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Manager Edge Ai Machine Learning Jobs in Austin, TX

Cogent Info

AI/ Machine Learning Engineer

Austin, TX · On-site

As an AI/Machine Learning Engineer, you'll play a key role in designing, developing, and deploying intelligent systems that support millions of users worldwide. From building scalable machine ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

... of AI/Machine Learning. The product they offer allows their clients to monitor, manage, integrate, visualize, export, and analyze their data to inform decisions and streamline business. They are ...

Avride

Machine Learning Engineer

Austin, TX · On-site

In this role, you will conduct experiments, manage large-scale datasets, and implement deep ... Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning ...

Avride

Machine Learning Engineer

Austin, TX · On-site +1

In this role, you will conduct experiments, manage large-scale datasets, and implement deep ... Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning ...

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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 May 28, 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 popular job titles related to Manager Edge Ai Machine Learning jobs in Austin, TX? For Manager Edge Ai Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Manager Edge Ai Machine Learning jobs in Austin, TX look for? The top searched job categories for Manager Edge Ai Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for Manager Edge Ai Machine Learning jobs? Cities near Austin, TX with the most Manager Edge Ai Machine Learning job openings:
Manager Edge Ai Machine Learning jobs near you

AI/ Machine Learning Engineer

Cogent Info

Austin, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Mid-Level AI/Machine Learning Engineer

Join one of the top 10 global powerhouses transforming the future of Market. As an AI/Machine Learning Engineer, you'll play a key role in designing, developing, and deploying intelligent systems that support millions of users worldwide. From building scalable machine learning models and data pipelines to deploying AI solutions on cloud platforms, this is your opportunity to make a global impact with next-generation, data-driven systems. Whether you're a model builder, problem-solver, or technical leader, this team values engineers who bring innovation, collaboration, and a passion for applying AI at scale.

Location: flexible to relocate nationwide / relocate in particular time zone Full-time on-site required

Build Intelligent Systems That Make an Impact!

We're looking for mid-level AI professionals (3–7 years' experience) who are passionate about building, deploying and scaling AI and Generative AI solutions in production environments.

Open Roles:

  • Machine Learning Engineer
  • AI/GenAI Engineer
  • MLOps/AI Platform Engineer
  • AI Application Engineer

What You'll Do:

  • Design, train and deploy ML and GenAI models for real-world applications
  • Build LLM-based applications, RAG pipelines and AI-powered APIs
  • Develop scalable MLOps pipelines for model training, validation, CI/CD and monitoring
  • Work with cloud platforms (AWS, Azure, GCP) and GPU/accelerated workloads
  • Integrate AI models into web and backend applications
  • Monitor model performance, drift and reliability in production

What We're Looking For (Mid-Level):

  • 3–7 years of experience in ML/AI/MLOps/AI Engineering
  • Strong programming in Python (PyTorch, TensorFlow, scikit-learn)
  • Experience with LLMs, prompt engineering, vector databases and RAG frameworks
  • Knowledge of Docker, Kubernetes, CI/CD and cloud ML services
  • Experience with APIs, microservices and production deployments

Preferred Skills & Certifications:

  • Experience with OpenAI, Azure OpenAI, Vertex AI, Bedrock, Hugging Face
  • MLOps tools: MLflow, Kubeflow, Airflow, Weights & Biases
  • Cloud certifications or AI/ML certifications
  • Exposure to data pipelines, streaming and feature stores

Cogent Infotech is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment where everyone feels welcome and valued. We encourage applications from individuals of all backgrounds, identities, abilities, and experiences. If you're excited about this role but don't meet every requirement, we still encourage you to apply.

At Cogent Infotech, your ideas matter. Join a purpose-driven organization that celebrates diversity, encourages collaboration, and invests in your future.

Apply