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Remote Deep Learning Jobs in North Carolina (NOW HIRING)

Labcorp

Senior Cytogenetic Technologist - US Remote

Concord, NC · Remote

$33 - $38/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

With our global scale and deep expertise, you'll have the opportunity to do meaningful work, grow ... Join us and discover a path filled with opportunities for growth, continuous learning, professional ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Machine Learning and AI Solutions : Lead the development and implementation of machine learning ... Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation ...

EnrollHere

Senior Software Engineer - Call Routing Product

Raleigh, NC · On-site +1

$119K - $157K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate will have deep expertise in VoIP/CCaaS technologies, distributed systems, and ... PTO & Flexibility: Generous PTO and remote work support * Growth: Learning stipends and ...

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All JobsDeep Learning JobsRemote Deep Learning JobsRemote Deep Learning Jobs in North Carolina

Remote Deep Learning information

See North Carolina salary details

$21

$49

$75

How much do remote deep learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for remote deep learning in North Carolina is $49.54, according to ZipRecruiter salary data. Most workers in this role earn between $40.10 and $61.30 per hour, 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 are the most commonly searched types of Deep Learning jobs in North Carolina? The most popular types of Deep Learning jobs in North Carolina are:
What are popular job titles related to Remote Deep Learning jobs in North Carolina? For Remote Deep Learning jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning jobs in North Carolina look for? The top searched job categories for Remote Deep Learning jobs in North Carolina are:
What cities in North Carolina are hiring for Remote Deep Learning jobs? Cities in North Carolina with the most Remote Deep Learning job openings:
Remote Deep Learning jobs near you
Infographic showing various Remote Deep Learning job openings in North Carolina as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $103,036 per year, or $49.5 per hour.

AVP, AI (Data Science/Engineer) Remote - EST

Archgroup

Raleigh, NC • Remote

$185K - $235K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 days ago

Job description

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility.

Strategic Analytics is a dynamic and growing team at Arch that drives innovation and transforms how the business operates. We build AI-first, agent-driven products that change how Arch underwrites, services, and learns from its book, combining frontier LLMs, multi-agent systems, retrieval-augmented generation (RAG), evaluation frameworks, and traditional machine learning.Our mission spans agentic automation, decision intelligence, AI-driven insights, and the responsible deployment of AI at scale. With a proven track record of productionizing dozens of high-quality GenAI products over the past three years, we are continuing to scale our impact and are seeking an AVP, AI Engineering to lead the design and application of advanced AI systems within Strategic Analytics.

Reporting to the SVP of AI & Automation, you will lead the development of multi-agent AI solutions that automate complex business decisions across underwriting and claims. This role is focused on applying AI, machine learning, and data science to solve high-value business problems, establish decision frameworks, and ensure AI systems deliver measurable outcomes with high levels of accuracy and trustworthiness.

Key Responsibilities

Lead the design of multi-agent AI systems that coordinate specialized models and agents to solve complex business problems.

Drive the end-to-end delivery of AI-powered underwriting and claims solutions from experimentation through production deployment.

Develop and evaluate decision frameworks that combine LLMs, retrieval systems, machine learning models, business rules, and human review.

Establish methodologies for measuring model performance, calibration, confidence, accuracy, and business impact to determine when automation is appropriate.

Define the conditions under which AI-driven decisions should be trusted, reviewed, or escalated.

Partner with cross-functional teams to integrate AI capabilities into business workflows and operational processes.

Mentor data scientists, AI engineers, and analysts on agentic AI, model evaluation, prompt engineering, and responsible AI practices.

Establish standards for AI evaluation, monitoring, governance, and continuous improvement within the AI & Automation Center of Excellence.

Translate business opportunities into scalable AI solutions that deliver measurable business value.

Required Skills and Experience

7+ years of experience in AI, machine learning, data science, analytics, or related disciplines.

3+ years of people leadership experience.

Demonstrated experience building and deploying production-grade AI, machine learning, or agentic systems beyond proof-of-concept work.

Strong track record of developing supervised learning models (ML and/or GLMs) that have delivered measurable financial impact.

Deep understanding of model evaluation, experimentation, statistical analysis, and decision science.

Strong experience evaluating AI technologies, platforms, and vendors.

Strong Python experience for data science, machine learning, and AI development.

Exceptional problem-solving skills with the ability to frame ambiguous business challenges as analytical and AI opportunities.

Strong communication skills with the ability to influence technical and non-technical stakeholders.

Hands-on experience with modern AI technologies, including LLMs, RAG, agentic systems, evaluation frameworks, and emerging AI tooling.

Desired Skills and Experience

Familiarity with P&C insurance, including underwriting, claims, or the submission lifecycle.

Experience with retrieval-augmented generation (RAG), evaluation frameworks, and structured-output techniques.

Experience applying AI and machine learning within enterprise environments.

Experience leading multidisciplinary teams across data science, AI, analytics, and technology functions.

Demonstrated commitment to staying current with advancements in AI through research, experimentation, publications, conference participation, or contributions to the AI community.

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Analytics, or equivalent practical experience.

#LI-LH1

#LI-REMOTE

For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible.

$185,000 - $235,000/year

  • Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.

  • Arch is committed to helping employees succeed through our comprehensive benefits package that includes multiple medical plans plus dental, vision and prescription drug coverage; a competitive 401k with generous matching; PTO beginning at 20 days per year; up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer; basic Life and AD&D Insurance as well as Short and Long-Term Disability; Paid Parental Leave of up to 10 weeks; Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care; and more. Click here to learn more on available benefits.

Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you.If this job isn't the right fit but you're interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch's Talent Acquisition team.

10200 Arch Capital Services LLC

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