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Mlops Contract Jobs (NOW HIRING)

MLOPS Engineer

Malvern, PA · On-site

$50 - $60/hr

Contract * Knowledge of MLOps platforms * Good experience with Sage Maker * Proven 8+ years of professional experience across MLOps, DevOps, or similar disciplines. * Knowledge in the life cycle ...

Job Title MLOps Engineer to work on AWS GovCloud Databricks Projected Start Date05-09-2025 Projected End Date10-31-2025 Position Type Contract Location : Bellevue, WA Remote Work100% Primary ...

Contract * 4 to 6 years of strong experience with AWS Gov Cloud environments Export Control FedRAMP ... MLOps architecture with practical expertise in Databricks Unity Catalog MosaicAI serverless ...

You will lead by influence across MLOps, Autonomy, Data Platform, and TeleOp - establishing the standards, contracts, and tooling that turn one-off research code into a repeatable, auditable pipeline ...

MLOps Engineer, Mid

Chantilly, VA · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... as well as contract-specific affordability and organizational requirements. The projected ...

R0241240 MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a ... as well as contract-specific affordability and organizational requirements. The projected ...

MLOps Engineer, Mid

Aurora, CO · On-site

$77K - $176K/yr

MLOps Engineer, Mid The Opportunity : Are you looking for an opportunity to make a difference and ... as well as contract-specific affordability and organizational requirements. The projected ...

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Mlops Contract information

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How much do mlops contract jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for mlops contract in the United States is $26.18, according to ZipRecruiter salary data. Most workers in this role earn between $20.19 and $28.61 per hour, depending on experience, location, and employer.

What is an MLOps contract?

An MLOps contract refers to a temporary or project-based agreement for professionals who specialize in Machine Learning Operations (MLOps). MLOps combines machine learning, software engineering, and DevOps practices to streamline the deployment, monitoring, and management of machine learning models in production. These contracts typically require expertise in automation, CI/CD pipelines, cloud platforms, and model lifecycle management. Contractors are often hired to help organizations quickly implement or scale their machine learning infrastructure, ensuring models are reliable, scalable, and secure.

What are the key skills and qualifications needed to thrive as an MLOps Contract professional, and why are they important?

To thrive as an MLOps Contract professional, you need solid experience in machine learning, software engineering, and cloud infrastructure, often supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and platforms such as AWS, Azure, or GCP, along with certifications like AWS Certified Machine Learning or Google Professional ML Engineer, is highly valuable. Strong problem-solving, communication, and collaboration skills help you deliver robust solutions and work effectively with cross-functional teams. These skills ensure efficient deployment, scalability, and maintenance of machine learning models in production environments.

What is the difference between Mlops Contract vs Data Engineer?

AspectMlops ContractData Engineer
Required CredentialsCertifications in cloud platforms, scripting, and ML toolsDegree in Computer Science or related field, SQL, Python skills
Work EnvironmentProject-based, contract roles in cloud and ML teamsFull-time or contract, data pipeline development in data teams
Employer & Industry UsageTech companies, startups, consulting firmsLarge enterprises, finance, healthcare, tech
Search & Comparison IntentUnderstanding contract roles in ML operationsData pipeline and infrastructure roles

While both roles involve working with data and cloud tools, Mlops Contract focuses on deploying and maintaining machine learning models in production environments on a contractual basis. Data Engineers primarily build and manage data pipelines and infrastructure. The roles overlap in skills like scripting and cloud familiarity but differ in scope and responsibilities.

What are some common challenges faced by MLOps contractors when integrating machine learning models into existing production systems?

MLOps contractors often encounter challenges such as aligning model deployment processes with an organization's existing infrastructure and ensuring seamless collaboration between data science and engineering teams. They must navigate differences in technology stacks, manage versioning of models and datasets, and address issues related to scalability and monitoring in production environments. Effective communication and a thorough understanding of both machine learning workflows and DevOps practices are key to overcoming these hurdles and delivering reliable, maintainable solutions.
More about Mlops Contract jobs
What cities are hiring for Mlops Contract jobs? Cities with the most Mlops Contract 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 Mlops Contract jobs? States with the most job openings for Mlops Contract jobs include:
What job categories do people searching Mlops Contract jobs look for? The top searched job categories for Mlops Contract jobs are:
Infographic showing various Mlops Contract job openings in the United States as of June 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $54,445 per year, or $26.2 per hour.
MLOPS Engineer

MLOPS Engineer

Siri InfoSolutions Inc

Malvern, PA • On-site

$50 - $60/hr

Contractor

Posted 16 days ago


Job description

Role: MLOps Engineer

Location: Malvern, PA / Raleigh, NC or USA Any LOcation (Onsite)

Duration: Contract

  • Knowledge of MLOps platforms
  • Good experience with Sage Maker
  • Proven 8+ years of professional experience across MLOps, DevOps, or similar disciplines.
  • Knowledge in the life cycle management of Machine Learning models.
  • Proficiency with Machine Learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • An in-depth understanding of contemporary software engineering techniques.
  • Docker, Kubernetes, and/or Python or R expertise.
  • Expertise in cloud computing systems, including AWS, Azure, and GCP.
  • Working experience with version control systems such as Git, automation tools, and CI/CD pipelines

Siri Infosolutions logo

About Siri Infosolutions

Sourced by ZipRecruiter

Our team of experts first gather each and every requirement of yours. Our research and development team then sit around those requirements and come up with a plan. Our implementation team then executes that plan for optimal results. After that our support team remains in constant touch with you during and after the entire process.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

Edison, NJ, US

Year founded

2005