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Mlops Programmer Jobs (NOW HIRING)

Codinix Consulting Services

MLOps Engineer

California, MO · On-site

$125 - $150/hr

Local candidates only Job Overview We are seeking an experienced MLOps Engineer to design, build, and maintain scalable machine learning operations pipelines that support the full model lifecycle ...

4i Americas

MLOPs Engineer

Concord, CA · On-site

Ensure best practices in scalability, security, and reliability Required Skills & Qualifications * 2-5 years of experience in MLOps, DevOps, or ML Engineering * Strong proficiency in Python * Hands ...

NBCUniversal

Staff MLOps Engineer

They are seeking a Staff MLOps Engineer to build and scale infrastructure for large media datasets, ensuring automated, reproducible, and performant data pipelines for the machine learning lifecycle.

Redolent, Inc.

MLOps Engineer

Sunnyvale, CA · On-site

MLOps Engineer Duration: 12+ Months Location:Sunnyvale CA - hybrid Rate: DOE Key Responsibilities : Design and implement scalable model serving platforms for both batch and real-time inference Build ...

Redolent, Inc.

MLOps Engineer

Sunnyvale, CA · On-site

MlOps Engineer Duration: 12+ Months Location:Sunnyvale CA or Remote Key Responsibilities : Design and implement scalable model serving platforms for both batch and real-time inference Build model ...

Saksoft

MLOPS Engineer

Portland, OR · On-site

MLOPS ENGINEER JD: This data science role requires a minimum of 7 years of Python and data science experience, 3 years of AWS experience, and hands-on delivery of machine learning and Generative AI ...

HeadHR

NY · On-site

$60 - $80/hr

Minimum 3 lata doświadczenia w obszarze DevOps, MLOps lub Inżynierii Oprogramowania, w tym praktyka w pracy z modelami ML na produkcji. * Zaawansowana znajomość Docker i Kubernetes (zarządzanie ...

Apptronik

Staff MLOps Engineer

Austin, TX · On-site

JOB SUMMARY Apptronik is seeking a Staff MLOps Engineer to own the technical direction of our MLOps platform - the system of record for datasets, experiments, model artifacts, and serving paths that ...

Hirekeyz Inc

MLOps Engineer

San Francisco, CA · On-site

Role: MLOps Engineer Location: San Francisco, California Duration: Long Term Contract Key Responsibilities * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

HCA Healthcare

Staff MLOps Engineer

Murfreesboro, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

HCA Healthcare

Staff MLOps Engineer

Lebanon, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

Tror AI for everyone

MLOPS Engineer

Concord, CA · On-site

Job Role: MLOPS Engineer Job Location: Concord, CA (100% Onsite) Job Type: Contract Key Responsibilities: * Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

B Capital

Staff MLOps Engineer

Austin, TX · On-site

$125 - $150/hr

Job Summary Apptronik is seeking a Staff MLOps Engineer to own the technical direction of our MLOps platform -- the system of record for datasets, experiments, model artifacts, and serving paths that ...

HCA Healthcare

Staff MLOps Engineer

Franklin, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

HCA Healthcare

Staff MLOps Engineer

Nashville, TN · On-site

Staff ML Ops Engineer Job Summary and Qualifications Position Summary The Staff MLOps Engineer plays a pivotal role in shaping our MLOps practice within ITG by building and enhancing a scalable ...

ClifyX

MLOps Engineer

Hartford, CT · On-site

ClifyX is seeking an MLOps Engineer to enhance their machine learning operations. The primary responsibilities include developing and automating ML pipelines, deploying models, and ensuring ...

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How much do mlops programmer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for mlops programmer in the United States is $39.54, according to ZipRecruiter salary data. Most workers in this role earn between $25.72 and $51.44 per hour, depending on experience, location, and employer.

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Mlops Programmer jobs near you
Infographic showing various Mlops Programmer job openings in the United States as of August 2026, with employment types broken down into 83% Full Time, 6% Part Time, 10% Contract, and 1% Nights. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $82,234 per year, or $39.5 per hour.

MLOps Engineer

California, MO • On-site

Codinix Consulting Services
See more jobs at Codinix Consulting Servicesexternal

$125 - $150/hr

Other

Posted 21 days ago

Key responsibilities

  • Develop and maintain scalable machine learning pipelines using frameworks such as MLflow, Kubeflow, or Vertex AI

  • Design and implement CI/CD pipelines for machine learning models, managing model versioning, registry, and deployment with governance

  • Deploy and manage ML workloads on cloud platforms, utilizing containerization technologies like Docker and Kubernetes

Job description

Location: SFO, California, Duration: Long-Term Contract, Note: Local candidates only

Job Overview

We are seeking an experienced MLOps Engineer to design, build, and maintain scalable machine learning operations pipelines that support the full model lifecycle—from development and training to deployment, monitoring, and retraining. This role focuses on enabling production-grade ML systems using modern cloud platforms, CI/CD practices, and MLOps frameworks, ensuring reliability, scalability, governance, and performance of machine learning models in enterprise environments.

Key Responsibilities

ML Pipeline Development & Operations

  • Develop and maintain robust machine learning pipelines using frameworks such as MLflow, Kubeflow, or Vertex AI.
  • Automate the end-to-end ML lifecycle, including model training, validation, testing, deployment, and monitoring in cloud environments.
  • Implement reusable and scalable workflows for model versioning, tracking, and retraining.

CI/CD & Model Lifecycle Management

  • Design and implement CI/CD pipelines for machine learning models, ensuring seamless integration from development to production.
  • Manage model versioning, model registry, and deployment pipelines with strong governance practices.
  • Ensure reproducibility and traceability across ML lifecycle stages.

Cloud, Containers & Deployment

  • Deploy and manage ML workloads on cloud platforms such as GCP, AWS, or Azure.
  • Work with containerization technologies like Docker and Kubernetes to provision scalable model serving environments.
  • Enable low-latency model scoring APIs for real-time inference use cases.

Monitoring, Governance & Compliance

  • Implement model monitoring and observability frameworks to track performance, drift, and anomalies in production.
  • Ensure compliance with model risk management (MRM) standards, including documentation, explainability, and audit readiness.
  • Establish alerts and feedback loops for continuous model improvement and retraining.

Collaboration & Engineering Enablement

  • Collaborate with data engineering and platform teams to build and optimize data pipelines and ML infrastructure.
  • Support engineering teams in provisioning scalable environments for ML model development and deployment.
  • Partner with stakeholders to translate business requirements into ML-driven solutions.

AutoML & Accelerated ML Development

  • Leverage AutoML tools such as Vertex AI AutoML and H2O Driverless AI to accelerate model development and deployment.
  • Enable low-code/no-code ML workflows where appropriate, while ensuring production-grade quality and governance.
Required Qualifications
  • 10+ years of experience in Software Engineering, with at least 3+ years focused on AI/ML and MLOps.
  • Strong programming experience in Python and Java, along with SQL and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
  • Hands-on experience with cloud platforms (GCP, AWS, or Azure).
  • Strong knowledge of containerization technologies (Docker, Kubernetes).
  • Experience with data engineering and workflow orchestration tools such as Airflow and Spark.
  • Solid understanding of DevOps principles, CI/CD practices, and software engineering best practices.
  • Strong communication skills with the ability to explain complex ML concepts to both technical and non-technical stakeholders.
Preferred Qualifications
  • Experience with Vertex AI, MLflow, Kubeflow, or similar MLOps platforms.
  • Familiarity with model governance frameworks (MRM, model documentation, explainability tools).
  • Experience building real-time inference systems and scalable ML APIs.
  • Exposure to enterprise-scale ML systems in regulated industries.
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