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Hourly Remote Machine Learning Engineer Jobs in Utah

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 ...

... programming languages such as Python, Java and C * Familiar with one or more machine learning or ... S. pay range for this positionis $45.00 -- $55.00 hourly. Your recruiter can share more about the ...

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Hourly Remote Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as an Hourly Remote Machine Learning Engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What does an Hourly Remote Machine Learning Engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.
What are the most commonly searched types of Remote Machine Learning Engineer jobs in Utah? The most popular types of Remote Machine Learning Engineer jobs in Utah are:
What are popular job titles related to Hourly Remote Machine Learning Engineer jobs in Utah? For Hourly Remote Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Machine Learning Engineer jobs in Utah look for? The top searched job categories for Hourly Remote Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Hourly Remote Machine Learning Engineer jobs? Cities in Utah with the most Hourly Remote Machine 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