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Remote Deep Learning Engineer Jobs in Utah (NOW HIRING)

Senior Machine Learning Engineer

Draper, UT · On-site +1

$145.70K - $174.80K/yr

Whether in one of our offices in San Jose, CA, Draper, UT, or in a remote-eligible role, BILLders ... As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ...

This freelance role is fully remote and offers flexible hoursyou can contribute whenever it fits ... Were looking for people with * 2+ years of experience in backend engineering, AI automation, or ...

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Remote Deep Learning Engineer information

See Utah salary details

$10K

$76.4K

$127.5K

How much do remote deep learning engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for remote deep learning engineer in Utah is $76,367.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,500.00 and $126,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Deep Learning Engineer, and why are they important?

To thrive as a Remote Deep Learning Engineer, you need a strong background in machine learning, deep learning frameworks, and programming languages like Python, usually supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (e.g., AWS, GCP), and version control systems is typically required, with certifications in AI or cloud technologies being advantageous. Excellent problem-solving, communication, and self-management skills make candidates stand out in remote environments. These skills and qualities are essential for developing effective AI solutions, collaborating across distributed teams, and driving innovation in the fast-evolving field of deep learning.

How do Remote Deep Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Deep Learning Engineers frequently collaborate with data scientists, product managers, and software engineers using digital tools such as Slack, Zoom, and collaborative code platforms like GitHub. Regular virtual meetings and sprint planning sessions help ensure alignment on project goals and milestones. Clear documentation and asynchronous communication are crucial for effective teamwork, especially when team members are in different time zones. This collaborative structure enables remote engineers to contribute meaningfully to model development, deployment, and integration while maintaining flexibility.

What is a Remote Deep Learning Engineer?

A Remote Deep Learning Engineer is a professional who works primarily online to design, develop, and implement deep learning models and algorithms. These engineers use neural networks and large datasets to solve complex problems in fields like computer vision, natural language processing, and more. Working remotely, they collaborate with team members via digital tools, write code, optimize models, and often deploy solutions to cloud environments. This role requires strong programming skills, experience with deep learning frameworks (like TensorFlow or PyTorch), and the ability to work independently in a distributed team setting.

What is the difference between Remote Deep Learning Engineer vs Remote Machine Learning Engineer?

AspectRemote Deep Learning EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with deep learning frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch and development, model training, neural network designData analysis, model deployment, algorithm development
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce

Remote Deep Learning Engineers focus on designing and training neural networks for complex AI tasks, while Remote Machine Learning Engineers work on broader ML models and algorithms. Both roles require strong programming skills and knowledge of machine learning frameworks, but Deep Learning Engineers specialize in neural networks and large-scale data processing.

What are the most commonly searched types of Deep Learning Engineer jobs in Utah? The most popular types of Deep Learning Engineer jobs in Utah are:
What job categories do people searching Remote Deep Learning Engineer jobs in Utah look for? The top searched job categories for Remote Deep Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Remote Deep Learning Engineer jobs? Cities in Utah with the most Remote Deep Learning Engineer job openings:
Senior Staff Machine Learning Engineer, (Machine Learning)

Senior Staff Machine Learning Engineer, (Machine Learning)

Affirm

Salt Lake City, UT • On-site, Remote

$101.10K - $138.90K/yr

Full-time

Medical

This job post has expired today. Applications are no longer accepted.


Job description

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. Join the team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to affirming the mission of revolutionizing financial services with transparency and inclusivity at its core.

What You'll Do You will define and drive multi-year, multi-team technical strategy for machine learning across affirm, ensuring alignment with company-wide priorities and influencing the roadmaps of partner teams and platforms. You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads. You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next-generation ML methods.

You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross-org guidance. You will drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions, balancing competing priorities, and exercising judgement optimized for the broader engineering organization. You will champion operational and system excellence at the area level, owning the long-term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams.

What We Look For You have 10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE. You have experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment.

You use distributed frameworks such as Spark, Ray, or similar large-scale data processing systems. You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.

You have a strong understanding of representation learning and embedding-based modeling. You possess deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale.

You have deep hands‐on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining. You provide strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.

You demonstrate exceptional judgement, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning. You have strong verbal and written communication skills that support effective collaboration across our global engineering organization.

This position requires equivalent practical experience or a Bachelor's degree in a related field. Remote Affirm is proud to be a remote‐first company! The majority of our roles are remote and you can work almost anywhere within the country of employment.

A limited number of roles remain office‐based due to the nature of their job responsibilities. Benefits Health care coverage – affirm covers all premiums for all levels of coverage for you and your dependents. Flexible Spending Wallets – generous stipends for spending on technology, food, lifestyle needs, and family‐forming expenses.

Time off – competitive vacation and holiday schedules allowing you to take time off to rest and recharge. ESPP – an employee stock purchase plan enabling you to buy shares of affirm at a discount. We believe it's On Us to provide an inclusive interview experience for all, including people with disabilities.

We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. By clicking "Submit Application," you acknowledge that you have read affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein. #J-18808-Ljbffr