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Ml Inference Jobs in Garland, TX (NOW HIRING)

eTeam

Machine Learning Platform Engineer

Richardson, TX · On-site

Responsibilities : • Should have 7 years of experience with a strong foundation in ML inference, deployment, and quality validation. Should be capable of end-to-end ownership from model deployment ...

USM

JB061761 - MLOps Engineer

Grapevine, TX · On-site

$80/hr

Shell scripting and automation Containerization and orchestration (Docker, Kubernetes) Building reliable, scalable backend systems for ML inference Preferred / Nice-to-Have Experience with computer ...

Johnson Controls

Ai/ML Engineer

Dallas, TX · On-site

$85K - $107K/yr

This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...

Catalyst Labs

ML Engineer

Dallas, 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 : • ...

Johnson Controls

Ai/ML Engineer

Dallas, TX · On-site

$85K - $107K/yr

This role is pivotal in enabling enterprise-scale ML and generative AI capabilities by building ... Design highly available and performant serving environments for LLM inference using Azure ...

1 point system

AI/ML Engineer

Plano, TX · On-site

Core Responsibilities (AI/ML, Python, AWS, GenAI) * Design and implement end-to-end AI/ML and ... Build robust MLOps workflows, including model versioning, containerized training/inference ...

ClifyX

Senior AI/ML Developer

Irving, TX · On-site

Preferred : • Financial domain expertise (risk, fraud, forecasting, customer intelligence). • Advanced ML topics: time series, graph ML, optimization, causal inference. • ONNX/TensorRT model ...

Ruri Software Technologies LLC

ML Engineer

Irving, TX · On-site

Development and Implement data pipelines and ML pipelines to facilitate model inference (both Real-time and batch) * Analyze large, complex data sets to identify the most performant way to process ...

Toyota

Senior AI/ML Platform Engineer

Plano, TX · On-site

$100K - $137K/yr

As a Senior AI/ML Platform Engineer, you will design, build, and support scalable platform ... Develop reusable patterns for inference services, prompt flow integration, and performance tuning ...

Toyota

Lead AI/ML Platform Engineer

Plano, TX · On-site

$98K - $129K/yr

You will help enable secure, production-ready MLOps and LLMOps infrastructure that supports model training, inference, orchestration, and retrieval-augmented generation. The Lead AI/ML Platform ...

ConnectedX, Inc.

ML Engineer

Plano, TX · On-site

ML Engineer Location: Remote -ML Engineer Job Summary We are seeking a talented AI/ML Engineer to ... Optimize model inference performance for scalability and reliability. · Document model ...

Wellfit Technologies

Senior Data & AI/ML Engineer

Irving, TX · On-site

$101K - $138K/yr

Train, evaluate, and apply models for inference, insight generation, anomaly detection, and ... Experience with AI/ML concepts including model training, inference, evaluation, and applied machine ...

Socket.dev

Senior Data & AI/ML Engineer

Irving, TX · On-site

$140 - $190/hr

Train, evaluate, and apply models for inference, insight generation, anomaly detection, and ... Experience with AI/ML concepts including model training, inference, evaluation, and applied machine ...

Texas Instruments

AI/ML Engineer

Richardson, TX · On-site

... inference pipelines under technical guidance * Work with GenAI & LLMs - contribute to LLM-based ... Advanced AI/ML capabilities - experience building with LLMs or generative AI APIs; familiar with ...

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Showing results 1-20

All JobsMl Inference JobsMl Inference Jobs in Garland, TX

Ml Inference information

See Garland, TX salary details

$36.2K

$118.6K

$189.9K

How much do ml inference jobs pay per year?

As of Aug 11, 2026, the average yearly pay for ml inference in Garland, TX is $118,587.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $131,400.00 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 Garland, TX? For Ml Inference jobs in Garland, TX, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Garland, TX look for? The top searched job categories for Ml Inference jobs in Garland, TX are:
What cities near Garland, TX are hiring for Ml Inference jobs? Cities near Garland, TX with the most Ml Inference job openings:
Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Garland, TX as of August 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $118,587 per year, or $57 per hour.

Machine Learning Platform Engineer

eTeam

Richardson, TX • On-site

Full-time

Re-posted 19 hours ago

Job description

Job Summary:
eTeam is seeking a Machine Learning Platform Engineer to work onsite in Richardson, TX. The role requires strong expertise in ML inference, deployment, and quality validation, with responsibilities including end-to-end ownership from model deployment to user impact.
Responsibilities:
• Should have 7 years of experience with a strong foundation in ML inference, deployment, and quality validation. Should be capable of end-to-end ownership from model deployment to user impact, with the ability to quickly adapt to new technologies.
• Should have strong expertise in ML benchmarking and collaboration, along with hands-on experience deploying models on cloud platforms, preferably GCP. Familiarity with Java/JVM-based systems for model integration, streaming data architectures, and hybrid (on-prem and cloud) environments is essential.
• Must possess solid system design and distributed systems knowledge for troubleshooting, and hands-on experience with ML frameworks such as TensorFlow, PyTorch, or JAX.
Qualifications:
Required:
• 7 years of experience with a strong foundation in ML inference, deployment, and quality validation.
• Capability of end-to-end ownership from model deployment to user impact.
• Ability to quickly adapt to new technologies.
• Strong expertise in ML benchmarking and collaboration.
• Hands-on experience deploying models on cloud platforms, preferably GCP.
• Familiarity with Java/JVM-based systems for model integration.
• Experience with streaming data architectures.
• Experience in hybrid (on-prem and cloud) environments.
• Solid system design and distributed systems knowledge for troubleshooting.
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or JAX.
Company:
eTeam is a staffing agency that also provides payrolling services. Founded in 1999, the company is headquartered in Somerset, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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