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Contract Machine Learning Research Scientist Jobs in Texas

webAI

AI Research Scientist

Austin, TX · On-site

The AI Research Scientist will design, train, evaluate, and optimize cutting-edge machine learning models, collaborating with various teams to ensure innovations have real-world impact.

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Contract Machine Learning Research Scientist information

What are the key skills and qualifications needed to thrive as a contract machine learning research scientist?

To thrive as a Contract Machine Learning Research Scientist, you need advanced knowledge of machine learning algorithms, statistical modeling, and a graduate degree in computer science, mathematics, or a related field. Expertise with programming languages such as Python or R, familiarity with ML frameworks like TensorFlow or PyTorch, and experience using version control systems are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills set standout candidates apart in collaborative and fast-paced research environments. These skills are crucial for developing innovative solutions, interpreting complex data, and delivering high-quality research outcomes within contractual timelines.

What does a contract machine learning research scientist do?

A Contract Machine Learning Research Scientist is a professional hired on a temporary or project basis to design, develop, and implement machine learning models and algorithms. They collaborate with teams to analyze data, conduct experiments, and improve AI systems, often in academic, industrial, or commercial settings. Their work typically involves researching new techniques, publishing findings, and translating research into practical applications. Since they work on a contract basis, their roles may vary depending on the project's needs and duration.

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

AspectContract Machine Learning Research ScientistData Scientist
CredentialsMaster's or PhD in CS, ML, or related fieldsBachelor's or Master's in CS, Statistics, or related fields
Work EnvironmentResearch labs, R&D teams, academic collaborationsBusiness analytics, product teams, data-driven decision making
Employer & Industry UsageTech companies, research institutions, startupsFinance, healthcare, e-commerce, tech firms

Contract Machine Learning Research Scientists focus on developing new algorithms and conducting research, often in academic or R&D settings. Data Scientists analyze data to generate insights and support business decisions. While both roles require strong ML knowledge, the research scientist role emphasizes innovation and experimentation, whereas data scientists focus on applying existing models to real-world problems.

What are some common challenges faced by contract machine learning research scientists when working on short-term projects?

Contract machine learning research scientists often encounter challenges such as limited timeframes to achieve research milestones, quickly adapting to new domains or datasets, and efficiently integrating with existing teams. As short-term contributors, they must rapidly understand the project's context and deliver impactful results within strict deadlines. Clear communication and proactive collaboration with permanent staff are essential to ensure alignment with project goals and to maximize the value delivered during the contract period.
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Contract Machine Learning Research Scientist jobs near you

AI Research Scientist

webAI

Austin, TX • On-site

Full-time

Re-posted 15 days ago

Job description

Job Summary:
webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. The AI Research Scientist will design, train, evaluate, and optimize cutting-edge machine learning models, collaborating with various teams to ensure innovations have real-world impact.
Responsibilities:
• Design, train, and optimize machine learning models including LLMs, multimodal models, transformers, and diffusion architectures
• Conduct research on model efficiency, quantization, compression, and on-device deployment
• Prototype novel model architectures, training methods, and inference strategies for distributed AI
• Develop and evaluate benchmarks, datasets, and experimental frameworks to test model performance
• Collaborate with engineering teams to integrate research findings into production systems
• Stay current on leading research in deep learning, generative AI, and distributed ML
• Analyze experimental results and communicate insights clearly to technical and non-technical stakeholders
• Document research findings, contribute to internal papers, and present technical work across the organization
• Identify emerging technologies and propose research directions aligned with webAI’s strategic priorities
Qualifications:
Required:
• 4+ years of experience (can be graduate research) in machine learning research, AI model development, or related fields
• Strong expertise in deep learning architectures including transformers, CNNs, RNNs, and diffusion models
• Hands-on experience training and fine-tuning large-scale models
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
• Experience building datasets, designing experiments, and validating ML model performance
• Deep understanding of optimization techniques including quantization, distillation, pruning, and hardware-aware training
• Strong problem-solving skills and ability to work independently on complex research tasks
• Effective communication skills for presenting research findings to diverse audiences
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
Preferred:
• Master’s or PhD in Machine Learning, Computer Science, AI, or a related field
• Experience with distributed training, edge inference, or on-device ML
• Research experience in generative AI, reinforcement learning, or multimodal learning
• Familiarity with privacy-preserving ML techniques such as federated learning
• Experience contributing to academic publications, patents, or open-source ML projects
• Comfort operating in a fast-paced, high-growth startup environment
Company:
The leader in private AI. Founded in 2020, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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