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Contract Machine Learning Software Engineer Jobs in Texas

ExtendMyTeam

Machine Learning Engineer

Austin, TX

... software delivery, and streamline implementation processes across a large-scale delivery ... Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI ...

Cymertek

Machine Learning Engineer

San Antonio, TX

... Software Engineering, Electrical Engineering, Robotics, Computational Biology, Physics, ect ... Most contracts allow additional experience (4-5 years) in lieu of a Bachelor's Degree. Some ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

... Software Engineering, Electrical Engineering, Robotics, Computational Biology, Physics, ect ... Most contracts allow additional experience (4-5 years) in lieu of a Bachelor's Degree. Some ...

Avride

Machine Learning Engineer

Austin, TX

Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems. What You'll Need * Strong understanding of ...

Striveworks

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121K - $160K/yr

You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities. You're right for this opportunity if you value ...

Apple

Machine Learning Engineer

Austin, TX

$132K - $244K/yr

Description To be successful, candidates will need a machine learning background, proven software ... Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ...

Samprasoft

Machine Learning Engineer

Roanoke, TX

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

Apple

Machine Learning Engineer

Austin, TX

$132K - $244K/yr

Description To be successful, candidates will need a machine learning background, proven software ... Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ...

Apple

Machine Learning Engineer

Austin, TX

$132K - $244K/yr

Description To be successful, candidates will need a machine learning background, proven software ... Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ...

Mariana Minerals

Machine Learning Engineer

Houston, TX · On-site

Mariana Minerals is a software-first, vertically integrated minerals company focused on supplying critical minerals for modern energy and technology. They are seeking a Machine Learning Engineer to ...

PROS

Machine Learning Engineer II

Houston, TX · On-site

$93K - $127K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the ... Partner with software engineers to integrate ML solutions into the platform and meet SLA ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems. What You'll Need * Strong understanding of ...

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Contract Machine Learning Software Engineer information

How does a Contract Machine Learning Software Engineer typically collaborate with full-time team members during a project?

As a Contract Machine Learning Software Engineer, you will often work closely with full-time data scientists, software engineers, and product managers. Collaboration usually happens through regular stand-up meetings, code reviews, and shared documentation platforms. Despite being a contractor, you’re expected to integrate seamlessly with the team, communicate progress transparently, and adapt to the company’s workflows. Building strong relationships and proactively seeking feedback can help ensure your contributions align with the project’s goals and timelines.

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

AspectContract Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master’s in CS, ML, or related fields; experience with ML frameworksBachelor's or Master’s in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentProject-based, often remote, focused on developing ML models and softwareData analysis, visualization, and interpretation, often in research or business settings
Employer & Industry UsageTech companies, startups, consulting firms; used for deploying ML solutionsResearch institutions, finance, healthcare, and tech; used for insights and decision-making

The main difference is that Contract Machine Learning Software Engineers focus on developing and deploying ML models as software solutions, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary objectives and work environments differ.

Which 5 jobs will survive AI?

For a Contract Machine Learning Software Engineer, roles that involve complex problem-solving, creativity, and human judgment are more likely to persist, such as AI research, data science, cybersecurity, software architecture, and technical consulting. These jobs require specialized skills, domain expertise, and adaptability that AI tools currently cannot fully replicate. Continuous learning and proficiency with AI and machine learning tools will help maintain relevance in this evolving field.

What engineers make $500,000?

Senior machine learning software engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation may include base salary, bonuses, and stock options, especially in competitive markets or executive-level roles.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI research director, often involving advanced skills in deep learning, data science, and software engineering. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working with cutting-edge AI technologies. Compensation at this level reflects the complexity and impact of the work, often including bonuses and stock options.

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

To thrive as a Contract Machine Learning Software Engineer, you need a strong background in computer science, proficiency in programming languages like Python, and expertise in machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, along with knowledge of version control systems like Git, is essential. Strong problem-solving abilities, communication skills, and the ability to work independently or with cross-functional teams make someone stand out in this role. These skills ensure efficient delivery of scalable machine learning solutions that meet client requirements and project timelines.

How much do contract software engineers make?

Contract machine learning software engineers typically earn between $50 and $150 per hour, depending on experience, location, and project complexity. Rates can vary based on skills in specific frameworks, tools, and the duration of the contract.

What is a Contract Machine Learning Software Engineer?

A Contract Machine Learning Software Engineer is a professional who is hired on a temporary or project basis to design, develop, and deploy machine learning models and systems. They often work with organizations that need specialized expertise for a limited duration, helping to build algorithms, analyze data, and integrate AI solutions into existing software products. Contract engineers typically have strong backgrounds in programming, mathematics, and data science, and they may work remotely or on-site. Their responsibilities can range from data preprocessing and model training to deploying models in production environments. This arrangement allows companies to access advanced machine learning skills without committing to a full-time hire.
What are the most commonly searched types of Machine Learning Software Engineer jobs in Texas? The most popular types of Machine Learning Software Engineer jobs in Texas are:
What cities in Texas are hiring for Contract Machine Learning Software Engineer jobs? Cities in Texas with the most Contract Machine Learning Software Engineer job openings:
Contract 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

$89K - $123K/yr

Full-time

Posted 14 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 190 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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