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Mlops Machine Learning Engineer Jobs in Austin, TX

Bespoke Labs

Machine Learning Engineer

Austin, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

San Marcos, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Austin, TX

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

DPR Construction

MLOps Engineer

Austin, TX

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Machine Learning,Data Science, Data Engineering and Software Engineering. Position Overview ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

webAI Inc

Staff Machine Learning Engineer

Austin, TX · On-site +1

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track ...

Fluidstack

Machine Learning Engineer

Austin, TX · On-site

$130 - $180/hr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Austin, TX

Mlops Machine Learning Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

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

As of Aug 8, 2026, the average yearly pay for mlops machine learning 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 does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.
What are popular job titles related to Mlops Machine Learning Engineer jobs in Austin, TX? For Mlops Machine Learning Engineer jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Mlops Machine Learning Engineer jobs in Austin, TX look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Austin, TX are:
What cities near Austin, TX are hiring for Mlops Machine Learning Engineer jobs? Cities near Austin, TX with the most Mlops Machine Learning Engineer job openings:
Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,637 per year, or $61.4 per hour.

Machine Learning Engineer

Bespoke Labs

Austin, TX • On-site

Full-time

Re-posted 22 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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