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Mlops Contract Jobs (NOW HIRING)

Booz Allen Hamilton

MLOps Engineer, Mid

Alexandria, VA

$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 ...

Hirekeyz Inc

MLOps Engineer

San Francisco, CA · On-site

San Francisco, California Duration: Long Term Contract Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI. * Automate model training, testing ...

IT America Inc

DevOps/MLOps Engineer

Cumming, GA · On-site

$47 - $64.50/hr

Cumming, GA Duration: Long-term contract Note: Final interview will take place onsite--only local candidates will be considered * Our Fintech client is looking for an experienced DevOps / MLOps ...

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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:
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Mlops Contract jobs near you
Infographic showing various Mlops Contract job openings in the United States as of May 2026, with employment types broken down into 8% Locum Tenens, 7% Internship, 18% As Needed, 37% Full Time, 21% Temporary, and 9% Nights. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $54,445 per year, or $26.2 per hour.

ML / AI Engineer - MLOps & GenAI Platforms - AIRLHV

NavitasPartners

Austin, TX • Hybrid

Full-time

Posted 12 days ago

Job description

ML / AI Engineer – MLOps & GenAI Platforms

Location: US / Canada (Remote/Hybrid)
Type: Contract / Full-Time

Overview:

We are seeking an ML/AI Engineer to contribute to large-scale AI and data transformation programs. This role focuses on building, deploying, and scaling machine learning and GenAI solutions in cloud environments.

Key Responsibilities:

  • Design and deploy scalable ML and GenAI solutions
  • Build and manage end-to-end MLOps pipelines
  • Collaborate with data engineers, architects, and business teams
  • Ensure model performance, governance, and lifecycle management

Required Skills:

  • Strong experience in ML/AI engineering and MLOps practices
  • Proficiency in Python and frameworks such as PyTorch
  • Experience with cloud platforms (AWS, Azure, GCP)
  • Hands-on experience with model deployment and monitoring

Nice to Have / Coverage:

  • Experience with LangChain and GenAI/agentic AI implementations
  • Exposure to Databricks, Snowflake, Azure Synapse, or BigQuery
  • Familiarity with AI governance, Responsible AI, and compliance frameworks
  • Experience working with cloud-native data platforms and architectures

For more details reach at resumes@navitassols.com.