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Remote Aws Machine Learning Jobs in Utah (NOW HIRING)

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$98K - $134K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Senior Data Scientist

Lehi, UT · On-site +1

$133K - $213K/yr

Partner with machine learning engineers to move successful experiments into production. * Develop ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Partner with machine learning engineers to move successful experiments into production. * Develop ... Flexible and transparent culture with remote and hybrid work options, generous vacation time, and ...

Lead Data Scientist

Draper, UT · On-site +1

$144K - $250K/yr

Advanced machine learning modeling and/or technical expertise in developing market differentiation ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

... eligible for remote or hybrid work. The IT Enterprise Cloud Architect to lead the design ... Design and evolve enterprise AWS cloud architecture * Establish governance and best practices

... eligible for remote or hybrid work. The IT Enterprise Cloud Architect to lead the design ... Design and evolve enterprise AWS cloud architecture * Establish governance and best practices

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Remote Aws Machine Learning information

What is a remote AWS Machine Learning job?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

What are the key skills and qualifications needed to thrive as a remote AWS Machine Learning engineer?

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.

What is the difference between Remote Aws Machine Learning vs Remote Data Scientist?

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

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

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

What are popular job titles related to Remote Aws Machine Learning jobs in Utah?

For Remote Aws Machine Learning jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Remote Aws Machine Learning jobs in Utah look for?

The top searched job categories for Remote Aws Machine Learning jobs in Utah are:

What cities in Utah are hiring for Remote Aws Machine Learning jobs?

Cities in Utah with the most Remote Aws Machine Learning job openings:

Senior Machine Learning Engineer

Lehi, UT • On-site, Remote


Entrata
Software Development • 1 - 5K employees

7.9

Company rating: 7.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

130th of 247 rated software companies

Good employer

Paid breaks

Recommended by parents


$144K - $233K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 14 days ago


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 Machine Learning Engineer to help build and scale Entrata's applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management use cases, building reliable model training and evaluation pipelines, and deploying AI systems into production.

Responsibilities
  • Fine-tune and adapt large language models for Entrata-specific use cases using supervised fine-tuning and other post-training techniques.
  • Build scalable data preparation, curation, filtering, and synthetic data pipelines to support model training and evaluation.
  • Develop agentic AI systems that can reason across multi-step workflows, use tools, retrieve context, and operate reliably in production.
  • Build evaluation frameworks and benchmarks to measure model quality, safety, reliability, and task performance.
  • Optimize model inference, serving, and deployment for performance, cost, and scalability.
  • Partner with engineering, product, and data teams to integrate AI capabilities into Entrata products and workflows.
  • Help establish best practices for model experimentation, fine-tuning, evaluation, and deployment.
Minimum Qualifications
  • 5+ years of software engineering or machine learning engineering experience.
  • Hands-on experience fine-tuning, adapting, or deploying large language models.
  • Strong proficiency with Python and PyTorch or similar deep learning frameworks.
  • Experience building ML data pipelines, training workflows, and evaluation systems.
  • Experience deploying machine learning models into production environments.
  • Familiarity with modern LLM tooling, model serving, and inference frameworks.
  • Strong understanding of machine learning fundamentals and model performance tradeoffs.
Preferred Qualifications
  • Experience with supervised fine-tuning, preference optimization, or related post-training techniques.
  • Experience building agentic systems, tool-using models, or retrieval-based AI applications.
  • Experience with distributed training or GPU-based model workloads.
  • Familiarity with frameworks such as vLLM, DeepSpeed, FSDP, or similar technologies.
  • Experience working with enterprise or domain-specific AI applications.
  • Bachelor's or advanced degree in Computer Science, Machine Learning, Engineering, or a related field, or equivalent practical experience.
$144,000 - $233,100 a year
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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