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Machine Learning Software Engineer Jobs in Dallas, 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 ...

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 ...

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 ...

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 ...

Seven Seven Software

Software Engineer

Plano, TX · On-site

Leads communities of practice across Software Engineering to drive awareness and use of new and ... intelligence, machine learning, mobile, etc.) * In-depth knowledge of the financial services ...

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 ...

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Machine Learning Software Engineer information

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$63.1K

$146.6K

$204.2K

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

As of May 30, 2026, the average yearly pay for machine learning software engineer in Dallas, TX is $146,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $171,900.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

What are the key skills and qualifications needed to thrive in the Machine Learning Software Engineer position, and why are they important?

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.
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Machine Learning Software Engineer jobs near you
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 25 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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