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Deep Learning Developer Jobs in Austin, TX (NOW HIRING)

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site +1

$335K - $400K/yr

You will be working with our engineering and product teams to design, build and productionize ... Keep track of emerging tech and trends, research the state-of-the-art deep learning models ...

Rokt

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

You will be working with our engineering and product teams to design, build and productionize ... Keep track of emerging tech and trends, research the state-of-the-art deep learning models ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

Understanding of machine learning and deep learning fundamentals * Develop internal tooling as ... Support infrastructure engineering, security engineering, and architecture * Willing to learn and ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

Understanding of machine learning and deep learning fundamentals * Develop internal tooling as ... Support infrastructure engineering, security engineering, and architecture * Willing to learn and ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning ...

Varsity Tutors

Machine Learning Tutor

Round Rock, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

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Deep Learning Developer information

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How much do deep learning developer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for deep learning developer in Austin, TX is $38.10, according to ZipRecruiter salary data. Most workers in this role earn between $32.40 and $42.40 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning developer?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What is a deep learning developer?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges deep learning developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
What cities near Austin, TX are hiring for Deep Learning Developer jobs? Cities near Austin, TX with the most Deep Learning Developer job openings:
Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer 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 $79,254 per year, or $38.1 per hour.

Senior Machine Learning Engineer

Rokt

Austin, TX • On-site, Remote

$335K - $400K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago

Job description

Rokt is an ecommerce technology company with the mission of making every transaction more relevant. The Rokt Ecommerce Network leverages proprietary machine learning recommendation systems, powering billions of transactions for hundreds of millions of customers, and is trusted to do this by companies like Live Nation, Fanatics, Macy's, AMC Theatres, PayPal, Uber, Hulu, Staples, Albertsons and HelloFresh.

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 product teams to design, build and productionize proprietary machine learning models to solve different business challenges including smart bidding, lookalike modelling, forecasting, etc.

Target total compensation ranges from $335k - $400k, comprised of a fixed annual salary of $210k - $260k, plus employee equity plan grant. In addition, you will receive world-class employee benefits.

Responsibilities

  • Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions for smart bidding, lookalike modelling, forecasting, and related ranking and prediction tasks.
  • Build and productionise machine learning models, including model-specific data pipelines, feature engineering within the team's feature store, and integration with the team's orchestration and serving infrastructure.
  • Evaluate model performance through offline metrics, and monitor deployed models for drift, leading retraining or rollback decisions as needed.
  • Contribute to and maintain the high quality of the code base with tests that provide a high level of functional coverage as well as non-functional aspects such as load testing, unit testing, and integration testing.
  • Keep track of emerging tech and trends, research the state-of-the-art deep learning models, prototype new modelling ideas, and conduct offline and online experiments

Requirements

  • Willingness to work 4 day in-office, 1 day remote weekly schedule.
  • PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization in ML, AI, or Information Retrieval (or equivalent experience)
  • Extensive knowledge in and experience with some of the following areas: Bayesian methods, recommender systems, multi-task modelling, meta-learning, click-through rate modelling or conversion rate modelling
  • 3+ years of industry experience building production-grade machine learning systems, spanning model training, tuning, deployment, serving, and monitoring
  • Experience with Kubeflow (or similar), TensorFlow, and a feature store in a production environment is a massive plus
  • Bonus points if you are familiar with any of the following architectures or have experience with the models mentioned: DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, and GDCN

Benefits

  • Equity in a profitable, fast-growing company approaching $1 Billion in revenue.
  • Dollar-for-dollar 401K matching plan (up to 4% of fixed annual remuneration)
  • Fully funded health insurance (Dental, Optical, and Medical)
  • Generous allowances for wellness, technology, mobile, and transit.
  • Daily catered lunch, stocked pantry & fridges
  • Extra leave (bonus annual leave, sabbatical leave etc.)

Equal employment opportunities are available to all applicants without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

If this sounds like a role you'd enjoy, apply here, and you'll hear from our recruiting team.

Note: The first stage of the recruitment process for this role is to complete a 15-minute online aptitude test, which will be sent out to your application email. Successful candidates will be contacted to discuss the next steps.

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