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Principal Mlops Engineer Jobs (NOW HIRING)

Redolent, Inc.

Prinicipal MlOps Engineer

Sunnyvale, CA · On-site

Principal MLOps Engineer Location: Sunnyvale, CA Job Type: - Contract - 12+ Months Department: Data Science / Machine Learning About the Role We are seeking an experienced Principal MLOps Engineer to ...

PNC

Quality Engineer Principal - MLOps

Pittsburgh, PA · On-site

As a Quality Engineer Principal within PNC's Data and Automation Technology organization, you will be based in Pittsburgh, PA, Strongsville, OH or Dallas, TX. We are looking for a MLOPs Quality ...

FutureFit AI

ML Ops Lead

$104K - $138K/yr

Staff / Principal MLOps Engineer Full-Time | Remote (US or Canada) or Contract (6 months, potential to convert) Come join our Data team! High velocity, high trust, and high impact with a will to win.

Tiger Analytics Inc.

MLOps Lead Engineer

Saint Louis, MO · On-site

$99K - $131K/yr

You will act as the principal technical authority, bridging platform engineering with client-side ... MLOps/Data platform implementations. * Core Technical Stack: Advanced proficiency in Azure ...

Tiger Analytics

MLOps Lead Engineer

Saint Louis, MO · On-site

$150 - $200/hr

You will act as the principal technical authority, bridging platform engineering with client-side ... MLOps/Data platform implementations. * Core Technical Stack: Advanced proficiency in Azure ...

Tiger Analytics Inc.

MLOps Lead Engineer

Saint Louis, MO · On-site

$99K - $131K/yr

You will act as the principal technical authority, bridging platform engineering with client-side ... MLOps/Data platform implementations. * Core Technical Stack: Advanced proficiency in Azure ...

Tiger Analytics

$150 - $200/hr

You will act as the principal technical authority, bridging platform engineering with client-side ... MLOps/Data platform implementations. * Core Technical Stack: Advanced proficiency in Azure ...

Tiger Analytics Inc.

MLOps Lead Engineer

Saint Louis, MO · On-site

$99K - $131K/yr

You will act as the principal technical authority, bridging platform engineering with client-side ... MLOps/Data platform implementations. * Core Technical Stack: Advanced proficiency in Azure ...

Cotiviti

Principal AI Engineer

$208K - $260K/yr

Overview We are seeking a highly experienced Principal AI Engineer to lead the architecture, design ... Working closely with Data Scientists, MLOps Engineers, Data Engineers, and Product Engineering ...

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How much do principal mlops engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for principal mlops engineer in the United States is $147,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What states have the most Principal Mlops Engineer jobs?

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Infographic showing various Principal Mlops Engineer job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $147,220 per year, or $70.8 per hour.

Prinicipal MlOps Engineer

Sunnyvale, CA • On-site

Redolent, Inc.
IT Services • 51 - 200 employees
Learn more about Redolent, Inc.external

Contractor

Re-posted 8 days ago

Job description

Job Title: Principal MLOps Engineer
Location: Sunnyvale, CA
Job Type: - Contract - 12+ Months
Department: Data Science / Machine Learning
About the Role
We are seeking an experienced Principal MLOps Engineer to lead and scale our machine
learning operations, ensuring eJicient, secure, and reliable ML model deployments. As a
senior technical leader, you will be responsible for designing and implementing a cutting-
edge MLOps framework, driving automation, and enhancing ML infrastructure to support
large-scale, mission-critical applications. This role requires deep expertise in MLOps best
practices, cloud architecture, and DevOps principles, along with strong leadership and
collaboration skills to guide engineering teams and stakeholders.
Key Responsibilities
  • Architect and lead the development of scalable and robust ML infrastructure to support the entire model lifecycle, from experimentation to production.
  • Establish MLOps best practices, ensuring automation, reproducibility, versioning, and monitoring of models in production.
  • Design and implement CI/CD pipelines for machine learning models, integrating security, compliance, and performance optimization.
  • Drive ML observability strategies, implementing monitoring tools for detecting model drift, data drift, and performance degradation.
  • Optimize and manage cloud-based ML workloads using AWS, GCP, or Azure, ensuring cost-eJiciency and scalability.
  • Lead and mentor a team of MLOps engineers, collaborating closely with data scientists, software engineers, and DevOps teams.
  • Define infrastructure as code (IaC) using Terraform, Kubernetes, and containerization tools to standardize deployments.
  • Enhance ML model serving architectures, leveraging Kubernetes, serverless computing, or specialized model-serving frameworks.
  • Implement robust security frameworks for ML workflows, ensuring data privacy, access control, and compliance with industry regulations.
  • Stay ahead of industry trends, evaluating and integrating new technologies to improve automation and eJiciency in ML workflows.

Requirements
Technical Skills
  • Expertise in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
  • Deep knowledge of CI/CD pipelines, DevOps practices, and cloud-native architectures.
  • Strong experience with Kubernetes, Docker, and infrastructure-as-code tools (Terraform, Ansible, etc.).
  • Advanced understanding of ML pipeline orchestration tools like Kubeflow, MLflow, Airflow, or TFX.
  • Proficiency in monitoring and observability tools like Prometheus, Grafana, ELK Stack, or Datadog for ML workloads.
  • Experience with distributed computing frameworks (e.g., Spark, Ray, Dask) is a plus.
  • Familiarity with model explainability, fairness, and bias detection tools is highly desirable.
  • Strong knowledge of security best practices for ML systems, including data encryption, API security, and governance.

Soft Skills
  • Proven leadership in architecting, deploying, and managing large-scale M infrastructure.
  • Strong ability to mentor and lead teams, fostering best practices and knowledge sharing.
  • Excellent problem-solving and critical thinking skills to tackle complex ML engineering challenges.
  • EJective communication and collaboration with cross-functional teams, including engineering, product, and business stakeholders.

Education & Experience
  • Bachelor's or master's degree in computer science, Machine Learning, Data Engineering, or a related field.
  • 7+ years of experience in MLOps, DevOps, or ML infrastructure engineering.
  • Proven track record of leading ML deployment initiatives at scale in enterprise or high growth environments.
Redolent logo

About Redolent

Sourced by ZipRecruiter

Redolent, a dynamic and rapidly expanding company committed to excellence in software solutions, where success is fueled by a combination of technical expertise and efficient management practices. Our solutions create a measurable delta in our clients’ productivity and profitability, contributing to their growth and success.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

San Jose, CA, US

Year founded

2008

Social media

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