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Remote Deep Learning Jobs in Lancaster, TX (NOW HIRING)

Adidev Technologies Inc

ML/AI Engineers

Dallas, TX · Remote

Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

EnthuZiastic

Growth Hacker - Remote

Dallas, TX · Remote

Proven experience in digital marketing, with a deep understanding of various marketing channels and ... Continuous Learning: * A commitment to ongoing learning and professional development in growth ...

EnthuZiastic

Growth Hacker - Remote

Arlington, TX · Remote

Proven experience in digital marketing, with a deep understanding of various marketing channels and ... Continuous Learning: * A commitment to ongoing learning and professional development in growth ...

Directive

B2B Marketing Manager(Remote US)

Dallas, TX · Remote

$80K - $85K/yr

Deep technical knowledge of Strategy, Paid Media, SEO, and CRO for tech companies * Strong SaaS ... Driven to stay ahead of industry trends, including actively learning how AI and automation can ...

SysMind Tech

Remote | SAP ME & MII Consultant

Richardson, TX · On-site +1

$60.25 - $82.25/hr

Tperson ideal candidate will have a deep understanding of SAP Manufacturing solutions, include SAP ... You will be part of a learning culture, where teamwork and collaboration are encouraged, excellence ...

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All JobsDeep Learning JobsRemote Deep Learning JobsRemote Deep Learning Jobs in Lancaster, TX

Remote Deep Learning information

See Lancaster, TX salary details

$10.4K

$79.5K

$132.7K

How much do remote deep learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for remote deep learning in Lancaster, TX is $79,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,300.00 and $131,800.00 per year, depending on experience, location, and employer.

What is a remote deep learning engineer?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What are common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

What is the difference between Remote Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

What skills and qualifications are needed to thrive as a remote deep learning engineer?

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.
What job categories do people searching Remote Deep Learning jobs in Lancaster, TX look for? The top searched job categories for Remote Deep Learning jobs in Lancaster, TX are:
What cities near Lancaster, TX are hiring for Remote Deep Learning jobs? Cities near Lancaster, TX with the most Remote Deep Learning job openings:
Remote Deep Learning jobs near you

Software Engineer - AI Specialist | Remote

GigWorld Talent Solutions

Dallas, TX • On-site, Remote

Other

Re-posted 25 days ago

Job description

Job Description Software Engineer - AI Specialist | Remote Permanent, Full-Time We are supporting an innovative technology firm dedicated to building AI-driven solutions that drive efficiency and transformation across industries. We are seeking a highly skilled Software Engineer specializing in Artificial Intelligence to develop, optimize, and deploy AI-powered applications. Responsibilities: Design, develop, and implement AI models and machine learning algorithms.

Collaborate with cross-functional teams to integrate AI solutions into existing platforms. Optimize AI models for performance, scalability, and efficiency. Research and apply the latest advancements in AI and deep learning.

Develop and maintain data pipelines and AI-driven analytics systems. Ensure AI models are robust, ethical, and aligned with best practices. Troubleshoot and improve AI-based applications as needed.

Stay updated on emerging AI trends and technologies. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience in AI and machine learning development.

Proficiency in programming languages such as Python, Java, or C++. Strong understanding of AI frameworks and libraries (TensorFlow, PyTorch, Scikit-learn, etc.). Experience with natural language processing (NLP), computer vision, or predictive analytics

Knowledge of data science methodologies and model evaluation techniques. Experience with cloud platforms and AI services (AWS, Azure, GCP). Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications: Experience with reinforcement learning and generative AI models. Familiarity with AI ethics, bias mitigation, and explainability techniques. Contribution to open-source AI projects.

Understanding of big data technologies and distributed computing. Benefits: Competitive salary and performance-based incentives. Flexible work schedule and remote work opportunities.

Professional development and continuous learning resources. Opportunity to work with a passionate and innovative team in a fast-growing industry.

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