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Online Machine Learning Postdoc Jobs in Texas (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 ...

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 ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoctoral Fellow - Biostatistics

Houston, TX · On-site

$64K - $76K/yr

... machine learning for estimation or decision-making. Please send CV and information on three referees directly to mliang2@mdanderson.org. POSITION INFORMATION MD Anderson offers full-time postdoc ...

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All JobsOnline Machine Learning Postdoc JobsOnline Machine Learning Postdoc Jobs in Texas

Online Machine Learning Postdoc information

What is the difference between Online Machine Learning Postdoc vs Data Scientist?

AspectOnline Machine Learning PostdocData Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often a PhD is preferred but not required
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, tech firms, startups, corporate analytics teams
Employer & Industry UsagePrimarily academic, research-focused roles in universities or research institutionsCommercial sector, product development, data analysis, and business intelligence

The Online Machine Learning Postdoc typically focuses on academic research, exploring new algorithms and theories in machine learning, often in a university setting. In contrast, a Data Scientist applies machine learning techniques to solve real-world business problems in industry. While both roles require strong technical skills, the Postdoc emphasizes research and publication, whereas Data Scientists focus on data analysis and product development.

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Online Machine Learning Postdoc jobs near you

Senior Machine Learning Engineer

Roku

Austin, TX

$121K - $160K/yr

Full-time

Re-posted 19 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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