameworks.
  • Experience designing experiments, analyzing model performance, and working with large datasets.
  • Strong understanding of supervised learning, model evaluation, and statistical analysis.
  • Experience building or evaluating machine learning systems in production environments.
  • Ability to communicate technical findings clearly to engineering, product, and business stakeholders.
Preferred Qualifications:
  • Experience with supervised fine-tuning, preference optimization, or other LLM post-training techniques.
  • Experience creating synthetic training data or model-generated datasets.
  • Experience building LLM evaluation frameworks, benchmark suites, or automated quality measurement systems.
  • Familiarity with agentic AI systems, tool use, and retrieval-based applications.
  • Experience working with enterprise, financial, legal, operational, or other domain-specific AI applications.
  • Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
This band covers the full salary range for the role. Your offer within this range will depend on factors like experience, skills, and internal equity.
 
Level - P4
Benefits:
Flexible and transparent culture with remote and hybrid work options, generous vacation time, and frequent company recharge days for work-life balance.

Comprehensive medical, dental, and vision coverage, including fertility benefits, available for eligible employees and their families.

HSA/FSA options and employer-paid disability benefits provided for eligible employees.

Access to 401(k) or similar retirement plans with employer matching for eligible employees, ensuring long-term financial security.

Wellness initiatives promoting physical and mental well-being, access to an onsite gym at HQ, gym memberships, mental health resources, wellness challenges, and employee assistance programs.

Entrata Cares programs offers opportunities for volunteerism, charity events, and giving back to our community.

Exclusive Previ cell phone plan and discounts on services or local business partnerships for additional employee benefits.

Bi-annual swag drops for employees

Currently, Entrata hires in Arizona, Idaho, Utah, Wyoming, Texas, North Carolina, Florida, Georgia, South Carolina, Ohio, Pennsylvania, and Illinois for Exempt roles and Arizona, Idaho, Utah, Wyoming, Texas, North Carolina, and Florida for Non-Exempt roles. 

Entrata is dedicated to creating a workplace where a diverse and inclusive team thrives in an environment free from discrimination. We provide equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, protected veteran status, or any other applicable characteristics protected by law.

It’s a great place to work! Will you join us?

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.


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