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Ml Inference Jobs in Forney, TX (NOW HIRING)

Vizient

Senior Software Engineer

Irving, TX

$102K - $179K/yr

Support production deployment of ML models, LLM applications, RAG pipelines, and agentic AI systems while collaborating with AI/ML engineers to productionize model serving, inference pipelines, and ...

Vizient, Inc.

Senior Software Engineer

Irving, TX · On-site

$102K - $179K/yr

Support production deployment of ML models, LLM applications, RAG pipelines, and agentic AI systems while collaborating with AI/ML engineers to productionize model serving, inference pipelines, and ...

Vizient, Inc.

Senior Software Engineer

Irving, TX · On-site

$102K - $179K/yr

Support production deployment of ML models, LLM applications, RAG pipelines, and agentic AI systems while collaborating with AI/ML engineers to productionize model serving, inference pipelines, and ...

BMO Capital Markets

Senior Cloud Engineer AI

Dallas, TX · On-site

$81K - $151K/yr

SageMaker (training, pipelines, inference, JumpStart), Bedrock Deep hands-on expertise with Azure AI/ML services: Azure Machine Learning, Azure OpenAI, Azure AI Foundry Experience building MLOps ...

Deloitte

AI Engineer Consultant

Dallas, TX · Hybrid

Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...

Toyota

Security Dev Ops/ Platform Engineer, Lead

Plano, TX · On-site

$50.50 - $69.25/hr

Support ML training infrastructure (training jobs, model endpoints, model registry) * Build and maintain model serving infrastructure for production inference workloads * Ensure all processing occurs ...

Virtusa

Gen AI developer

Irving, TX · On-site

$116K - $157K/yr

... ML systemsStrong expertise in Python and data libraries (NumPy, Pandas, etc.) Proven experience ... training, inference, and monitoring Strong understanding of system architecture, distributed ...

Elevance Health

Gen AI Engineer

Grand Prairie, TX · Hybrid

... for inference optimization; RAG architecture design and implementation. * Advanced cloud infrastructure (AWS EKS/ECS, GCP GKE, Azure AKS) knowledge. * Containerization strategies for ML workloads;

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Showing results 41-60

All JobsMl Inference JobsMl Inference Jobs in Forney, TX

Ml Inference information

See Forney, TX salary details

$33.8K

$110.6K

$177K

How much do ml inference jobs pay per year?

As of Aug 6, 2026, the average yearly pay for ml inference in Forney, TX is $110,570.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,700.00 and $122,500.00 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 Forney, TX? For Ml Inference jobs in Forney, TX, the most frequently searched job titles are:
What cities near Forney, TX are hiring for Ml Inference jobs? Cities near Forney, TX with the most Ml Inference job openings:
Ml Inference jobs near you

Senior / Staff ML Training Optimization Engineer

Waabi

Dallas, TX • On-site, Remote

$141K - $249K/yr

Full-time

Re-posted 9 hours ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will...
- Build standardized distributed training frameworks for research and production, drive our training towards new levels of stability and efficiency.
- Comprehensively profile model runtime and memory to pinpoint performance bottlenecks.
- Identify and evaluate emerging technologies that can be adopted into Waabi’s training and inference frameworks. Examples include designing new CUDA kernels, quantization-aware training and inference, and compilation/deployment techniques.
- Work with researchers and ML engineers on best-practices for optimal resource usage.
- Create and improve tooling and dashboards to ensure broad adoption of your work.
 
Qualifications:
- MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Computer Science, Robotics and/or similar technical field(s) of study.
- Solid coding proficiency in a variety of coding languages including Python, C++ or Rust.
- Experience in deep learning frameworks such as PyTorch or Jax.
- Skilled in profiling CPU and GPU code using tools such as PyTorch Profiler and NVIDIA Nsight.
- Open-minded and collaborative team player with willingness to help others.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
 
Bonus/nice to have:
- Experience in identifying when custom CUDA kernels are needed, and implementing them.
- Experience in Bazel in a monorepo environment, and integrating third party packages into dev environments.
- Experience with Kubernetes-based training platforms.
 
The US yearly salary range for this role is: $141,000 - $249,000 in addition to competitive perks & benefits. Waabi’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
Waabi provides a competitive benefits package that includes:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage.
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- World-class facility that includes a gym, games room (ping pong table, video game consoles, board games, etc), multiple collaborative working spaces and a gorgeous patio!(when in office)
- As we grow, this list continues to evolve! 

Waabi is an equal opportunity employer that celebrates diversity and is committed to creating a supportive, inclusive, and accessible environment for all employees. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.