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Ml Inference Jobs in Forney, TX (NOW HIRING)

Vizient

Sr AI/ML Engineer

Irving, TX · On-site

$102K - $179K/yr

Own AI/ML solutions end to end, from scoping and design through implementation, deployment, and ... Experience optimizing cost and performance for large-scale inference workloads preferred.

Vizient, Inc.

Sr AI/ML Engineer

Irving, TX · On-site

$102K - $179K/yr

Own AI/ML solutions end to end, from scoping and design through implementation, deployment, and ... Experience optimizing cost and performance for large-scale inference workloads preferred.

Winaxis

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Build and maintain scalable data pipelines for model training and inference. Develop AI-powered ...

Winaxis

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Build and maintain scalable data pipelines for model training and inference. Develop AI-powered ...

Noblesoft Technologies

Gen AI Lead

Dallas, TX · On-site

$138K - $170K/yr

Design, develop, and deploy AI/ML and Generative AI models for enterprise and telecom use cases. * Build and optimize data pipelines for training, validation, and inference processes. * Develop web ...

Winaxis

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Build and maintain scalable data pipelines for model training and inference. Develop AI-powered ...

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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 Jul 17, 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 a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.

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 engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.

Which 3 jobs will survive AI?

Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.

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.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

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 job categories do people searching Ml Inference jobs in Forney, TX look for? The top searched job categories for Ml Inference jobs in Forney, TX 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
Feature Lead - Technology, AI/ML

Feature Lead - Technology, AI/ML

Bank of America

Plano, TX • On-site

Full-time

Posted 16 days ago

Bank Of America rating

8.2

Company rating: 8.2 out of 10

Based on 520 frontline employees who took The Breakroom Quiz

44th of 149 rated banks

Job description

Job Description:
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates' physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Description:
This job is responsible for providing leadership, technical direction and oversight to a team delivering technology solutions. Key responsibilities of the job are to provide oversight of the design, implementation, and maintenance of complex computer programs, align technical solutions to business objectives, and ensure that coding practices/quality comply with software development standards. Job expectations include conducting multiple software implementations and applying both depth and breadth in knowledge of several technical competencies.
Position Summary:
This is a Lead position in Bank of America's Erica, Chat, and Voice Technology organization. The Team builds next generation AI and Search platforms to enable virtual financial assistant / AI and search capabilities across multiple channels.
Responsibilities:
  • Designs, develops and is accountable for feature delivery
  • Applies enterprise standards for solution design, coding and quality
  • Ensures solution meets product acceptance criteria with minimal technical debt
  • Guides the team on work breakdown and execution
  • Works with the Product Owner to ensure that product backlog/requirements are healthy, with clear acceptance criteria
  • Plays a team lead role (as an individual contributor) and mentors the team
  • Guides team members with skills and practices (planning and estimation, peer reviews, and other engineering practices)
  • Guides the team on solution design, AI/ML model integration, work breakdown, and execution.
  • Evaluates and applies emerging AI technologies, frameworks, and models to solve business problems.
  • Leads the deployment and optimization of AI workloads across CPU/GPU infrastructures and cloud platforms.
  • Ensures AI solutions meet enterprise standards for security, governance, observability, performance, and responsible AI practices.
  • Guides the team in implementing prompt engineering, retrieval strategies, model evaluation, and inference optimization techniques.
  • Drives technical innovation and adoption of AI/ML best practices across the organization.

Required Qualifications:
  • 5+ years of hands-on software development experience using Java, Python, or related technologies.
  • Strong software engineering skills with proficiency in Python and Java.
  • Experience building AI/ML-powered applications using machine learning and Generative AI techniques.
  • Knowledge of modern AI technologies including Transformers, Large Language Models (LLMs), Agentic AI, and Generative AI frameworks.
  • Experience implementing Retrieval Augmented Generation (RAG) pipelines and related retrieval techniques.
  • Experience deploying and optimizing AI applications on CPU/GPU infrastructure using technologies such as CUDA, vLLM, Triton, or equivalent inference platforms.
  • Understanding of supervised, unsupervised, and reinforcement learning methodologies.
  • Good understanding of source control systems such as Git and modern collaborative development practices.
  • Good interpersonal communication skills for technical and business conversations
  • Good analytical skills to break down requirements and solve complex problems
  • Proven task management and leadership skills
  • Experience building restful web services

Desired Qualifications:
  • Experience in performance tuning with good understanding of JVM internals
  • Experience with NoSQL databases like Cassandra
  • Experience in distributed caching frameworks like hazelcast, ignite, redis
  • Experience in modern JVM languages like groovy, scala
  • Experience with Full-stack development, especially including Angular
  • Experience with Generative AI
  • Spring MVC
  • Experience with Container technologies, such as Kubernetes and Docker
  • Experience working with NLP and Machine learning
  • Prior open source contributions
  • Background in mathematics or statistics
  • Proven task management and leadership skills
  • Experience working in agile teams
  • Experience building chatbot, conversational AI, or virtual assistant platforms.
  • Experience with Azure, AWS, or cloud-native AI platforms.
  • Experience with vector databases, embeddings, semantic search, and AI retrieval systems.
  • Experience with Elasticsearch, SOLR, OpenSearch, or related search technologies.
  • Experience with MLOps, model deployment, monitoring, and AI observability.
  • Experience with inference optimization frameworks, GPU acceleration, and distributed model serving.
  • Experience with prompt engineering, model evaluation, and AI safety/governance practices.

Skills:
  • Automation
  • Influence
  • Result Orientation
  • Stakeholder Management
  • Technical Strategy Development
  • Architecture
  • Business Acumen
  • Risk Management
  • Solution Delivery Process
  • Solution Design
  • Agile Practices
  • Analytical Thinking
  • Collaboration
  • Data Management
  • DevOps Practices

Bachelors or Master's Degree in Computer Science or related field
Shift:
1st shift (United States of America)
Hours Per Week:
40

What Bank Of America employees say

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About Bank Of America

Sourced by ZipRecruiter

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1998

Social media

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