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Mlops Contract Jobs (NOW HIRING)

Staffingine LLC

AIML Engineer

Scottsdale, AZ · On-site

Contract to Hire * Design and implement scalable MLOps supportive data pipelines for data ingestion processing and storage * Experience deploying models with MLOps tools such as Vertex Pipelines ...

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 ...

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 ...

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 ...

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Mlops Contract information

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$17

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How much do mlops contract jobs pay per hour?

As of Aug 10, 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.
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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 92% Full Time, 1% Part Time, and 7% Contract. Highlights an 71% Physical, 10% Hybrid, and 19% Remote job distribution, with an average salary of $54,445 per year, or $26.2 per hour.

Senior MLOps Platform Engineer {S}

ARKA Group

Colorado Springs, CO • On-site, Remote

$90K - $123K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 23 days ago

Job description

ARKA Group L.P. (“ARKA”) is an advanced technologies company serving the U.S. military, intelligence community, and commercial space industry delivering next-generation solutions to support the national security space enterprise. Built on more than six decades of excellence, ARKA brings modern approaches and a culture of innovation to the challenges of today.

Join the ARKA team to learn how Beyond Begins Here. Discover your next career opportunity now!

Position Overview:

Our AI Center of Excellence builds the next generation of Agentic AI products that autonomously reason, plan, and act on behalf of our customers. To deliver these capabilities at scale, we need a platform engineering group that provides a robust, secure, and highly available MLOps foundation across both on premise clusters and AWS. The team works closely with data scientists, product engineers, and SREs to turn experimental models into reliable services that power mission critical applications. 

In support of work/life balance, many positions are available for a flexible schedule within the pay period.  Ask us about the opportunity for flex scheduling if that’s of interest to you. 

Why join us 

  • Shape the end-to-end lifecycle of cutting-edge AI services—from model training to production inference. 
  • Influence architecture decisions for a hybrid cloud environment that will serve thousands of concurrent agents. 
  • Collaborate with world-class researchers and product teams while enjoying a strong engineering culture focused on automation, observability, and reliability. 

      Responsibilities: 

      • Design, implement, and operate a unified MLOps platform that supports both on-premise Kubernetes clusters and AWS. The platform should enable rapid onboarding of new Agentic AI services and provide consistent governance across environments. 
      • Develop reusable CI/CD pipelines (GitLab CI) for model packaging, containerization, automated testing, canary releases, and rollbacks. 
      • Build observability, monitoring, and alerting stacks (Prometheus, Grafana, OpenTelemetry, CloudWatch) to track inference latency, throughput, resource utilization, and data drift for real time and batch workloads. 
      • Create self-service tooling (CLI, SDKs, UI dashboards) that allows data science and product teams to register models, define inference endpoints, and manage versioning without deep DevOps involvement. 
      • Architect and maintain data pipelines that feed training data, model artifacts, and inference logs into a governed data lake (S3, on prem object store). 
      • Collaborate with research and product engineers to translate experimental Agentic AI prototypes into production grade services, ensuring reproducibility, security, and compliance. 
      • Drive performance optimization for inference workloads (GPU/CPU scaling, model quantization, batching strategies) 
      • Champion best practices in security (IAM, network policies, secret management), cost efficiency, and disaster recovery for the hybrid infrastructure. 
      • Mentor junior engineers and contribute to internal knowledge bases, upskilling, and review processes. 

      Required Qualifications:

      • BS in computer science or related engineering field
      • 5+years of experience building and operating production grade software infrastructure, preferably in a hybrid onprem / cloud environment
      • Deep expertise with Kubernetes (cluster provisioning, Helm, operators, custom resources) and container runtimes (Docker, OCI)
      • Hands on experience with AWS services (EKS, SageMaker, S3, IAM, CloudWatch, Step Functions) and the ability to bridge onprem resources with AWS via VPN/Direct Connect
      • Strong software engineering skills in Python and at least one compiled language (Go, Rust, or Java) for building platform components and SDKs
      • Proficiency with CI/CD and GitOps tooling (Argo CD, Flux, Gitlab, GitHub Actions, or similar)
      • Solid understanding of distributed systems (consensus, fault tolerance, load balancing) and experience tuning high throughput, low latency inference pipelines
      • Experience with data engineering frameworks (Airflow, Prefect, Kafka, Spark, Flink) and building robust, versioned data pipelines
      • Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK) and the ability to define meaningful SLIs/SLOs for AI services
      • Track record of collaborating with research or product teams to move prototypes to production, translating experimental code into maintainable services
      • Strong problem solving mindset, excellent written and verbal communication, and a passion for building scalable AI platforms

      Preferred Qualifications:

      • Working knowledge of Scrum and Agile software development methodology

      Location: Remote

      This is a remote position that will primarily be supporting our Aurora, CO and King of Prussia, PA locations.  Due to contract requirements, the job has to be performed from a remote location in the United States.

      What We Offer:

      • Comprehensive medical/vision/dental insurance packages
      • Company contributions to qualified HSA accounts
      • 401k retirement plan with industry leading company contributions
      • 3 weeks of vacation accrual per year plus time off for sick leave and unscheduled life events
      • 13 paid holidays
      • Upfront tuition assistance for approved degree programs
      • Annual bonus program based on company and employee performance
      • Company paid life insurance, AD&D, Short-Term and Long-Term disability insurance
      • 4 weeks paid Parental Leave
      • Employee assistance program (EAP)

      EHS/Environmental Requirements:

      This job operates alongside a professional office environment. While performing the duties of this job, the employee routinely is required to use hands to keyboard, communicate, listen to, and interpret instructions and remain stationary for extended periods of the time. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the job.

      Applicants are invited to apply for a reasonable accommodation to perform the essential duties of the job. To apply, send a request to staffing@arka.org or contact 203-797-5000 and press 2 for Human Resources.

      ITC & Security Clearance Requirements:

      This position requires the incumbent to access export-controlled information. If you are not a U.S. Person, any offer is contingent upon the Company's ability to obtain a special license granting you access. This could take several months. You will not be able to begin employment until such license is obtained.

      Visa Restrictions:

      No visa sponsorship is available for this position.

      Pre-employment Screenings:

      Employment with any ARKA companies in the U.S. is contingent upon satisfactory completion of several pre-employment requirements to include a credit check, background check, and drug screen.

      Apply