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Manager Edge Ai Machine Learning Jobs in Austin, TX

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Job Summary : webAI is seeking a Senior Machine Learning Engineer to support their Public Sector ... Preferred : • Experience with edge AI, federated learning, or offline inference systems. • ...

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Job Summary : webAI is seeking a Senior Machine Learning Engineer to support their Public Sector ... Preferred : • Experience with edge AI, federated learning, or offline inference systems. • ...

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer to transform prototype models into scalable ... Preferred : • Experience with edge AI, federated learning, or offline inference systems. • ...

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... Help build a first-class machine learning platform from the ground up which manages the entire ...

SpangleAI

AI/ML Scientist

Austin, TX · On-site

Responsibilities : • Conduct cutting-edge research in Generative AI (GAI) and Large Language ... D. or Master's degree in AI, Machine Learning, Data Science, Computer Science, Electrical ...

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Showing results 21-40

All JobsEdge Ai Machine Learning JobsManager Edge Ai Machine Learning JobsManager Edge Ai Machine Learning Jobs in Austin, TX

Manager Edge Ai Machine Learning information

See Austin, TX salary details

$30.7K

$76.7K

$128.9K

How much do manager edge ai machine learning jobs pay per year?

As of Sep 3, 2026, the average yearly pay for manager edge ai machine learning in Austin, TX is $76,699.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,500.00 and $86,700.00 per year, depending on experience, location, and employer.

What is the difference between Manager Edge Ai Machine Learning vs Data Scientist?

AspectManager Edge Ai Machine LearningData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; certifications in AI/MLBachelor's or Master's in Data Science, Statistics, Computer Science; often certifications in data analysis or ML
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in AI/ML applicationsAnalyzes data, develops models, and provides insights, often working independently or in teams
Employer & Industry UsageTech companies, AI startups, enterprises implementing AI solutionsResearch institutions, tech firms, finance, healthcare, and other data-driven industries

While both roles involve AI and machine learning, the Manager Edge Ai Machine Learning focuses on leading teams and managing AI projects, whereas Data Scientists primarily analyze data and develop models. The manager role emphasizes leadership and project oversight, while Data Scientists concentrate on technical analysis and model development.

What are the most commonly searched types of Edge Ai Machine Learning jobs in Austin, TX?

The most popular types of Edge Ai Machine Learning jobs in Austin, TX are:

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Manager Edge Ai Machine Learning jobs near you

Senior Machine Learning Engineer

webAI

Austin, TX • On-site

$103K - $142K/yr

Full-time

Re-posted 16 days ago

Job description

Job Summary:
webAI is seeking a Senior Machine Learning Engineer to support their Public Sector initiatives focused on building and optimizing production-ready AI systems. The role involves transforming prototype models into scalable and reliable production systems that operate across various hardware environments.
Responsibilities:
• Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems.
• Productionize AI models from research prototypes into scalable, deployable systems used in real world applications.
• Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.
• Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific acceleration.
• Build and maintain Retrieval Augmented Generation (RAG) pipelines, including vector database integration for contextual retrieval.
• Work with multi-modal AI systems across computer vision, audio, and natural language domains.
• Optimize model execution for distributed and resource constrained environments, ensuring reliability under variable connectivity conditions.
Qualifications:
Required:
• Active US Security clearance
• 4+ years of experience in applied AI, ML engineering, or production AI systems.
• Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers.
• Proven experience deploying AI models across cloud, edge, and mobile hardware environments.
• Expertise in model compression and optimization (quantization, pruning, distillation).
• Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone).
• Familiarity with multi-modal models and synthetic data generation methods.
• Strong algorithmic and problem solving skills, especially in distributed or constrained compute environments.
Preferred:
• Experience with edge AI, federated learning, or offline inference systems.
• Understanding of AI governance and compliance frameworks relevant to public sector deployments.
• Experience integrating models into large scale distributed systems or microservice architectures.
• Excellent communication and technical documentation skills for collaboration across multi disciplinary teams.
• Strong understanding of GPU computing, CUDA, and performance profiling.
Company:
The leader in private AI. Founded in 2020, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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