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Ml Inference Jobs in Texas (NOW HIRING)

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 ...

Neurophos

Senior ML Engineer, Optimization

Austin, TX · On-site

$150 - $190/hr

Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The ... The ideal candidate will bridge the gap between cutting-edge ML research and novel hardware ...

Socket.dev

Senior ML Engineer, Optimization

Austin, TX · On-site

$150 - $230/hr

Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The ... The ideal candidate will bridge the gap between cutting‑edge ML research and novel hardware ...

Neurophos Inc

Senior ML Engineer, Optimization

Austin, TX · On-site

$160K - $215K/yr

Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The ... The ideal candidate will bridge the gap between cutting-edge ML research and novel hardware ...

Nvidia

Principal Architect, AI Networking

Austin, TX · On-site

Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. CUDA programming and NVIDIA GPU architecture expertise. Proved experience influencing product ...

SEMRON

ML Research Scientist

Austin, TX · On-site

SEMRON is redefining what's possible in AI hardware, and they are seeking an ML Research Scientist to design algorithms and quantization schemes for efficient inference on their analog in-memory ...

Carmax

Engineer II, AI/ML

Dallas, TX

$96K - $132K/yr

Experience with model serving platforms and real-time inference (Azure ML endpoints, Databricks ... SageMaker, or equivalent) * Experience designing or operating microservices and distributed ...

CarMax, Inc.

Engineer II, AI/ML

Plano, TX · On-site

$91K - $124K/yr

Experience with model serving platforms and real-time inference (Azure ML endpoints, Databricks ... SageMaker, or equivalent) * Experience designing or operating microservices and distributed ...

Carmax

Engineer II, AI/ML

Plano, TX · On-site

$88K - $133K/yr

Experience with model serving platforms and real-time inference (Azure ML endpoints, Databricks ... SageMaker, or equivalent) * Experience designing or operating microservices and distributed ...

Nvidia

Principal Architect, AI Networking

Austin, TX · On-site

Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. * CUDA programming and NVIDIA GPU architecture expertise. * Proved experience influencing ...

Toyota

Lead AI/ML Platform Engineer

Plano, TX

$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 ...

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Ml Inference information

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.

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Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Texas as of August 2026, with employment types broken down into 44% Full Time, 11% Part Time, and 45% Contract. Highlights an 89% In-person, and 11% Remote job distribution.

ML Engineer

Ruri Software Technologies LLC

Irving, TX • On-site

Full-time

Re-posted 19 days ago

Job description

Job Title: ML Engineer
Work Location: Irving,TX (Hybrid)
Duration: 8+ Months
Job Description:
  • 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 large volume data using spark, hive and SQL
  • Collaborate with cross functional teams to gather reqs and design scalable solutions
  • Work on deployment of machine learning models - on prem cloud and Kubernetes
  • Monitor the performance of data pipelines and make improvements as necessary
  • Stay up to date with latest advances in big data processing
  • Productionalize time series and registration of real-time models

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