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Temporary Machine Learning Scientist Jobs in Dallas, TX

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

D. preferred) in Computer Science, Machine Learning, or a closely related field. * Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.

Yum Brands

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Bachelor's or master's degree in computer science, engineering, mathematics, or a related field.

Yum! Brands

Machine Learning Engineer II

Plano, TX

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Bachelor's or master's degree in computer science, engineering, mathematics, or a related field.

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $138K/yr

Required : • 7+ years of experience in machine learning, data science, or related fields. • Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $138K/yr

Required : • 7+ years of experience in machine learning, data science, or related fields. • Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost ...

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 ... Collaborate closely with data engineers, data scientists, and product teams to integrate models ...

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All JobsMachine Learning Scientist JobsTemporary Machine Learning Scientist JobsTemporary Machine Learning Scientist Jobs in Dallas, TX

Temporary Machine Learning Scientist information

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a temporary machine learning scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.
What are the most commonly searched types of Machine Learning Scientist jobs in Dallas, TX? The most popular types of Machine Learning Scientist jobs in Dallas, TX are:
What are popular job titles related to Temporary Machine Learning Scientist jobs in Dallas, TX? For Temporary Machine Learning Scientist jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Scientist jobs in Dallas, TX look for? The top searched job categories for Temporary Machine Learning Scientist jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Temporary Machine Learning Scientist jobs? Cities near Dallas, TX with the most Temporary Machine Learning Scientist job openings:
Temporary Machine Learning Scientist jobs near you
Infographic showing various Temporary Machine Learning Scientist job openings in Dallas, TX as of August 2026, with employment types broken down into 20% Internship, and 80% Full Time. Highlights an 60% In-person, and 40% Remote job distribution.

Machine Learning Engineer

Quarterhill

Frisco, TX • On-site

Full-time

Medical, Dental, Retirement, PTO

Posted 24 days ago

Job description

Overview
Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will design, develop, and deploy state-of-the-artcomputer vision and language models that power scalable, real-world solutions. You'll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.
As part of our AI team, you'll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands-on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.
Responsibilities
  • Fine-tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
  • Develop vision-language models and Mixture of Experts architectures, from experimental design through production deployment.
  • Architect Retrieval-Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
  • Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
  • Contribute to our machine learning repositories and optimize models for performance, scalability, and real-time inference across edge and cloud environments.
  • Drive performance optimization and scalability of ML systems across edge and cloud environments.
  • Collaborate with cross-functional teams to integrate computer vision solutions into end-to-end products, translating research outcomes into measurable platform impact.

This list of responsibilities might not cover everything you'll end up doing.
Qualifications
  • 5+ years of hands-on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
  • Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
  • Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
  • Experience building and deploying LLM-based systems and Retrieval-Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
  • Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.

Benefits
We offer a Total Rewards plan designed with you and your family's health and wellness in mind that includes:
  • Paid days off (i.e. vacation, sick days, bereavement leave)
  • Health and Dental plans
  • Retirement plans
  • Employee and Family Assistance Program (EFAP)
  • Employee referral program

We welcome applicants from all backgrounds, regardless of race, color, religion, sex, veteran status, sexual orientation, gender identity, national origin, age, or disability or any other protected characteristics in accordance with applicable federal, state/provincial, and local laws. We're committed to creating a workplace where everyone feels valued and respected.
We appreciate all responses and will acknowledge only those being considered for an interview.
We respectfully request no calls or unsolicited resumes from Agencies.

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