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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 ...

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 ...

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 · On-site

$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

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

Mythic

Senior Silicon Emulation Engineer

Austin, TX · On-site

$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

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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 6, 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 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 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 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.

Is ML inference a high paying job?

ML inference roles are generally well-paying, especially for those with skills in machine learning frameworks, programming, and cloud platforms. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech-related positions.
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 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 50% Full Time, and 50% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $115,453 per year, or $55.5 per hour.

Staff AI/ML Engineer - AV ML Infra

General Motors

Austin, TX • On-site

$218K - $335K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago

General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 305 frontline employees who took The Breakroom Quiz

7.4

Company rating compared to similar companies: 7.4 out of 10

Automakers average

Based on 6,270 frontline employees who took The Breakroom Quiz

Job description

Job Description

Staff AI/ML Engineer, AV ML Infra

We'reGeneral Motors (GM), a company driving the future of mobility with advanced self-driving and electric vehicle technologies.

We'rebuilding the world's most innovative autonomous vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.

GM employees have the opportunity to grow and develop while learning from leaders at the forefront of their fields.With a culture of internal mobility,there'san opportunity to thrive in a variety of disciplines. This is a place for dreamers anddoersto succeed.

If you are looking to play a part in making a positive impactinthe world by advancing the revolutionary work of self-driving vehicles, join us.

About the team:

The AV ML Infra team at GM builds ML infrastructure designed to meet the unique demands of AI and ML innovation, supporting a wide range of use cases across teams such as Embodied AI, Simulation, Data Science, and more. We enable scalable and efficient ML experimentation, enhance the productivity of ML engineers, and drive the adoption ofcutting-edgeML techniques.

Our ML infrastructure includes:

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

  • ML Compute:Streamlines andoptimizeslarge-scale ML training and inference across cloud and on-premcomputeresources.

  • AV Pipelines & Lineage:Automates ML workflows while tracking data and model lineage across diverse infrastructures, accelerating engineering velocity and ensuring reproducibility.

Together, these tools and systems empower GM to tackle the complexities of autonomous driving technology andexpediteour path to commercialization.

Position Overview:

  • As aStaff AI/ML Engineer, you will be a technical expert within the AV ML Infra team, driving the design and implementation of scalable ML infrastructure solutions. You will influence the direction of our technical projects, provide mentorship to peers, and help shape the adoption of best practices across GM's ML infrastructure. This is an individual contributor/Tech Lead role focused on deep technical impact rather than team management.

    Note: This role is part of an ML infrastructure engineering team and does not involve applying machine learning models for specific tasks. The focus is on developing infrastructure products that empower GM teams to perform machine learning and data science atscale.

    Whatyou'llbe doing:

    • Design & Implementation:Utilizethe latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud.

    • Project Ownership:Take ownership of technical projects frominceptionto completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs.

    • Collaboration:Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts.

    • Mentorship & Recruitment:Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing.

    What you must have:

    • 8+ years of experience, with a strong background in large-scaledistributedsystems preferred.

    • 3+ years of experience leading and driving large-scale initiatives.

    • Proficiencyin building scalable infrastructureon the cloudusing Python, C++, Golang, or similar languages.

    • Experience working with relational and NoSQL databases.

    • Demonstrated ability to develop andmaintainsystems at scale.

    • A Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience.

    • A passion for autonomous vehicle technology and its transformative potential.

    • Strong attention to detail anda commitmentto accuracy.

    • A proventrack recordof efficiently solving complex problems.

    • A startup mentality with a willingness to embrace uncertainty and wear multiple hats.

    Bonus Points:

    • Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services.

    • Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, etc.

    • Experience with Kubernetes.

    • Understanding ofMachine Learning (ML) models/pipelines.

    • Python/C++/Golangproficiency.

    • Relevant publications.

    Compensation:

    • The expected base compensation for this role is: $218,800 - $335,300. Actual base compensation within the identified range will vary based on factors relevant to the position.
    • You also need to include general information about potential commissions, if applicable.
    • Bonus Potential:An incentive pay program offers payouts based on company performance, job level, and individual performance.

    Benefits:
    • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

    Company Vehicle:Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Working at General Motors

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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908

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