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Remote Machine Learning Compiler Engineer Jobs in Leander, TX

David Joseph & Company

AI Engineer

Austin, TX · On-site +1

$140K - $200K/yr

Remote (United States) Compensation: $140,000 - $200,000 base Visa Sponsorship: None available ... About the Role As an AI Engineer, you will design, train, and deploy machine learning models and ...

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AI Engineer (Remote)

Austin, TX · Remote

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

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AI Engineer (Remote)

Austin, TX · On-site +1

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

Continued

AI Engineer (Remote)

Austin, TX · Remote

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

Victory

Data Scientist (Remote)

Austin, TX · Remote

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+ ...

Driver AI Inc.

Software Engineer - Backend

Austin, TX · Remote

Remote or Austin, TX About the Role Our core innovation, the Driver Transpiler, treats software ... compiler design, and generative AI, building systems that expand how both humans and machines ...

Wsgr

Innovations and AI Solutions Engineer

Austin, TX · On-site +1

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 ...

Kake Group

Senior AI Talent Sourcer

Austin, TX · Remote

... machine learning engineers, research engineers, AI researchers, domain experts, and other ... Ability to work independently in a remote, fast-paced environment. Other Traits * Naturally curious ...

Hired Recruiters

Senior DevOps Engineer

Austin, TX · On-site +1

$128K - $165K/yr

Remote * Salary $150k - $200k * Seed Company * Skills: Ansible, Bash, Python, Terraform, Docker ... machine learning architecture. * Have an expert level understanding of Terraform and Ansible in ...

Driver AI Inc.

Software Engineer - Backend

Austin, TX · On-site +1

$175K - $275K/yr

Remote or Austin, TX About the Role Our core innovation, the Driver Transpiler, treats software ... compiler design, and generative AI, building systems that expand how both humans and machines ...

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All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Leander, TX

Remote Machine Learning Compiler Engineer information

See Leander, TX salary details

$71.7K

$160K

$195.9K

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

As of Jul 22, 2026, the average yearly pay for remote machine learning compiler engineer in Leander, TX is $159,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,600.00 and $195,900.00 per year, depending on experience, location, and employer.

How does a Remote Machine Learning Compiler Engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a Remote Machine Learning Compiler Engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Compiler Engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Leander, TX? For Remote Machine Learning Compiler Engineer jobs in Leander, TX, the most frequently searched job titles are:
What cities near Leander, TX are hiring for Remote Machine Learning Compiler Engineer jobs? Cities near Leander, TX with the most Remote Machine Learning Compiler Engineer job openings:
Remote Machine Learning Compiler Engineer jobs near you

AI Engineer

David Joseph & Company

Austin, TX • On-site, Remote

$140K - $200K/yr

Full-time

Medical, Dental, Vision

Posted 17 days ago

Job description

AI Engineer

Location: Remote (United States)
Compensation: $140,000 – $200,000 base
Visa Sponsorship: None available — US Citizen or Green Card holder required
Experience Level: 5+ years
Employment Type: Full-Time

About the Company

The company is an enterprise AI company based in Austin, Texas, founded in 2021. The company offers a hybrid AI platform that integrates autonomous AI agents with human expertise, allowing businesses to build, deploy, and scale custom AI solutions significantly faster and at lower cost than traditional methods. The no-code platform supports full-lifecycle AI including data integration, predictive analytics, and workflow automation. Series A with $39.5M raised, serving manufacturing, retail, and financial services customers globally.

About the Role

As an AI Engineer, you will design, train, and deploy machine learning models and LLM-powered systems that power an automated machine learning platform for enterprise users. You will bridge the gap between complex data science and intuitive user experiences — owning everything from RAG pipeline architecture to production deployment and API development.

What You'll Own
  • Design, train, and optimize ML models and LLMs to solve complex predictive and generative tasks within the RapidCanvas platform
  • Architect and implement robust RAG workflows — vector database management, embedding optimization, and advanced prompt engineering
  • Deploy scalable AI services using containerization and orchestration tools, ensuring high availability and low-latency inference
  • Build and maintain automated data ingestion and preprocessing pipelines to transform raw enterprise data into high-quality training sets and feature stores
  • Establish rigorous evaluation frameworks to measure model accuracy, drift, and computational efficiency
  • Develop secure, high-performance APIs to expose AI capabilities to the frontend
Requirements
  • 5+ years of professional experience moving ML models into production environments
  • Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related quantitative field
  • Proven experience implementing LLMs and RAG architectures using LangChain, LlamaIndex, OpenAI APIs, or similar
  • Advanced Python proficiency including FastAPI or Flask for model serving
  • Hands-on experience with vector databases — Pinecone, Milvus, Weaviate, or equivalent
  • MLOps experience — Docker, Kubernetes, MLflow, Airflow, or similar for full ML lifecycle management
  • Cloud platform experience — AWS, GCP, or Azure
  • Experience with SQL/NoSQL databases and large-scale data processing
  • US Citizen or Green Card holder — no visa sponsorship available
Nice to Have
  • Experience with Auto-ML or No-Code/Low-Code data science platforms
  • Proficiency with gradient-boosted trees (XGBoost, LightGBM), time-series forecasting, and deep learning frameworks
  • Experience with automated feature engineering and hyperparameter tuning (Optuna, Ray Tune)
  • Familiarity with Spark or Dask for large-scale data processing
  • Master's or PhD in Computer Science, Statistics, Mathematics, or related quantitative field
Benefits
  • Health, dental, and vision insurance
  • Outcome-oriented flexibility — focus on impact over hours logged
Interview Process
  1. First-round team interview — technical and collaborative session
  2. Technical assessment — practical skills evaluation or take-home assignment
  3. Deep-dive interview — architecture, methodologies, and project experience
  4. Cultural alignment and leadership interview with key stakeholders
Logistics
  • Role is fully remote within the United States
  • US Citizen or Green Card holder required — no visa sponsorship or relocation assistance available

Shortlisted candidates will be contacted by David Joseph & Co.