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Freelance Nvidia Machine Learning Jobs in Alabama

Data Engineer

Redstone Arsenal, AL

$116K - $140K/yr

... Kubeflow, Nvidia Triton, PyTorch, TensorFlow, Weaviate, Neo4j, Grafana, etc. * Cloud native ... Develop services and extend infrastructure to enable machine learning workflows * Integrate ...

Data Engineer

Redstone Arsenal, AL · On-site

$116K - $140K/yr

... Kubeflow, Nvidia Triton, PyTorch, TensorFlow, Weaviate, Neo4j, Grafana, etc. * Cloud native ... Develop services and extend infrastructure to enable machine learning workflows * Integrate ...

Computer Vision AI/ML Engineer

Huntsville, AL · On-site

$87.10 - $157.45/hr

... and machine learning. Typical customers include Defense Advanced Research Projects Agency (DARPA ... Experience deploying to various edge processing devices including the NVIDIA Jetson family and ...

New

Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ... Edge & Deployment: ONNX/TensorRT, quantization/compression, ARM/NVIDIA Jetson/DSP targets ...

Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ... Edge & Deployment: ONNX/TensorRT, quantization/compression, ARM/NVIDIA Jetson/DSP targets ...

... and machine learning. Typical customers include Defense Advanced Research Projects Agency (DARPA ... Experience deploying to various edge processing devices including the NVIDIA Jetson family and ...

Freelance Nvidia Machine Learning information

What are the key skills and qualifications needed to thrive as a freelance Nvidia machine learning specialist?

To thrive as a Freelance Nvidia Machine Learning Engineer, you need a strong background in machine learning principles, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in Python programming, often supported by a relevant degree or certifications. Familiarity with Nvidia hardware (GPUs), CUDA programming, and tools like Nvidia Deep Learning SDKs is essential for optimizing and deploying models efficiently. Exceptional problem-solving, self-management, and client communication skills help you deliver effective solutions and maintain successful freelance relationships. Mastery of these skills ensures you can build high-performance models, meet client expectations, and stay competitive in the rapidly evolving ML landscape.

What is the difference between Freelance Nvidia Machine Learning vs Freelance Data Scientist?

AspectFreelance Nvidia Machine LearningFreelance Data Scientist
Required CredentialsKnowledge of Nvidia GPU architectures, CUDA programming, machine learning frameworksStatistics, programming, data analysis skills, often with similar certifications
Work EnvironmentProject-based, remote, often with tech companies or startupsProject-based or consulting, remote or on-site, across various industries
Industry UsageAI, deep learning, GPU-accelerated applicationsData analysis, predictive modeling, business insights

Freelance Nvidia Machine Learning specialists focus on GPU-accelerated AI projects using Nvidia technologies, while Freelance Data Scientists handle broader data analysis and modeling tasks. Both roles are in high demand for tech-driven projects but differ in technical focus and tools used.

What are some common challenges freelance Nvidia machine learning specialists face when working with clients remotely?

Freelance Nvidia Machine Learning specialists often encounter challenges such as ensuring compatibility between client hardware and Nvidia GPU requirements, effectively communicating technical needs and project progress to non-expert clients, and managing project timelines without in-person oversight. Additionally, freelancers may need to set up secure access to client data or cloud environments, which can require extra coordination. Proactively clarifying expectations, maintaining clear documentation, and staying current with Nvidia's latest tools (like CUDA, cuDNN, or TensorRT) are essential strategies for overcoming these challenges.

What does a freelance Nvidia machine learning specialist do?

A Freelance Nvidia Machine Learning specialist is an independent contractor who uses Nvidia hardware and software platforms, such as CUDA and TensorRT, to develop, optimize, and deploy machine learning models. These professionals often work with clients to accelerate AI workloads, implement deep learning solutions, and leverage GPU computing for data processing tasks. Their projects may include computer vision, natural language processing, or other AI applications that benefit from Nvidia’s technology stack. Freelancers in this field need strong programming skills, familiarity with Nvidia SDKs, and experience optimizing models for high-performance computing environments.

What cities in Alabama are hiring for Freelance Nvidia Machine Learning jobs?

Cities in Alabama with the most Freelance Nvidia Machine Learning job openings:

Artificial Intelligence / Machine Learning Engineer

DESE Research, Inc.

Huntsville, AL • On-site

$115K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Job description

DESE's Cyber Works and Digital Engineering teams design, build, and integrate emerging AI/ML technologies to harden and secure the systems that defend the nation, across ground, missile defense, space, and installation infrastructure S&T programs. We're expanding our Secure AI practice to build and assure trusted, robust AI/ML solutions that interpret complex datasets, predict outcomes, and automate decision-making in support of critical military platforms.This is a consolidated announcement covering multiple tracks; your assignment may emphasize one or a blend of: Classic ML & Predictive Modeling, LLM/GenAI Applications, AI Assurance & Responsible AI, Edge AI/ML Deployment, and hardening AI/ML systems against adversarial threats. All tracks require independent research, cross-functional collaboration, and the ability to clearly communicate complex technical work to stakeholders.Core Responsibilities:Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ensembles, clustering) to modern deep learning architectures.Build LLM-enabled applications and retrieval-augmented generation (RAG) pipelines, including vector embedding generation, vector database integration, and prompt/context engineering.Develop AI assurance and evaluation tooling: robustness testing, bias/fairness analysis, model traceability, red-team/adversarial testing, and audit artifact generation.Optimize and deploy models for production and edge environments (quantization, compression, containerized inference, ONNX/TensorRT).Implement secure model and data pipelines, defend against adversarial ML threats, and ensure supply-chain integrity (SBOM) for AI components.Conduct data processing/analysis to improve model accuracy; document and present development processes and assurance evidence to stakeholders.Contribute to Agile, team-based planning and estimating in a fast-paced, collaborative environment.Minimum Requirements: Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field).Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions.Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Proficiency in Python and at least one additional language (Java, C++).Strong understanding of data structures, data modeling, and software architecture.Highlighted Skills & Experience: Modern AI: LLM frameworks and application development; vector embeddings and vector databases; RAG architectures; prompt/context engineering; LLM fine-tuning; model evaluation and benchmarking.Classic ML: Feature engineering, model selection/tuning, statistical analysis, and predictive modeling across structured and unstructured data.AI Assurance: Responsible AI practices (robustness, bias/fairness, traceability); adversarial ML defenses; red-team testing; auditability and compliance documentation.Edge & Deployment: ONNX/TensorRT, quantization/compression, ARM/NVIDIA Jetson/DSP targets, containerized inference, MLOps in controlled/classified environments.Platform & DevSecOps: REST APIs, CI/CD for software and ML systems, SAST/DAST, Infrastructure-as-Code, cloud platforms (AWS, Azure, GCP).Domain: Familiarity with computer networking, secure system integration for mission platforms, and test/V&V support (Python/MATLAB analysis).Contributions to open-source AI/ML projects; experience deploying AI models in production, classified, or embedded environments.Understanding of computer security principles and secure software development lifecycle (SSDLC) practices.Why This Role Matters:You'll join a high-impact team solving some of the DoD's hardest problems in AI-enabled system security, building the next generation of trusted, auditable, and mission-ready AI for national defense.About DESEFor the past 43 years, DESE has provided industry-leading technical and engineering solutions in the fields of Defense, Energy, Space, and Environment. As a small, family-oriented business, DESE provides a compelling benefits package including a generous profit-sharing plan, competitive salaries, and perhaps most importantly, the opportunity to work alongside talented professionals leveraging cutting-edge technologies to solve complex and engaging problems.Why employees love working for DESE:At DESE, we are committed to creating a company that is known for its respect and care for employees. We understand that happy employees are what keeps our business going and we strive to provide the best opportunities for each individual working on our team! Here are a few reasons you will love working here:Competitive health, dental and vision insurance with affordable premiumsFlexible work schedulesTwo different flexible spending account optionsCompany paid life insurance with options for employee paid additionalPerformance bonus programEducation reimbursement programCompany paid personal leave for approved philanthropic activitiesVacation, Sick & Holiday leaveRobust 401k profit sharing planOpportunities for internal promotionsEmployee referral incentive programRewards and gifts for service anniversariesDisability Accommodation for Applicants - DESE Research, Inc. is an Equal Employment Opportunity employer and provides reasonable accommodation for qualified individuals with disabilities and disabled veterans in its job application procedures. If you have any difficulty using our online system and you need an accommodation due to a disability, you may use the following alternative email address or phone number to contact us about your interest in employment with us: hrandsecurity@dese.com or 256-837-8004x123.
Job Posted by ApplicantPro