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Machine Learning Manager Jobs in Austin, TX (NOW HIRING)

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

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 ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

... and product managers, to help develop and implement machine learning algorithms and testing ... workflows. Minimum Qualifications Bachelorʼs degree in Computer Science, Statistics, Mathematics ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

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 ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

... managers, to help develop and implement machine learning algorithms and testing workflows ... responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

... managers, to help develop and implement machine learning algorithms and testing workflows ... responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $324K/yr

... managers, to help develop and implement machine learning algorithms and testing workflows ... responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions ...

PayPal

Sr Machine Learning Engineer

Austin, TX · On-site

$55.25 - $73/hr

We also help merchants connect with their customers, process exchanges and returns, and manage risk ... Develop and optimize machine learning models for various applications. * Preprocess and analyze ...

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Machine Learning Manager information

See Austin, TX salary details

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$81K

$117K

How much do machine learning manager jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning manager in Austin, TX is $80,990.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,400.00 and $91,700.00 per year, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and their role involves understanding algorithms, data processing, and model deployment. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and overseeing complex AI solutions, making complete replacement unlikely in the near term.

What are some of the main challenges a Machine Learning Manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning manager or director, often involving leadership, advanced technical skills, and strategic responsibilities. These roles usually require extensive experience, expertise in AI tools and frameworks, and may include performance-based bonuses or stock options that contribute to the total compensation. Such salaries are common in large tech companies or organizations with significant AI investments.

What are the key skills and qualifications needed to thrive as a Machine Learning Manager, and why are they important?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

Is ML a high paying job?

Machine Learning Managers typically earn high salaries due to the specialized skills required, such as expertise in algorithms, programming, and data analysis. Compensation varies based on experience, location, and industry, but it is generally above average compared to many other tech roles.

Which 3 jobs will survive AI?

Machine Learning Managers will continue to be essential as they oversee AI projects, interpret complex data, and coordinate teams, tasks that require strategic thinking and human judgment. Roles that involve creative problem-solving, emotional intelligence, and domain-specific expertise, such as healthcare professionals, educators, and skilled tradespeople, are also likely to persist despite AI advancements. These jobs rely on human intuition and adaptability that AI cannot fully replicate.

What are Machine Learning Managers?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.
What are the most commonly searched types of Machine Learning jobs in Austin, TX? The most popular types of Machine Learning jobs in Austin, TX are:
What are popular job titles related to Machine Learning Manager jobs in Austin, TX? For Machine Learning Manager jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Manager jobs in Austin, TX look for? The top searched job categories for Machine Learning Manager jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Manager jobs? Cities near Austin, TX with the most Machine Learning Manager job openings:
Machine Learning Manager jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Roku

Austin, TX

$121K - $160K/yr

Other

Posted 28 days ago

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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