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Temporary Mlops Jobs (NOW HIRING)

Amazon

Data Engineer, OIS/CXI Analytics

Austin, TX

$113K - $136K/yr

You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and ... as seasonal or temporary employment. The benefits that generally apply to regular, full-time ...

Amazon

Data Engineer, OIS/CXI Analytics

Austin, TX

$113K - $136K/yr

You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and ... as seasonal or temporary employment. The benefits that generally apply to regular, full-time ...

Uottawa

APTPUO-Fall 2026-DTI6302 F

Campus, IL

$239.47/hr

Professeur a temps-partiel regulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/05 ... They should have hands-on experience applying the latest MLOps techniques, such as continuous ...

AllSTEM Connections

Backend AI Engineer

San Francisco, CA · On-site

$228K/yr

... MLOps tools (MLflow, Kubeflow, SageMaker Pipelines) and Infrastructure as Code (Terraform ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

UST Inc

Senior AI/ML Engineer

Denver, CO · On-site

$106K - $159K/yr

Experience with MLOps tools/platforms * Exposure to Generative AI / LLMs (prompt engineering ... Full-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires ...

TEKsystems

OpenShift Engineer

Denver, CO · Hybrid

$90 - $100/hr

AI/ML infrastructure (GPU-enabled clusters, MLOps) * Familiarity with: * Cloud management ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

AllSTEM Connections

Sr Software Dev Engineer

La Honda, CA · On-site

$126K - $185K/yr

Senior ML Infrastructure & MLOps Engineer (Core Platform) Role Overview We are seeking an ownership ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

T-Mobile

Senior Data Science Engineer

Philadelphia, PA · On-site

$116K - $210K/yr

... MLOps and DevOps practices and tools. (Required) * 4-7 years Experience working within big data ... At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic ...

Avathon

Senior AI Engineer

Pleasanton, CA

$130K - $155K/yr

Knowledge of MLOps practices, CI/CD for ML (Travis CI, Jenkins), and model lifecycle management ... temporary roles are not eligible for the above benefits. Compensation Pay Range: $130k - $155k ...

CRC Group

Software Engineer - Machine Learning

Charlotte, NC · On-site

$95K - $130K/yr

Regular or Temporary: Regular Language Fluency: English (Required) Work Shift: 1st Shift (United ... Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.

Monitise

AI Engineer

Alpharetta, GA · On-site

Experience with MLOps practices and tooling (for example, CI/CD for models, model registries ... Individuals with temporary visas including, but not limited to, F-1 (OPT, CPT, STEM), H-1B, H-2, or ...

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Temporary Mlops information

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How much do temporary mlops jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for temporary mlops in the United States is $18.38, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $19.95 per hour, depending on experience, location, and employer.

What is a Temporary MLOps role?

A Temporary MLOps role involves supporting machine learning operations on a short-term or contract basis. Professionals in this position are responsible for deploying, managing, and maintaining machine learning models and the infrastructure around them, ensuring efficient workflows and scalability. Temporary MLOps specialists may work on specific projects, help with pipeline automation, or assist with transitioning models from development to production. Their work helps organizations streamline ML processes and minimize downtime, even if only for a limited period.

What are the typical challenges faced by professionals in a Temporary MLOps role?

In a Temporary MLOps role, professionals often encounter the challenge of rapidly integrating into existing teams and workflows, as well as quickly familiarizing themselves with company-specific tools and infrastructure. They are expected to efficiently support the deployment, monitoring, and maintenance of machine learning models, frequently under tight deadlines. Additionally, adapting to diverse project requirements and collaborating with data scientists, engineers, and IT staff within a limited timeframe can be demanding. However, this role provides valuable exposure to various MLOps practices and technologies, which can be advantageous for future career growth.

What are the key skills and qualifications needed to thrive as a Temporary MLOps Engineer, and why are they important?

To thrive as a Temporary MLOps Engineer, you need strong knowledge of machine learning workflows, software development, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, TensorFlow, CI/CD pipelines, and cloud platforms (AWS, GCP, or Azure) is essential, as are certifications in cloud services or DevOps. Excellent problem-solving, adaptability, and collaboration skills help you integrate seamlessly into teams and ensure smooth project handovers. These competencies enable efficient deployment, monitoring, and maintenance of ML models in production environments, ensuring project continuity and reliability.

What is the difference between Temporary Mlops vs Data Engineer?

AspectTemporary MlopsData Engineer
Required CredentialsRelevant certifications in cloud platforms, scripting, and ML toolsDegree in Computer Science, Data Science, or related field; SQL and programming skills
Work EnvironmentProject-based, short-term contracts, often in cloud or AI-focused teamsLong-term, ongoing data infrastructure development in various industries
Employer & Industry UsageTech companies, startups, AI firmsFinancial, healthcare, tech, and other data-driven industries

Temporary Mlops roles focus on short-term deployment and management of ML systems, often requiring cloud and scripting skills. Data Engineers build and maintain data pipelines over the long term. While both roles involve data and cloud tools, Temporary Mlops positions are more specialized in ML deployment, making them distinct in scope and duration.

More about Temporary Mlops jobs
What cities are hiring for Temporary Mlops jobs? Cities with the most Temporary Mlops job openings:
What are the most commonly searched types of Mlops jobs? The most popular types of Mlops jobs are:
What states have the most Temporary Mlops jobs? States with the most job openings for Temporary Mlops jobs include:
What job categories do people searching Temporary Mlops jobs look for? The top searched job categories for Temporary Mlops jobs are:
Temporary Mlops jobs near you
Infographic showing various Temporary Mlops job openings in the United States as of May 2026, with employment types broken down into 3% Locum Tenens, 85% Full Time, and 12% Temporary. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $38,238 per year, or $18.4 per hour.
Data Engineer, OIS/CXI Analytics

Data Engineer, OIS/CXI Analytics

Amazon

Austin, TX

$113K - $136K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 12 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,823 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers

Job description

Join the OIS/CXI Analytics team to build strategic data infrastructure powering Amazon's Operations Technology ecosystem. Our team provides critical data infrastructure support for OpsTech IT, supporting Amazon's global customer commitment. You'll work at the intersection of large-scale data processing and real-world operational impact - creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, and Amazon Campus.


As a Data Engineer, you will build and maintain scalable data pipelines and ML-ready data infrastructure that power AI-driven operational insights and Data Science initiatives across Amazon's global fulfillment and maintenance networks. You will design and implement ETL/ELT pipelines, build feature engineering workflows, and partner with ML Engineers, Data Scientists, Applied Scientists, and BIEs to deliver data products that drive measurable business outcomes. You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and model retraining data support - and help establish engineering best practices within the team.

You will support Data Science teams by building curated, analysis-ready models and datasets and enabling self-service data access through well-governed data infrastructure. This role directly enables the team's mission to implement GenAI solutions for automated reporting, diagnostics, and predictive and prescriptive analytics across worldwide operations.
This is a high-impact individual contributor role with significant opportunity to grow technical scope and organizational influence at the intersection of data engineering, Data Science, and AI.


Key job responsibilities
- Design, build, and maintain production-grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence.
- Build feature engineering workflows and ML-ready data pipelines that support Data Science experimentation and production model serving.
- Contribute to data governance and quality standards across analytical and ML data products.
- Support implementation of GenAI solutions for automated reporting, diagnostic, predictive, and prescriptive analytics.
- Build and maintain semantic layers and dashboard data models that power worldwide operations business decisions.
- Partner with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS business goals.
- Follow and contribute to best practices for data engineering, including code reviews, testing, monitoring, and documentation.
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1

Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4.

401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you. At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!.

What Amazon employees say

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Benefits

Hours and flexibility

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Get the full story on Breakroom

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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