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Senior Machine Learning Software Engineer Jobs in Dallas, TX

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/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 ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud ...

Samprasoft

Machine Learning Engineer

Roanoke, TX · On-site

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI ... Experience building ML infrastructure, with an eye towards software engineering * Excellent ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · Hybrid

Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to identify opportunities for leveraging machine learning techniques to drive business ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to identify opportunities for leveraging machine learning techniques to drive business ...

Yum!

Machine Learning Engineer II

Plano, TX

Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to identify opportunities for leveraging machine learning techniques to drive business ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

We're more than just a software company -- we're building the AI-native platform where the real ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

We're more than just a software company -- we're building the AI-native platform where the real ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

Toyota

Sr. Machine Learning Engineer

Plano, TX

$117K - $154K/yr

Software engineering and production ML experience: 2+ years of hands-on experience building ... AWS Certified Machine Learning Engineer - Associate, Solutions Architect, Developer, or equivalent ...

Clevanoo LLC

Be Seen First

Machine Learning Engineer

Dallas, TX · Remote

Their expertise in machine learning frameworks and software engineering ensures that the predictive power of models seamlessly integrates into everyday operations. POSITION REQUIREMENTS ...

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All JobsSenior Machine Learning Software Engineer JobsSenior Machine Learning Software Engineer Jobs in Dallas, TX

Senior Machine Learning Software Engineer information

See Dallas, TX salary details

$74.7K

$141.7K

$189.9K

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

As of Jun 22, 2026, the average yearly pay for senior machine learning software engineer in Dallas, TX is $141,749.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,200.00 and $159,800.00 per year, depending on experience, location, and employer.

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

AspectSenior Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related; experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, integrates algorithms into products, collaborates with engineering teamsAnalyzes data, builds statistical models, visualizes insights, collaborates with business teams
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, healthcare

While both roles involve working with data and algorithms, Senior Machine Learning Software Engineers focus on developing and deploying scalable ML models within software systems, whereas Data Scientists primarily analyze data to generate insights and inform business decisions.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Software Engineer, and why are they important?

A Senior Machine Learning Software Engineer requires deep expertise in machine learning algorithms, statistical analysis, and strong programming skills in languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, as well as experience with cloud platforms and version control systems, is standard. Exceptional problem-solving, leadership, and communication skills help drive project success and mentor junior engineers. These competencies are crucial for designing scalable ML solutions, ensuring code quality, and effectively collaborating within cross-functional teams.

What is a Senior Machine Learning Software Engineer?

A Senior Machine Learning Software Engineer is an experienced professional who designs, develops, and deploys machine learning models and systems to solve complex problems. They work closely with data scientists, engineers, and other stakeholders to build scalable and efficient solutions that leverage large data sets and advanced algorithms. Their responsibilities often include architecting ML pipelines, optimizing model performance, and mentoring junior team members. Typically, they have a strong background in computer science, programming, and applied mathematics, along with several years of hands-on experience in machine learning and software engineering.

What are some common challenges Senior Machine Learning Software Engineers face when deploying models to production?

Senior Machine Learning Software Engineers often encounter challenges such as ensuring model scalability, maintaining performance under real-world data conditions, and integrating models seamlessly with existing systems. Handling data drift and monitoring model predictions for accuracy over time are also critical responsibilities. Collaboration with data engineers, DevOps, and product teams is essential to address these challenges and ensure robust, reliable deployments.
What are popular job titles related to Senior Machine Learning Software Engineer jobs in Dallas, TX? For Senior Machine Learning Software Engineer jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Software Engineer jobs in Dallas, TX look for? The top searched job categories for Senior Machine Learning Software Engineer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Senior Machine Learning Software Engineer jobs? Cities near Dallas, TX with the most Senior Machine Learning Software Engineer job openings:
Senior Machine Learning Software Engineer jobs near you
Infographic showing various Senior Machine Learning Software Engineer job openings in Dallas, TX as of June 2026, with employment types broken down into 1% Locum Tenens, 71% Full Time, 21% Part Time, 2% Temporary, 4% Contract, and 1% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $141,749 per year, or $68.1 per hour.
Machine Learning Software Engineer II

Machine Learning Software Engineer II

Cambium Learning Group

Dallas, TX • On-site, Remote

$89K - $123K/yr

Full-time

Posted 18 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

14th of 191 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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