ZipRecruiter

Log In

1

Mlops Contract Jobs (NOW HIRING)

Inficare Technologies

AI Python Engineer

Phoenix, AZ · On-site

Phoenix, AZ (Hybrid - 3 days onsite) Job Type: Long-Term Contract Experience: 10+ years Job ... Contribute to cloud-native ML pipelines and AI application deployment using MLOps, APIs, Docker ...

Ampcus Inc

Machine Learning Engineer

... end-to-end MLOps pipelines for data prep, training, validation, packaging, and deployment. • Develop FastAPI microservices for model inference with clear API contracts, versioning, and ...

Mondo

Data Scientist

Phoenix, AZ · Remote

$65 - $75/hr

Contract, 6 Months (extension likely) Compensation Range: $65/hr to $75/hr Benefits: Eligible for ... This role requires hands on MLOps maturity, not just model building, the candidate will own how ...

KAPITAL

Microsoft AI Architect

Boston, MA · On-site

Microsoft AI Architect Duration: 6+ months Contract Location: Boston, MA - 2-4 days onsite; must be ... Experience with LLMs, RAG, vector search, APIs, data pipelines, and MLOps . * Strong enterprise ...

Gain America

AI / ML Engineer - Remote (US)

Hicksville, NY · On-site +1

$135K/yr

Gain America is recruiting a AI / ML Engineer for contract and contract-to-hire engagements with ... Python, LLMs, PyTorch, RAG, vector databases, MLOps What you'll do * Build and fine-tune ML and LLM ...

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Contract To Hire Visa : USC, GC, EAD (Only W2, No Sponsorship) Responsibilities * Optimize and ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Contract To Hire Visa : USC, GC, EAD (Only W2, No Sponsorship) Responsibilities * Optimize and ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Contract To Hire Visa : USC, GC, EAD (Only W2, No Sponsorship) Responsibilities * Optimize and ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Contract To Hire Visa : USC, GC, EAD (Only W2, No Sponsorship) Responsibilities * Optimize and ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

previous page

Showing results 41-60

All Jobsfreelance JobsTechnology JobsMlops Contract Jobs

Mlops Contract information

See salary details

$17

$26

$49

How much do mlops contract jobs pay per hour?

As of Sep 5, 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 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.

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.

Is MLOps in high demand?

MLOps roles are in high demand due to the increasing adoption of machine learning and AI across industries. Professionals with skills in cloud platforms, automation, and tools like Docker, Kubernetes, and CI/CD pipelines are particularly sought after. The field offers strong job growth prospects and competitive salaries for qualified candidates.
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:

Mlops Contract jobs near you
Infographic showing various Mlops Contract job openings in the United States as of August 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $54,445 per year, or $26.2 per hour.

ML Systems Engineer - Fully Remote | Upto $110/hr

Mercor

San Francisco, CA • Remote

$110/hr

Full-time

This job post has expired 5 days ago. Applications are no longer accepted.

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: MLOps Engineer (JAX, PyTorch, Pallas/Triton)
Type: Contract
Compensation: $70–$110/hour
Location: Remote
Commitment: 40 hours/week

Role Responsibilities

  • Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics.
  • Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to MLOps and ML systems problems.
  • Evaluate MLOps tasks and solutions and provide clear, written technical feedback.
  • Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks.
  • Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Qualifications

Must-Have

  • 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization.
  • Hands-on production experience with JAX and/or PyTorch at scale.
  • Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton.
  • Demonstrable career progression.
  • Ability to engage reliably for at least 40 hours/week during weekdays.
  • Strong written communication skills and the ability to explain complex technical decisions clearly.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.