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Python Ai Ml Jobs in Austin, TX (NOW HIRING)

Cliftonlarsonallen

Lead ML Ops Engineer

Austin, TX · On-site

$101K - $133K/yr

Broad experience integrating and governing multilanguage systems, including Python, JavaScript/TypeScript, and enterprise platforms (e.g., .NET). * Leadershiplevel expertise in AI/ML platform ...

Ascent360

Principal AI Architect

Austin, TX · On-site

$150 - $180/hr

Python (expert-level required) Java, TypeScript, Node.js, or similar * Experience with AI frameworks such as: LangGraph LangChain LlamaIndex Semantic Kernel AutoGen AI / ML Expertise * Deep ...

Tricentis

Principal AI Architect

Austin, TX

Python (expert-level required) Java, TypeScript, Node.js, or similar * Experience with AI frameworks such as: LangGraph LangChain LlamaIndex Semantic Kernel AutoGen AI / ML Expertise * Deep ...

Tricentis

Principal AI Architect

Austin, TX · On-site

Python (expert-level required) Java, TypeScript, Node.js, or similar * Experience with AI frameworks such as: LangGraph LangChain LlamaIndex Semantic Kernel AutoGen AI / ML Expertise * Deep ...

Northern Base

Gen AI Engineer

Austin, TX · On-site

Strong Java & Python Development * AI-Driven Automation Solutions Development * AI Agentic ... Familiarity with AI/ML solutions and cloud-native applications * Strong analytical, problem-solving ...

Gainwell Technologies LLC

Expert AI Engineer

Austin, TX · On-site

$147K - $210K/yr

Extensive AI/ML Experience : 5+ years in AI/ML engineering, including hands-on work with GenAI, NLP, deep learning, and computer vision. * Technical Proficiency : Strong coding skills in Python and ...

Tricentis GmbH

Principal AI Architect

Austin, TX · On-site

$150 - $180/hr

Python (expert-level required) Java, TypeScript, Node.js, or similar* Experience with AI frameworks such as: LangGraph LangChain LlamaIndex Semantic Kernel AutoGen### **AI / ML Expertise*** Deep ...

Introlligent Inc.

QA

Austin, TX · On-site

$41 - $55.75/hr

Develop AI testing and evaluation pipelines using Python. * Collaborate with AI/ML teams to improve AI application quality. Required Skills * Strong experience in AI Engineering , Generative AI , and ...

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All JobsPython Ai Ml JobsPython Ai Ml Jobs in Austin, TX

Python Ai Ml information

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How much do python ai ml jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for python ai ml in Austin, TX is $58.11, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

What is a Python AI ML engineer?

Python AI/ML engineers are professionals who use Python programming language to design, develop, and implement artificial intelligence (AI) and machine learning (ML) algorithms and models. Their work involves analyzing data, building predictive models, and deploying machine learning solutions to solve real-world problems. They are skilled in libraries such as TensorFlow, PyTorch, and Scikit-learn, and often collaborate with data scientists and software engineers. These engineers play a key role in transforming data into actionable insights and AI-powered applications.

What are the key skills and qualifications needed to thrive as a Python AI ML engineer, and why are they important?

To thrive as a Python AI/ML Engineer, you need strong proficiency in Python programming, a solid background in mathematics and statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), version control systems, and cloud platforms is typically required, along with relevant certifications being advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills that help translate business needs into technical solutions. These skills ensure the development of accurate, scalable, and efficient AI/ML models that deliver value to organizations.

How does a Python AI ML engineer typically collaborate with data engineers and domain experts during a project?

Python AI/ML professionals frequently work closely with data engineers to ensure data pipelines are robust, clean, and optimized for modeling. They also collaborate with domain experts to understand business needs, refine problem statements, and interpret results in the context of real-world applications. Effective communication and regular meetings are essential, as these collaborations help bridge technical and business perspectives, ensuring that machine learning solutions are both technically sound and aligned with organizational goals.
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Python Ai Ml jobs near you
Infographic showing various Python Ai Ml job openings in Austin, TX as of August 2026, with employment types broken down into 77% Full Time, 19% Part Time, and 4% Contract. Highlights an 72% Physical, 4% Hybrid, and 24% Remote job distribution, with an average salary of $120,861 per year, or $58.1 per hour.

Software Engineer 3 - AI Engineer : Austin, TX [ Hybrid ] : Only local

Marvel Technologies Inc

Austin, TX • On-site

Contractor

Re-posted 9 days ago

Job description

Title: Software Engineer 3 -  AI Engineer ( Locals preferrably)
Location: Austin, TX [ Hybrid ]
12 months

Position will be 3 days remote with 2 days (Tuesdays and Fridays) required to be onsite at the location listed above. ***Subject to change per manager***
Program will only accept LOCAL ONLY candidates for this position.
We are seeking an AI Engineer to drive innovation in our SDLC processes using artificial intelligence and automation. This role is ideal for an engineer passionate about automation and applying AI/ML techniques to improve reliability, observability, and operational workflows. The focus of this role is not to support external AI/ML product teams, but to internally develop AI-driven solutions that optimize SDLC processes, reduce toil, and increase automation maturity across the organization.
Key Responsibilities:
• Design and implement AI/ML models that improve SDLC processes in domains, such as: 
        o     Developer experience and productivity
        o   Intelligent test management using data analytics and predictive techniques
        o   Predictive infrastructure failure detection
        o   Agentic AI, MCP implementation, and RAG techniques
        o   Intelligent alerting and noise reduction
        o   Automated incident classification and root-cause analysis
        o   CI/CD optimization based on historical trends
        o   Using GenAI for IaC
        o   Any other innovative use-cases.
• Work closely with Development, DevOps, and Infrastructure teams to identify automation opportunities and pain points.
• Develop automation scripts and tooling to reduce manual tasks, operational efficiencies, and user experience.
• Build, deploy, and maintain pipelines to train and continuously improve AI models for DevOps use-cases.
• Collaborate with Infrastructure, Cloud, and DevOps teams to create architecture/design documents for proposed solutions.
• Ensure operational reliability, scalability, and performance of AI-driven automation tooling.
• Integrate AI solutions into monitoring.
• Experience with Agile Scrum and DevOps methodologies
•    Experience working in Developer IDEs, such as Eclipse, IBM Rational Application Developer, STS, etc.
•    Create technical and design documentation, as required
•    Perform system analysis, troubleshooting, diagnosis and problem resolution. Analyze software for defects and performance tuning opportunities
• GitHub Administration:
    - Manage repositories, branching strategies, and access control.
    -Automate workflows using GitHub Actions or similar CI/CD tools.
    -Maintain code quality and integration processes.
    -Define and implement governance rules.
•    Other duties as assigned.
 
Required Skills & Qualifications:
• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• 3+ years in Development/Automation roles.
• Strong background in cloud-native infrastructure (AWS, Azure, or GCP).
• Proficiency in automation and scripting (Python is preferred, Bash, etc.).
• Solid understanding of CI/CD pipelines 
• Experience with cloud-native technologies
• Experience applying AI/ML techniques to solve engineering problems (e.g., anomaly detection, classification, clustering).
• Familiarity with Python machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Good understanding of monitoring, logging, and observability tooling.

Preferred Skills:
• Experience with anomaly detection, predictive analytics, or time-series forecasting.
• Knowledge of MLOps practices (for internal AI models).
• Experience integrating AI solutions into DevOps toolchains and platforms.
• Familiarity with infrastructure as code (Terraform, Pulumi, CloudFormation).
•    Some working experience with Hyper-V Virtual Machine Management
• Asset and service account management 
• BMC Helix ticketing system