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Temporary Machine Learning Testing Jobs in Texas

Avride

Machine Learning Engineer

Austin, TX · On-site

Develop efficient workflows for training, validation, and testing, incorporating distributed ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

ExtendMyTeam

Machine Learning Engineer

Austin, TX

Support experimentation, evaluation, testing, and continuous improvement of AI systems * Stay current with emerging AI, LLM, and machine learning technologies Required Experience / Ideal Background ...

Avride

Machine Learning Engineer

Austin, TX

Develop efficient workflows for training, validation, and testing, incorporating distributed ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

Apple

Machine Learning Engineer

Austin, TX · On-site

... and testing workflows. 4+ years of related experience building high throughput scalable applications or building machine learning models.Proficiency in one or more object-oriented programming ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... testing and validation EXPERIENCE AND KNOWLEDGE • Bachelor's degree in related field and 5-8 ...

Q2

Machine Learning Engineer

Austin, TX

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... testing and validation EXPERIENCE AND KNOWLEDGE Bachelor's degree in related field and 5-8 years ...

Visa

Director, Machine Learning

Austin, TX · On-site

This includes idea generation, architecture, design, development, and testing of products ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

Visa

Director, Machine Learning

Austin, TX · Hybrid

This includes idea generation, architecture, design, development, and testing of products ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

Visa

Director, Machine Learning

Austin, TX · Hybrid

This includes idea generation, architecture, design, development, and testing of products ... We are currently looking for a Director of Machine Learning who will take the lead and manage ...

Apple

Machine Learning Engineer

Austin, TX

$132.10K - $244.60K/yr

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

Apple

Machine Learning Engineer

Austin, TX

$132.10K - $244.60K/yr

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

Apple

Machine Learning Engineer

Austin, TX

$132.10K - $244.60K/yr

... and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable ... Experience building data processing pipelines and large scale machine learning systems with ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121.40K - $160.10K/yr

... testing. You will also work on building out a SOTA machine learning platform. We're looking for strong engineers well versed with modern large scale machine learning platforms with a solid grasp of ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years ... Solid understanding of statistical analysis , probability, hypothesis testing, and experimental ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in ... Solid understanding of statistical analysis , probability, hypothesis testing, and experimental ...

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Temporary Machine Learning Testing information

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and test AI models, and their role involves understanding complex algorithms and data handling. While AI automation tools can assist with certain tasks, MLEs are essential for creating, fine-tuning, and maintaining AI systems, making complete replacement unlikely in the near term. Skills in programming, data analysis, and model evaluation remain critical for MLEs working alongside AI technologies.

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

AspectTemporary Machine Learning TestingData Scientist
CredentialsTypically requires knowledge of machine learning tools, programming, and basic statisticsRequires advanced degrees (e.g., Master’s or PhD) in data science, statistics, or related fields
Work EnvironmentProject-based, often temporary roles focused on testing models and algorithmsLong-term, strategic roles involving data analysis, model development, and business insights
Industry UsageCommon in tech, finance, and research sectors for specific testing tasksWidely used across industries for data-driven decision making

Temporary Machine Learning Testing roles focus on evaluating and validating machine learning models in short-term projects, while Data Scientists develop, implement, and interpret complex data models for ongoing business strategies. Both roles require technical skills, but Data Scientists typically have higher educational credentials and broader responsibilities.

What are popular job titles related to Temporary Machine Learning Testing jobs in Texas? For Temporary Machine Learning Testing jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Testing jobs in Texas look for? The top searched job categories for Temporary Machine Learning Testing jobs in Texas are:
What cities in Texas are hiring for Temporary Machine Learning Testing jobs? Cities in Texas with the most Temporary Machine Learning Testing job openings:
Temporary Machine Learning Testing jobs near you

Machine Learning Engineer

Avride

Austin, TX • On-site

Full-time

Posted 5 days ago

Job description

About the Team
Avride develops autonomous vehicle and delivery robot technology, leveraging deep expertise in autonomous systems. With the recent launch of our robotaxi service in Dallas, we are accelerating innovation and redefining the future of mobility.
Our team builds self-driving solutions from the ground up, with machine learning at the core of our development pipeline to enable safe and intelligent navigation. We design and deploy state-of-the-art models to address key challenges in autonomous systems, utilizing advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). These models power both onboard and offboard applications, ensuring robust and efficient operation. Your work will directly contribute to enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.
About the Role
We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In this role, you will conduct experiments, manage large-scale datasets, and implement deep learning models tailored for autonomous systems.
You will utilize cloud platforms, orchestration tools, and machine learning frameworks to develop scalable and efficient solutions. Additionally, you will analyze the latest research, assess the applicability of emerging deep learning techniques, and drive innovation in autonomous vehicle technology.
What You'll Do
  • Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ensure efficiency, scalability, and robustness. This may include developing models for understanding a self-driving vehicle's surroundings or predicting the intentions of other road users.
  • Curate and Manage Large-Scale Datasets: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation.
  • Enhance and Maintain Training Pipelines: Develop efficient workflows for training, validation, and testing, incorporating distributed training, hyperparameter tuning, and automated monitoring.
  • Improve Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across various hardware platforms.
  • Explore and Apply Cutting-Edge ML Techniques: Stay up to date with advancements in deep learning and experiment with novel approaches to improve model performance.
  • Collaborate with Cross-Functional Teams: 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 fundamental machine learning algorithms and neural network techniques.
  • Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.
  • At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.
  • Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.
  • Working knowledge of C++ and SQL.
  • Ability to quickly absorb new concepts by reviewing research papers, technical reports, and documentation.
  • Strong collaboration and communication skills, with the ability to align technical work with business objectives and drive results.
Nice to Have
  • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.
  • Experience developing ML algorithms for autonomous vehicles or robotics applications.
  • Familiarity with neural network deployment and optimization tools such as triton, TensorRT, or similar frameworks.
  • Proven ability to set and achieve mid- and long-term goals, prioritize tasks, and meet deadlines independently.
  • Experience working in cross-functional teams within a multidisciplinary environment.
  • Publications in top-tier ML conferences or contributions to patent applications or ML-related open-source projects.

Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.
Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai.

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