ZipRecruiter

Log In

1

Ml Inference Jobs in Pflugerville, TX (NOW HIRING)

General Motors

Senior AI/ML Engineer - AV Infra

Austin, TX · On-site

$170K - $261K/yr

AI Validation & Inference: Ensures robust model performance by running large-scale simulation workloads and managing reliable ML inference pipelines. * ML Compute: Streamlines andoptimizeslarge-scale ...

SambaNova

ML Features Solutions Engineer

Austin, TX

Drive improvements to ML features including model optimization, inference performance, and feature enhancements. * Production-Ready Solutions: Build and deploy production-ready ML solutions for ...

PICTOR LABS INC

Senior Software Engineer

Austin, TX · On-site

$118K - $156K/yr

Architect and implement containerized AI/ML inference pipelines for deployment on both cloud infrastructure and edge devices (NVIDIA DGX hardware) * Isolate and address performance issues end-to-end ...

SambaNova

ML Features Solutions Engineer

Austin, TX · On-site

$81K - $109K/yr

Responsibilities : • Design and implement core ML features including model optimization, quantization, and inference enhancements • Optimize model performance for latency, throughput, and memory ...

Latent AI

Senior Silicon Emulation Engineer

Austin, TX · On-site

$120 - $225/hr

Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators

New

SambaNova

ML Features Solutions Engineer

Austin, TX · On-site

$200K - $270K/yr

Drive improvements to ML features including model optimization, inference performance, and feature enhancements. * Production-Ready Solutions: Build and deploy production-ready ML solutions for ...

Catalyst Labs

ML Engineer

Austin, TX · On-site

... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...

Catalyst Labs

ML Engineer

Austin, TX · On-site

... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...

Mythic

Senior Silicon Emulation Engineer

Austin, TX

$120K - $225K/yr

Enable early firmware, driver, runtime, and ML stack bring-up on emulated hardware * Support execution of AI inference workloads (e.g., CNNs, transformers) on emulated Mythic accelerators

next page

Showing results 1-20

All JobsMl Inference JobsMl Inference Jobs in Pflugerville, TX

Ml Inference information

See Pflugerville, TX salary details

$35.3K

$115.5K

$184.8K

How much do ml inference jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ml inference in Pflugerville, TX is $115,453.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,700.00 and $127,900.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What are popular job titles related to Ml Inference jobs in Pflugerville, TX?

For Ml Inference jobs in Pflugerville, TX, the most frequently searched job titles are:

What job categories do people searching Ml Inference jobs in Pflugerville, TX look for?

The top searched job categories for Ml Inference jobs in Pflugerville, TX are:

What cities near Pflugerville, TX are hiring for Ml Inference jobs?

Cities near Pflugerville, TX with the most Ml Inference job openings:

Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Pflugerville, TX as of August 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $115,453 per year, or $55.5 per hour.

Lead ML Inference Engineer, Advertising

Roku, Inc.

Austin, TX • On-site

$150 - $200/hr

Other

Medical, Dental, Vision, Life, Retirement

Posted 3 days ago

New

Job description

About the team

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem—Advertisers, Publishers, and Roku. The systems and solutions span multiple disciplines and technologies to perform real‑time multi‑objective optimization across distributed systems at large scale and with low latency. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning and Inference Platform that powers the entire landscape.

About the role

In this role, you will architect, design, and lead the development of a state‑of‑the‑art inference platform that can handle Advertising‑level low latencies, scale, throughput, and availability with optimizations that span across hardware, software, and models. We’re looking for a strong technical leader with deep experience in ML serving, high‑performance computing, and industry standard frameworks—someone excited to mentor engineers, innovate at scale, and shape the future of machine learning at Roku.

What you’ll be doing
  • Lead the design and development of a state‑of‑the‑art inference platform.
  • Oversee the development of monitoring, observability, and other tooling to ensure system and model performance, reliability, and scalability of online inference services.
  • Identify and resolve system inefficiencies, performance bottlenecks, and reliability issues, ensuring optimized end‑to‑end performance.
  • Stay at the forefront of advancements in inference frameworks, ML hardware acceleration, and distributed systems, and incorporate innovations where and when they are impactful.
We’re excited if you have
  • M.S. or above in CS, ECE, or a related field.
  • 10+ years of experience in developing and deploying large‑scale, distributed systems, with at least 5 years in a leadership or technical lead role.
  • Strong programming skills in high‑performance languages.
  • Deep understanding of inference frameworks and ML system deployment.
  • Proven experience optimizing performance for large‑scale machine learning systems, including a deep knowledge of state‑of‑the‑art model optimizations, hardware‑software co‑design, GPU acceleration, and HPC techniques.
  • Excellent communication and collaboration skills.
  • Experience leading teams working on high‑throughput, low‑latency ML serving systems.
  • Experience collaborating with and leading global, cross‑functional teams.
  • Contributions to open‑source ML or systems projects.
Our Hybrid Work Approach

Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five‑day in‑office policy.

Benefits

Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It’s important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult your recruiter.

Accommodations

Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.

#J-18808-Ljbffr

Apply