ZipRecruiter

Log In

1

Scientific Machine Learning Jobs in Texas (NOW HIRING)

Cotality

Senior Machine Learning Scientist

Dallas, TX · On-site

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with ...

Cotality

Senior Machine Learning Scientist

Dallas, TX · Hybrid

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with ...

Cotality

Senior Machine Learning Scientist

Austin, TX · Hybrid

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to identify opportunities for leveraging machine learning techniques to drive business ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

Utilize your fundamental understanding of neural networks and data science to develop models that serve as the foundation for machine learning applications for BCI. * Lead the team by performing at a ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

previous pagenext page

Showing results 21-40

All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Texas

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Texas? For Scientific Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Texas look for? The top searched job categories for Scientific Machine Learning jobs in Texas are:
What cities in Texas are hiring for Scientific Machine Learning jobs? Cities in Texas with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Adidev Technologies Inc

Austin, TX • On-site

Full-time

Re-posted just now

Job description

Role: Jr-Mid Machine Learning Engineer
(This role is open to US Citizens, Green Card holders, GC-EAD only. We do not sponsor visas.)
Summary:
Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced machine learning models, with a special emphasis on Generative AI. In this role, you will craft and refine AI-driven solutions, turning innovative ideas into value-adding features and services, thereby solidifying our market leadership and technological forefront for our clients.
About Adidev Technologies Inc.
Adidev Technologies,(www.adidevtechnologies.com) is a premier IT consulting firm delivering top-notch, Machine Learning Engineer, iOS and Android, data scientist, Developer solutions to industry giants including Delta, Google, Apple, Spotify, US Bank, FedEx, and more. We're not just a software consulting company - we're a dynamic force shaping the future of technology. Partnering with industry giants, we consistently deliver groundbreaking solutions that redefine the digital landscape. As we continue to expand our footprint, we're on the hunt for exceptional individuals who can bring their technical prowess to our team and elevate our projects to new levels of innovation.
Expertise: We excel in IT consultative services and quality engineer development, with Good years of experience.
Global Presence: Our diverse employee workforce spans four continents.
Proven Track Record: Hundreds of Fortune 1000 and innovative startup clients with thousands of successful projects across the USA.
How We'll Guide You
Teaching and Development: We are dedicated to nurturing your growth and development, shaping you into an exceptional consultant capable of delivering top-tier solutions to our end clients.
Custom Support: An array of teams, from Development Managers to Tech Subject Matter Experts, are dedicated to your success.
Project Placement: A market-expertise team ensures you secure and thrive in projects with our esteemed clients.
Career Growth: We facilitate industry experience to propel your technical journey forward.
Key Responsibilities:
• Architect and refine sophisticated ML models and algorithms, translating complex datasets into actionable solutions.
• Engage in the full lifecycle of data modeling projects, from understanding business requirements to deployment and monitoring.
• Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.
• Lead cross-functional collaborations to integrate Generative AI models into our offerings, enhancing product capabilities and user experiences.
• Apply advanced analytical techniques to analyze vast datasets, identifying trends, anomalies, and opportunities for improvement.
• Execute data preprocessing, feature engineering, and algorithm optimization to enhance model accuracy and efficiency.
• Conduct exploratory data analysis to extract valuable insights and influence strategic decisions.
• Keep abreast of and implement the latest ML trends, tools, and best practices, including AutoML, MLOps, and interpretability frameworks.
• Promote compliance with industry standards and regulatory requirements, emphasizing ethical AI practices.
Requirements:
• Degree in Computer Science, Engineering, Statistics, or a related technical field.
• Demonstrable experience in machine learning, deep learning, NLP, computer vision, reinforcement learning, and/or other AI domains.
• Demonstrable experience with Generative AI models and frameworks, such as GANs or Transformers, applied in industry settings.
• Practical experience with SQL/NoSQL databases, data visualization tools, and version control systems.
• Strong foundational understanding of algorithmic complexity and data structure optimization.
• Excellent problem-solving, collaboration, and communication abilities.
• Develop and implement cutting-edge machine learning models, with a particular focus on Generative AI applications such as text generation, image synthesis, and creative AI.
• Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.
• Stay ahead of AI research, especially in Generative AI, applying the latest findings and techniques to drive innovation within our projects.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Strong background in cloud computing and big data platforms (AWS, Azure, GCP), with hands-on experience in cloud-based ML services and serverless architectures.
• Familiarity with DevOps for AI, including containerization (Docker, Kubernetes), CI/CD pipelines, and MLOps practices.
• Facilitate knowledge sharing and best practices in AI/ML, particularly focusing on Generative AI, within the team.
• Ensure all AI implementations are compliant with ethical guidelines and data privacy standards.
How to Apply:
Interested candidates are invited to submit a comprehensive application, including a latest updated resume and a detailed cover letter, showcasing your expertise.
Perks and Beyond!
Competitive salary range: Based on experience and market value
Pack your bags! Paid relocation is on us.
Support, even from afar, with our remote assistance.
Regular salary reviews? You betcha!
Ready to Embark?
we invite you to take this extraordinary step with us. Showcase your journey in pushing the limits of mobile engineering by submitting your resume and a curated selection of your most influential projects. At Adidev Technologies, we're dedicated to shaping your success. Join us to craft a future powered by innovation and growth.
Note: Adidev Technologies Inc. is a staunch advocate of diversity and equal opportunity. We warmly welcome applications from candidates of all backgrounds, experiences, and walks of life. Your unique perspective could be the catalyst for our next revolutionary breakthrough

Apply