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Summer 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 ...

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 ...

Cymertek

Machine Learning Engineer

San Antonio, TX

Machine Learning Engineer LOCATIONSan Antonio, TX 78208 CLEARANCETS/SCI Full Poly (Please note this ... Software Engineering, Electrical Engineering, Robotics, Computational Biology, Physics, ect.

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 ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

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 ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the ...

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All JobsSummer Machine Learning Software Engineer JobsSummer Machine Learning Software Engineer Jobs in Texas

Summer Machine Learning Software Engineer information

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

AspectSummer Machine Learning Software EngineerSummer Data Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related fields; coding skills in Python, JavaBachelor's or Master's in Data Science, Statistics, or related fields; strong analytical skills
Work EnvironmentSoftware development teams, coding, model deploymentData analysis, statistical modeling, data visualization
Employer & Industry UsageTech companies, startups, research labsTech firms, finance, healthcare, consulting

While both roles involve working with data and algorithms, Summer Machine Learning Software Engineers focus on developing and deploying machine learning models through coding and software development. Summer Data Scientists primarily analyze data, build statistical models, and generate insights. The roles often overlap but differ in their core activities and skill emphasis.

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:
Summer 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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