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Remote Machine Learning Ops Engineer Jobs in Austin, TX

Senior Infrastructure/Cloud Engineer

Austin, TX · On-site +1

$107.50K - $146.20K/yr

Founded by an immigrant team with expertise in finance, technology, and machine learning, Stilt has ... You lean towards a data-driven approach to solving dev-ops and infrastructure-related problems.

Create predictive models and machine-learning algorithms * Modify and combine different models ... Work together with engineering and product development teams Data Scientist requirements are: * 3+ ...

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

Innovations and AI Solutions Engineer

Austin, TX · On-site +1

$116.88K - $158.13K/yr

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

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Showing results 1-20

Remote Machine Learning Ops Engineer information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

How much do remote machine learning ops engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for remote machine learning ops engineer in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 per year, depending on experience, location, and employer.
What cities near Austin, TX are hiring for Remote Machine Learning Ops Engineer jobs? Cities near Austin, TX with the most Remote Machine Learning Ops Engineer job openings:
Staff Software Engineer, Enterprise AI Platform

Staff Software Engineer, Enterprise AI Platform

Cloudera

Austin, TX • Remote

Other

PTO

Posted 6 days ago


Job description

Business Area:

Engineering

Seniority Level:

Mid-Senior level

Job Description:

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world's largest enterprises.

Our Data Services Pillar is the heart of data innovation. We don't just work with technology; we build it. Our mission is to empower data practitioners by creating seamless, enterprise-grade experiences for data engineering, warehousing, streaming, operational databases, and AI.

Join our Cloudera's Machine Learning Platform team as a Staff Software Engineer. You'll contribute to our next-gen AI & Machine Learning platform and will be responsible for helping design, build, and deliver a platform that not only accelerates machine learning & AI from exploration to production but also enables enterprises to create & deploy Generative AI applications using foundation models with enterprise data at scale in a hybrid cloud environment.This role requires an empathetic mindset and close collaboration with software engineers, designers, and product management.

In addition to experience with building AI/ML platforms or applications, we are also looking for prior experience/skills with container orchestration technologies like Kubernetes and cloud platforms like AWS, Azure, Openshift or GCP. Attention to detail and a strong drive are key qualities we value. As a senior engineer, you'll help our team develop and enjoy significant growth opportunities.


As a Staff Software Engineer you will:

  • Help build the leading platform for AI/machine learning in the enterprise

  • Design, and code elegant, scalable, enterprise-quality application services

  • Implement AI application services powered by machine learning models

  • Advocate for the implementation of Engineering best practices and coding standards

  • Build strong relationships and collaborate with platform and UI engineers, quality engineers, UX designers, as well as, Product Management, Field Engineering, and other external partners

  • Work to enhance developer velocity and team agility

We are excited if you have (Required Experience):

  • 8+ years of experience building scalable microservices or applications using Go, C#/C++ or Java

  • Bsc/Msc in related field or equivalent experience

  • Experience with foundation models, prompt engineering, fine-tuning, semantic search and Retrieval-Augmented Generation (RAG) using vector databases such as Pinecone, Milvus, etc.

  • Experience with Generative AI frameworks (LangChain, Guidance, NeMo etc.).

  • Experience building and deploying Generative AI applications

  • Experience with microservices design and development (Go, GRPC, SQL) on Kubernetes

  • Experience with at least one of the following Cloud technologies - Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure

  • Demonstrate ability to go deep into technology and complex distributed systems

  • Experience in crafting high level and low level design

  • Experience building scalable, robust and secure enterprise applications

  • Self-driven and motivated, with a strong sense of ownership and craftsmanship

  • Strong written and verbal communication skills.

You may also have:

  • Experience with building applications with machine learning models using data science and machine learning tools (Python, Tensorflow, Spark, MLflow, R, etc.)

  • Full stack experience with React, HTML, CSS

  • Experience with AI/ML orchestration software (Kubeflow, KServe, Knative, Ray)

  • Experience using Big Data technologies like Spark, Hive etc.

  • Proven track record of collaborating with agile teams across geographically dispersed locations


This role is not eligible for immigration sponsorship or relocation

What you can expect from us:

  • Generous PTO Policy

  • Support work life balance with Unplugged Days

  • Flexible WFH Policy

  • Mental & Physical Wellness programs

  • Phone and Internet Reimbursement program

  • Access to Continued Career Development

  • Comprehensive Benefits and Competitive Packages

  • Paid Volunteer Time

  • Employee Resource Groups

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