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Remote Nvidia Machine Learning Jobs in Anna, TX (NOW HIRING)

Performacentric

Full Stack Developer

Dallas, TX · On-site +1

Remote (Preferred: Philippines, Latin America, or North America) Employment Type: Full-Time / ... Candidates with experience in machine learning, large language models (LLMs), AI agents, and ...

Humana

Lead Data Scientist

Dallas, TX · On-site +1

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

Humana

Lead Data Scientist

Dallas, TX · On-site +1

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

Humana

Lead Data Scientist

Dallas, TX · On-site +1

... Machine Learning, or a related field. Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location ...

Toyota

Data Scientist

Plano, TX · On-site +1

... and remote work on Fridays Who we're looking for: Toyota Financial Services is seeking highly ... Hands-on experience using statistical or machine learning frameworks to solve a variety of real ...

Vytwo

Senior Data Engineer - Remote

Prosper, TX · Remote

$55 - $60/hr

Experience supporting machine learning workflows or analytical data science pipelines * Knowledge of distributed computing concepts and performance tuning This is a remote position.

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Remote Nvidia Machine Learning information

See Anna, TX salary details

$23.9K

$40K

$82.6K

How much do remote nvidia machine learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote nvidia machine learning in Anna, TX is $39,957.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,500.00 and $43,200.00 per year, depending on experience, location, and employer.

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

AspectRemote Nvidia Machine LearningRemote Data Scientist
Required CredentialsDeep learning, GPU programming, Nvidia certificationsStatistics, programming, data analysis
Work EnvironmentFocus on GPU-accelerated ML models, Nvidia toolsData analysis, modeling, visualization
Industry UsageAI, autonomous vehicles, gaming, HPCBusiness analytics, research, finance

Remote Nvidia Machine Learning specialists focus on developing GPU-accelerated AI models using Nvidia technologies, often requiring specific certifications and expertise in GPU programming. In contrast, Remote Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and programming skills, Nvidia Machine Learning roles are more specialized in GPU-based AI development, whereas Data Scientists have broader data analysis responsibilities.

Remote Nvidia Machine Learning jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Mckinney, TX • Remote

Full-time

Re-posted 18 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply