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Machine Learning Engineer Python Jobs in Leander, TX

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We're looking for seasoned engineers with a background in machine learning to aid in this mission ... Proficient coding skills and strong software development experience in Spark, Python, or Java

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and ... Python with demonstrated experience implementing ML algorithms in production environments. • ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$184K - $324K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience building data processing pipelines and large scale machine learning systems with ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$184K - $324K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience building data processing pipelines and large scale machine learning systems with ...

webAI Inc

Staff Machine Learning Engineer

Austin, TX · On-site +1

Strong programming skills in Python and machine learning frameworks like TensorFlow and/or PyTorch. * Demonstrated ability to lead complex projects and work collaboratively in a team environment.

Adobe

2027 Intern - Machine Learning Engineer

Austin, TX · On-site +1

Strong Python programming skills; familiarity with other languages such as Java or C++ is a plus * Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow; familiarity with ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and ... Python with demonstrated experience implementing ML algorithms in production environments. • ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX · On-site

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

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All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in Leander, TX

Machine Learning Engineer Python information

See Leander, TX salary details

$22K

$133.7K

$193.5K

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

As of Sep 15, 2026, the average yearly pay for machine learning engineer python in Leander, TX is $133,743.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $157,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

What are the key skills and qualifications needed to thrive as a machine learning engineer python?

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by machine learning engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What are popular job titles related to Machine Learning Engineer Python jobs in Leander, TX?

For Machine Learning Engineer Python jobs in Leander, TX, the most frequently searched job titles are:

What cities near Leander, TX are hiring for Machine Learning Engineer Python jobs?

Cities near Leander, TX with the most Machine Learning Engineer Python job openings:

Machine Learning Engineer Python jobs near you

Senior Machine Learning Engineer

Austin, TX

Roku
1 - 5K employees
Learn more about Rokuexternal

$121K - $160K/yr

Full-time

Re-posted yesterday

Key responsibilities

  • Build and maintain a machine learning platform that manages the entire model lifecycle, including feature engineering, training, versioning, deployment, and monitoring.

  • Apply expertise in data analysis and feature engineering to generate features for multiple use cases and models.

  • Develop and evaluate machine learning models using techniques such as Decision Trees, Logistic Regression, Neural Networks, and Bayesian Analysis for improving system performance and accuracy.

Job description

About the team 

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real-time multi-objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation, and Inference Platform that powers the entire landscape, which we continuously evolve over time.

About the role 

We're on a mission to build cutting-edge advertising technology that empowers businesses to run sustainable and highly-profitable campaigns. The Ad Performance team owns server technologies, data, and cloud services aimed at improving the ad experience. We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and many more. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning using both general purpose software and statistical languages.

What you'll be doing 
  • ML infrastructure: Help build a first-class machine learning platform from the ground up which manages the entire model lifecycle - feature engineering, model training, versioning, deployment, online serving/evaluation, and monitoring prediction quality
  • Data analysis and feature engineering: Apply your expertise to identify and generate features that can be leveraged by multiple use cases and models
  • Model training with batch and real-time prediction scenarios: Use machine learning and statistical modelling techniques such as Decision Trees, Logistic Regression, Neural Networks, Bayesian Analysis and others to develop and evaluate algorithms for improving product/system performance, quality, and accuracy
  • Production operations: Low-level systems debugging, performance measurement, and optimisation on large production clusters
  • Collaboration with cross-functional teams: Partner with product managers, data scientists, and other engineers to deliver impactful solutions
  • Staying ahead of the curve: Continuously learn and adapt to emerging technologies and industry trends
We're excited if you have 
  • Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field
  • 5 years of experience in applied machine learning on real use cases 
  • Proficient coding skills and strong software development experience in Spark, Python, or Java
  • Familiarity with real-time evaluation of models with low latency constraints
  • Familiarity with distributed ML frameworks such as Spark-MLlib, TensorFlow, etc.
  • Ability to work with large scale computing frameworks, data analysis systems, and modelling environments i.e. Spark, Hive, NoSQL stores such as Aerospike and ScyllaDB
  • Ad Tech experience is preferred 
  • Proficient use of AI tools and agentic coding practices 
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