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Physics Informed Machine Learning Jobs in Tennessee

Drives the conception, prototyping, and deployment of machine learning models-particularly in ... Bachelor's degree in Computer Science, Math, Physics, Engineering, or related quantitative field ...

Apply statistical methods, machine learning, and AI techniques to develop production-ready ... Enable leadership to make informed, data-driven decisions Our Benefits Include: * Medical, Dental ...

Apply statistical methods, machine learning, and AI techniques to develop production-ready ... Enable leadership to make informed, data-driven decisions Our Benefits Include: * Medical, Dental ...

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

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Physics Informed Machine Learning information

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.
What job categories do people searching Physics Informed Machine Learning jobs in Tennessee look for? The top searched job categories for Physics Informed Machine Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Physics Informed Machine Learning jobs? Cities in Tennessee with the most Physics Informed Machine Learning job openings:
AI Engineering Manager - SFL Scientific

AI Engineering Manager - SFL Scientific

Deloitte

Nashville, TN • On-site

Full-time

Posted 6 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

60th of 138 rated financial services


Job description

Job Summary:
Deloitte's Strategy & Transactions team is seeking an AI Engineering Manager to lead the design, development, and deployment of innovative AI applications across various sectors. This role involves collaborating with clients to create robust AI platforms and cloud solutions, while mentoring junior team members and ensuring the successful implementation of AI strategies.
Responsibilities:
• Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
• Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
• Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
• Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
• Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
• Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
• Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
• Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
• Mentor, motivate, and coach junior members on technical best practices and inspire professional development
Qualifications:
Required:
• Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.)
• 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
• 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
• 6+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
• 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
• 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
• 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
• 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
• Live within commuting distance to one of Deloitte's consulting offices
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
• Limited immigration sponsorship may be available
Preferred:
• Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
• AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
• 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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