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Machine Learning Ops Engineer Jobs (NOW HIRING)

Chalk

Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

They are seeking an Infrastructure Engineer to automate and manage their infrastructure ... Machine Learning Ops/Infrastructure Company : Chalk is a data platform for AI inference that ...

Photon

Senior ML Ops Engineer

Dallas, TX · On-site

$103K - $142K/yr

Machine Learning Algorithms. * Statistical Modeling. * End to end deployment. * Metric generation. * Model monitoring and deployment. * Prompt Engineering * Hand on with ML Model optimization ...

Mimecast

Senior ML Ops Engineer

Columbus, OH · On-site

$100K - $138K/yr

This role sits at the intersection of infrastructure engineering and machine learning. You will own ... Mentor ML Ops and ML Engineers on operational best practices. Participate in architectural reviews ...

Mimecast

Senior ML Ops Engineer

Columbus, OH · On-site

$100K - $138K/yr

This role sits at the intersection of infrastructure engineering and machine learning. You will own ... Mentor ML Ops and ML Engineers on operational best practices. Participate in architectural reviews ...

Adobe

Machine Learning Engineer 4

San Jose, CA · On-site

Adobe is looking for a Senior Machine Learning Engineer to help shape the future of agentic AI in ... Ops best practices, delivering high quality, production ready code. • Design and build ML ...

CoStar

Matterport - Senior ML Ops Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

Analyze and profile machine learning models to identify performance bottlenecks and areas for optimization. Implement and apply model optimization techniques such as quantization, pruning ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years ... Strong knowledge of ML Ops practices including version control, model monitoring, and retraining ...

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Machine Learning Ops Engineer information

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$31.5K

$128.8K

$193.5K

How much do machine learning ops engineer jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning ops engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a Machine Learning Ops Engineer job?

A Machine Learning Ops Engineer (MLOps Engineer) focuses on deploying, monitoring, and maintaining machine learning models in production. They bridge the gap between data science and software engineering, ensuring models run efficiently, reliably, and at scale. Their responsibilities include automating workflows, managing infrastructure, and ensuring CI/CD pipelines for ML models. They work with tools like Kubernetes, Docker, and cloud platforms to streamline model deployment. Ultimately, an MLOps Engineer ensures that machine learning models are operationalized and continuously improved in a real-world environment.

What does a typical day look like for a Machine Learning Ops Engineer?

A typical day for a Machine Learning Ops Engineer involves collaborating with data scientists to streamline the deployment of models, building and maintaining scalable infrastructure on cloud services, and automating workflows with CI/CD tools. You may troubleshoot issues in production environments, monitor model performance, and implement solutions for model versioning and retraining. Often, you’ll work closely with software engineers, DevOps teams, and data analysts to ensure seamless integration of machine learning solutions into products. This cross-functional role keeps you engaged with cutting-edge technology and provides opportunities to influence both technical and business outcomes.

What are the key skills and qualifications needed to thrive in the Machine Learning Ops Engineer position, and why are they important?

To thrive as a Machine Learning Ops Engineer, you need a solid grasp of machine learning concepts, cloud platforms, software engineering, and DevOps practices, typically supported by a degree in computer science or a related field. Experience with tools like Docker, Kubernetes, TensorFlow, CI/CD pipelines, and certifications such as AWS Certified Machine Learning – Specialty are highly valuable. Strong problem-solving skills, communication, and the ability to work collaboratively across data science and engineering teams set top candidates apart. These skills ensure reliable deployment, scalability, and optimization of machine learning models in production environments.

More about Machine Learning Ops Engineer jobs
What cities are hiring for Machine Learning Ops Engineer jobs? Cities with the most Machine Learning Ops Engineer job openings:
What are the most commonly searched types of Machine Learning Ops Engineer jobs? The most popular types of Machine Learning Ops Engineer jobs are:
What states have the most Machine Learning Ops Engineer jobs? States with the most job openings for Machine Learning Ops Engineer jobs include:
What job categories do people searching Machine Learning Ops Engineer jobs look for? The top searched job categories for Machine Learning Ops Engineer jobs are:
Machine Learning Ops Engineer jobs near you
Infographic showing various Machine Learning Ops Engineer job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Infrastructure Engineer

Infrastructure Engineer

Chalk

San Francisco, CA • On-site

$126K - $166K/yr

Full-time

Posted 17 days ago

Job description

Job Summary:
Chalk is a company focused on building a data platform for machine learning applications, aiming to simplify complex engineering challenges. They are seeking an Infrastructure Engineer to automate and manage their infrastructure, collaborate with engineering and sales teams, and contribute to the growth of the Engineering team.
Responsibilities:
• Write code to automate orchestration and provisioning of infrastructure to execute Chalk technology for Chalk customers and prospects.
• Build a platform for managing our hosted platform, and for managing the deployment of Chalk into customer-owned cloud accounts across AWS and GCP
• Work closely with our Engineering and Sales teams
• Help interview and grow the Engineering team
Qualifications:
Required:
• 4+ years experience writing software to automate infrastructure management
• Proficient in Python, Go, and/or Terraform
• Experienced in working with AWS and/or GCP
• Ability to collaborate effectively in teams of technical and non-technical individuals
• Bachelor's degree in Computer Science or equivalent
Preferred:
• Experience working closely with sales teams and customers is a plus.
• Previous experience working with ML/data products or services
• Have experience setting up hosted cloud resources for multiple companies
• Understanding of Machine Learning Ops/Infrastructure
Company:
Chalk is a data platform for AI inference that provides the infrastructure needed to operationalize machine learning and AI. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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