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Machine Learning Engineer Software Engineer Jobs in Coppell, TX

Intuit

Staff Machine Learning Engineer

Plano, TX

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Intuit

Staff Machine Learning Engineer

Plano, TX

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI ... Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ...

Capital One

Senior Machine Learning Engineer

Plano, TX · On-site +1

$100K - $137.30K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Collaborate as part of a cross-functional Agile team to create and enhance software that enables ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98.10K - $129.20K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Collaborate as part of a cross-functional Agile team to create and enhance software that enables ...

Vanguard

Machine Learning Engineer, Specialist

Dallas, TX

$113.30K - $136K/yr

Performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment. Leverages detailed understanding of ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Synergistic it

AI & Machine Learning Engineer

Dallas, TX

$113.70K - $136.60K/yr

In JOPP, the demand typically includes roles such as entry-level software programmer , Java full ... and machine learning/AI engineer . In other words, SynergisticIT focuses on building candidates ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · Remote

$94.30K - $129.50K/yr

We're more than just a software company -- we're building the cloud and AI-native platform where ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · Remote

$94.30K - $129.50K/yr

We're more than just a software company -- we're building the cloud and AI-native platform where ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

Synergistic it

AI & Machine Learning Engineer

Dallas, TX

$113.70K - $136.60K/yr

In JOPP, the demand typically includes roles such as entry-level software programmer , Java full ... and machine learning/AI engineer . In other words, SynergisticIT focuses on building candidates ...

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All JobsMachine Learning Engineer Software Engineer JobsMachine Learning Engineer Software Engineer Jobs in Coppell, TX

Machine Learning Engineer Software Engineer information

See Coppell, TX salary details

$58.6K

$136.2K

$189.7K

How much do machine learning engineer software engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for machine learning engineer software engineer in Coppell, TX is $136,189.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,800.00 and $159,700.00 per year, depending on experience, location, and employer.

How do Machine Learning Engineer Software Engineers typically collaborate with data scientists and software development teams?

Machine Learning Engineer Software Engineers often serve as a bridge between data scientists and software development teams. They work closely with data scientists to understand and implement machine learning models, ensuring that the models are production-ready and scalable. Additionally, they collaborate with software engineers to integrate these models into existing applications, monitor their performance, and address any engineering challenges. This cross-functional collaboration is essential for delivering robust, end-to-end AI solutions that add real value to the business.

What is the difference between Machine Learning Engineer Software Engineer vs Data Scientist?

AspectMachine Learning EngineerSoftware Engineer
Required CredentialsBachelor's/Master's in CS, specialized ML coursesBachelor's in CS or related field
Work EnvironmentDevelops ML models, algorithms, data pipelinesBuilds software applications, systems, APIs
Industry UsageAI/ML projects, data-driven solutionsWeb, mobile, enterprise software

Machine Learning Engineers focus on designing and deploying ML models, requiring expertise in algorithms and data handling. Software Engineers develop broader software applications, emphasizing coding and system architecture. While both roles require programming skills, ML Engineers specialize in AI/ML tasks, whereas Software Engineers work across various software domains.

What are popular job titles related to Machine Learning Engineer Software Engineer jobs in Coppell, TX? For Machine Learning Engineer Software Engineer jobs in Coppell, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Software Engineer jobs in Coppell, TX look for? The top searched job categories for Machine Learning Engineer Software Engineer jobs in Coppell, TX are:
What cities near Coppell, TX are hiring for Machine Learning Engineer Software Engineer jobs? Cities near Coppell, TX with the most Machine Learning Engineer Software Engineer job openings:
Machine Learning Engineer Software Engineer jobs near you
Infographic showing various Machine Learning Engineer Software Engineer job openings in Coppell, TX as of May 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $136,189 per year, or $65.5 per hour.
Machine Learning Software Engineer II

Machine Learning Software Engineer II

Cambium Learning Group

Dallas, TX • On-site, Remote

$89.90K - $123.10K/yr

Full-time

Posted 24 days ago

Cambium Learning Group rating

9.2

Company rating: 9.2 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

12th of 183 rated software companies

Job description

Cambium Learning® Group is an award-winning educational technology solutions leader dedicated to helping all students reach their potential through individualized and differentiated instruction. Using a research-based, personalized approach, Cambium Learning Group delivers SaaS resources and instructional products that engage students and support teachers in fun, positive, safe and scalable environments. These solutions are provided through Learning A-Z® (online differentiated instruction for elementary school reading, writing and science), ExploreLearning® (online interactive math and science simulations, a math fact fluency solution, and a K-2 science solution), Voyager Sopris Learning® (blended solutions that accelerate struggling learners to achieve in literacy and math and professional development for teachers), and VKidz Learning (online comprehensive homeschool education and programs for literacy and science). We believe that every student has unlimited potential, that teachers matter, and that data, instruction, and practice are the keys to success in the classroom and beyond.
Job Overview:
We are seeking a talented Machine Learning Engineer II to join our CAI machine learning and scoring development team. In this role, you will be the crucial bridge between applied research and production systems. Working alongside a cross-functional group of mathematicians, computer scientists, psychometricians, and statisticians, you will design and deploy custom machine learning solutions for our clients and internal platforms.
The ideal candidate is a full-stack ML practitioner who is equally comfortable discussing algorithmic design with researchers and architecting scalable, low-latency production systems. You will own the full software development lifecycle-transforming research prototypes into optimized, production-ready solutions using modern AWS infrastructure such as SageMaker, ECS, and Lambda, with an emphasis on high-throughput inference and PyTorch-to-ONNX model optimization.
Job Responsibilities:
  • Full-Lifecycle ML Development: Lead the transition of machine learning models from theoretical prototypes into scalable, high-performance production systems.
  • AWS Cloud Architecture & Deployment: Architect and deploy ML solutions utilizing AWS ECS (Elastic Container Service) for containerized workloads and AWS Lambda for serverless, event-driven inference pipelines.
  • Model & Inference Optimization: Optimize PyTorch models for production deployment by converting them to ONNX formats. Apply advanced inference optimization techniques (quantization, pruning, ONNX Runtime) and memory-efficient attention mechanisms like Flash Attention to minimize latency and maximize throughput.
  • Infrastructure & Engineering Best Practices: Champion infrastructure best practices for machine learning systems, establishing reliable CI/CD pipelines, and ensuring robust, secure, and reproducible deployments across the AWS ecosystem.
  • Algorithm Engineering: Design, develop, and evaluate algorithms that generate descriptive, diagnostic, predictive, and prescriptive insights from both structured and unstructured data.
  • Robust Software Engineering: Write clean, efficient, and well-tested code. Complete rigorous testing, debugging, and documentation to ensure seamless installation and long-term maintenance.
  • Cross-Functional Collaboration: Actively participate in research discussions, requirements gathering, and system design alongside domain experts to build tailored scoring and ML solutions.

Job Requirements:
  • Experience: 2-5 years of industry experience in Machine Learning Engineering, Software Engineering, or Data Science, with a proven track record of architecting and deploying models to production.
  • Cloud & MLOps Infrastructure: Deep, hands-on experience with the AWS ecosystem, specifically AWS ECS and Lambda. Solid understanding of containerization (Docker) and event-driven architectures.
  • Programming Proficiency: Strong proficiency in modern programming languages used in ML (e.g., Python, C++, Java) and familiarity with industry-standard coding practices.
  • ML Frameworks & Advanced Optimization: Hands-on experience with PyTorch and other machine learning libraries (e.g., Scikit-Learn, TensorFlow). Deep understanding of model optimization pipelines, including PyTorch to ONNX conversions, ONNX Runtime, and scaling attention mechanisms (e.g., Flash Attention).
  • Data Systems: Experience working with large-scale computing frameworks, data analysis systems, and relational/non-relational databases.

Nice to Have's:
  • AWS SageMaker: Experience utilizing AWS SageMaker for managed model training and hosting.
  • Advanced LLMOps & Fine-Tuning: Hands-on experience applying modern parameter-efficient fine-tuning methods (such as LoRA and qLoRA) to large language models.
  • AI Agents: Experience building, integrating, and deploying autonomous or semi-autonomous AI agents to automate complex workflows and connect ML models with external tools/APIs.
  • NLP Expertise: Proven experience and familiarity with deep learning technologies applied specifically to Natural Language Processing (NLP) and complex text-based modeling.
  • Cross-Disciplinary Collaboration: Experience collaborating with specialized researchers (e.g., psychometricians, statisticians) to operationalize complex mathematical concepts.
  • Infrastructure as Code: Experience implementing IaC using tools like Terraform or AWS CloudFormation.
  • Model Monitoring: Experience setting up comprehensive model monitoring systems to detect data drift, concept drift, and model degradation in production AWS environments.

To apply for this opportunity, simply click on the "Apply" button and submit a cover letter and resume.
An Equal Opportunity Employer
We are dedicated to fostering a culture that celebrates unique backgrounds, ideas, and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, gender, gender identity/expression, sexual orientation, national origin, protected veteran status, or disability.

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