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Machine Learning Engineer Mlops Engineer Jobs in Austin, TX

Kurai

MLOps Engineer MLOps Engineer

Austin, TX · On-site

Join our ML Infrastructure team as an MLOps Engineer where you'll build the pipelines and platforms that deploy, monitor, and scale ML models from research to production. You'll bridge the gap ...

Roku

Senior Machine Learning Engineer, DevOps/SRE

Austin, TX · On-site

$128K - $165K/yr

About the role We are seeking a talented and experienced Senior Software Engineer, MLOps/DevOps, to ... Machine Learning infrastructure. The ideal candidate has a strong background in DevOps/SRE ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

Experience working in MLOps and building pipelines for deploying ML models * Programming skills in Python, C/C++ or Javascript * Understanding of machine learning and deep learning fundamentals

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

Experience working in MLOps and building pipelines for deploying ML models * Programming skills in Python, C/C++ or Javascript * Understanding of machine learning and deep learning fundamentals

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

Experience working in MLOps and building pipelines for deploying ML models * Programming skills in Python, C/C++ or Javascript * Understanding of machine learning and deep learning fundamentals

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

They are seeking a Machine Learning Engineer to be a core contributor to projects and deliver machine learning capabilities for customers, utilizing their technical and communication skills to ...

Roku

Senior Machine Learning Engineer, DevOps/SRE

Austin, TX · On-site

$128K - $165K/yr

About the role We are seeking a talented and experienced Senior Software Engineer, MLOps/DevOps, to ... Machine Learning infrastructure. The ideal candidate has a strong background in DevOps/SRE ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Avride develops autonomous vehicle and delivery robot technology, and they are seeking an experienced Machine Learning Engineer to enhance their autonomous systems. The role involves developing and ...

AgileEngine

MLOps Engineer ID72409

Austin, TX · On-site

... Machine Learning, or Software Engineering ; - Degree in Computer Science, Software Engineering, or a related technical discipline (or equivalent practical experience); - Engineers located in the US ...

AgileEngine

MLOps Engineer ID72409

Austin, TX · On-site

... Machine Learning, or Software Engineering ; - Degree in Computer Science, Software Engineering, or a related technical discipline (or equivalent practical experience); - Engineers located in the US ...

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 ... Master's degree in Computer Science, Machine Learning, or a related technical field preferred;

AgileEngine, LLC.

MLOps Engineer ID72409

Austin, TX · On-site

ABOUT THE ROLE We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle ... Machine Learning, or Software Engineering ; * - Degree in Computer Science, Software Engineering ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

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Showing results 1-20

All JobsMachine Learning Engineer Mlops Engineer JobsMachine Learning Engineer Mlops Engineer Jobs in Austin, TX

Machine Learning Engineer Mlops Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

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

As of Sep 13, 2026, the average yearly pay for machine learning engineer mlops engineer in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Mlops Engineer vs Data Scientist?

AspectMachine Learning Engineer Mlops EngineerData Scientist
Primary FocusDeveloping, deploying, and maintaining ML models and MLOps pipelinesAnalyzing data, building models, and deriving insights
Skills & CertificationsMachine learning, software engineering, cloud platforms, MLOps toolsStatistics, data analysis, programming (Python/R), visualization
Work EnvironmentSoftware development teams, cloud infrastructure, production environmentsResearch teams, data analysis projects, exploratory data analysis
Industry UsageTech companies, startups, enterprises deploying ML solutionsResearch institutions, analytics firms, data-driven organizations

While both roles involve working with machine learning, Machine Learning Engineers and MLOps Engineers focus on deploying and maintaining scalable ML systems, whereas Data Scientists primarily analyze data and develop models for insights. MLOps Engineers often work closely with Machine Learning Engineers to ensure models are production-ready and reliable.

What cities near Austin, TX are hiring for Machine Learning Engineer Mlops Engineer jobs?

Cities near Austin, TX with the most Machine Learning Engineer Mlops Engineer job openings:

Infographic showing various Machine Learning Engineer Mlops Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $127,637 per year, or $61.4 per hour.

MLOps Engineer MLOps Engineer

Austin, TX • On-site

Kurai
See more jobs at Kuraiexternal

Other

Posted 26 days ago

Job description

Join our ML Infrastructure team as an MLOps Engineer where you’ll build the pipelines and platforms that deploy, monitor, and scale ML models from research to production. You’ll bridge the gap between data science and engineering, automating model training, feature engineering, and deployment workflows. Our models serve millions of predictions daily with sub-100ms latency requirements. You’ll work with Kubeflow, MLflow, and custom tooling to make MLOps seamless for our team.

Responsibilities
  • Design and maintain CI/CD pipelines for ML models using GitHub Actions, ArgoCD, and custom tooling
  • Build and operate ML platforms on Kubernetes with GPU acceleration (NVIDIA, AWS EKS)
  • Implement feature stores (Feast) and data versioning (DVC, Delta Lake) for reproducible ML
  • Monitor model performance in production with drift detection, A/B testing, and automated retraining
  • Optimize inference latency through model quantization, ONNX, TensorRT, or custom serving solutions
  • Manage ML experiment tracking with MLflow or Weights & Biases; ensure reproducibility
  • Collaborate with data scientists to productionize research code and establish best practices
  • Implement automated testing for data quality, model validation, and pipeline integrity
Qualifications
  • 4+ years of DevOps/MLOps experience with 2+ years specifically in ML infrastructure
  • Strong Python skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)
  • Production experience with Kubernetes, Docker, and GPU orchestration
  • Deep understanding of ML lifecycle: training, validation, deployment, monitoring, retraining
  • Experience with cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML)
  • Familiarity with feature stores, experiment tracking, and ML metadata systems
  • Infrastructure-as-Code skills: Terraform, CloudFormation, or Pulumi
  • Experience with monitoring: Prometheus, Grafana, DataDog, or CloudWatch
  • BS/MS in CS, Engineering, or related field; experience at ML-focused companies is a plus
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