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Full Time Neural Networks Jobs (NOW HIRING)

Rackner

AI/ML Engineer (Active TS/SCI )

Dayton, OH · On-site +1

Dayton, OH and Remote Employment Type: Full-Time Clearance requirements: TS/SCI About the Role ... Convolutional Neural Networks (CNNs) * Recurrent Neural Networks (RNNs) * Transformer-based ...

SRP Systems Inc

Senior Data Scientist

Princeton, NJ · On-site

Princeton, NJ Full Time Job Requirements: * A minimum of three years of experience working as a ... Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc * Experienced in ...

SRP Systems Inc

Senior Data Scientist

Princeton, NJ · On-site

Princeton, NJ Full Time Job Requirements: * A minimum of three years of experience working as a ... Highly conversant with Bayesian type algorithms, KNN, Neural Networks, SVM, etc * Experienced in ...

Designworks Talent

Senior Applied Scientist

Seattle, WA · Remote

$200K - $250K/yr

Seattle, WA (On-site downtown) - Hybrid Type: Full-Time Industry: Software (AI) Specialty ... Large language models (LLMs), agentic systems, reinforcement learning, and/or graph neural networks.

Cmu

RF Cyber Lab Intern

Pittsburgh, PA

$14.50 - $19.50/hr

Artificial neural networks design and implementation * Spiking temporal neural network ... Location Pittsburgh, PA Job Function Non-CMU Students Position Type Intern (Fixed Term) Full time ...

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Full Time Neural Networks information

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$38.5K

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How much do full time neural networks jobs pay per year?

As of Jun 25, 2026, the average yearly pay for full time neural networks in the United States is $103,920.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $132,500.00 per year, depending on experience, location, and employer.

What are the typical challenges faced by professionals working full-time with neural networks, and how can they be managed?

Professionals working full-time with neural networks often encounter challenges such as handling large and complex datasets, ensuring model generalization, and optimizing computational resources. Staying updated with rapidly evolving frameworks and techniques can also be demanding. Collaborating closely with data engineers, software developers, and domain experts helps in addressing these challenges effectively and ensures the successful deployment and scalability of neural network models.

What are the key skills and qualifications needed to thrive as a Neural Networks Engineer, and why are they important?

To thrive as a Neural Networks Engineer, you need a strong background in mathematics, deep learning theory, programming (especially Python), and a relevant degree such as computer science or engineering. Proficiency with frameworks like TensorFlow or PyTorch, as well as experience with cloud platforms and version control systems, is typically expected. Analytical thinking, creativity in problem-solving, and effective communication help distinguish top performers in this field. These skills are vital for designing, implementing, and optimizing neural network models that solve complex real-world problems efficiently.

What are full-time neural network jobs?

Full-time neural network jobs are positions where professionals work primarily with artificial neural networks and deep learning models. These roles typically involve developing, training, and deploying neural network architectures for tasks such as image recognition, natural language processing, and predictive analytics. Professionals in these jobs often have backgrounds in computer science, mathematics, or engineering, and work in industries like tech, healthcare, finance, and automotive. The work is usually project-based and may require collaboration with data scientists, engineers, and product managers.

What is the difference between Full Time Neural Networks vs Data Scientist?

AspectFull Time Neural NetworksData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; knowledge of neural network frameworksDegree in Statistics, Computer Science, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness environments, analytics teams, consulting firms
Industry UsageAI development, machine learning projects, deep learning researchData analysis, predictive modeling, business insights

Full Time Neural Networks specialists focus on designing and implementing neural network models for AI applications, often within research or development teams. Data Scientists analyze data to extract insights and build predictive models, sometimes utilizing neural networks. While both roles require programming skills and a background in data or AI, their primary focus and work environments differ. Understanding these distinctions helps in choosing the right career path or job search focus.

What cities are hiring for Full Time Neural Networks jobs? Cities with the most Full Time Neural Networks job openings:
What are the most commonly searched types of Neural Networks jobs? The most popular types of Neural Networks jobs are:
What states have the most Full Time Neural Networks jobs? States with the most job openings for Full Time Neural Networks jobs include:
Full Time Neural Networks jobs near you
AI/ML Engineer (Active TS/SCI )

AI/ML Engineer (Active TS/SCI )

Rackner

Dayton, OH • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Job description

Job Title: AI/ML Engineer

Location: Dayton, OH and Remote
Employment Type: Full-Time

Clearance requirements: TS/SCI

About the Role

Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning solutions that support mission-critical systems. This role will focus on building scalable models, developing training pipelines, and collaborating with cross-functional teams to deliver impactful AI-driven solutions.

Key Responsibilities

  • Design, develop, and implement machine learning and deep learning models
  • Build and optimize model architectures including CNNs, RNNs, and transformer-based models
  • Develop and deploy Large Language Models (LLMs) and object detection systems (e.g., YOLO, Faster R-CNN)
  • Perform feature engineering and prepare high-quality datasets for training and evaluation
  • Create and maintain AI/ML training runbooks and documentation
  • Collaborate with data engineers and software teams to integrate models into production systems
  • Ensure reproducibility through data versioning and metadata standards
  • Continuously evaluate and improve model performance and scalability

Required Qualifications

  • Strong proficiency in designing and implementing model architectures, including:
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    • Transformer-based architectures
    • Large Language Models (LLMs)
    • Object Detection models (e.g., YOLO, Faster R-CNN)
  • Hands-on experience with:
    • PyTorch and/or TensorFlow
    • Hugging Face, Ollama, or similar frameworks
  • Experience with data engineering concepts, including:
    • Feature engineering and dataset preparation
    • Data versioning tools (e.g., lakeFS)
    • Metadata standards such as STAC
  • Ability to create clear and effective AI/ML training runbooks
  • Strong problem-solving skills and ability to work in a collaborative environment

Preferred Qualifications

  • Experience deploying models in cloud-native environments
  • Familiarity with DevSecOps practices
  • Experience working with large-scale or federal datasets
  • Understanding of MLOps principles and pipelines

Benefits & Perks

  • Weekly pay with full remote flexibility
  • Professional growth investment, including paid certifications and training
  • Comprehensive benefits package, including:
    • Medical, dental, and vision coverage
    • 401(k) with 100% company match up to 6%
    • Paid time off (PTO)
    • Life and disability insurance
    • Home office equipment plan
  • A supportive, inclusive team culture focused on collaboration, trust, and mission impact

About Rackner

Rackner is a cloud-native software consultancy delivering solutions for startups, enterprises, and the public sector.

We enable digital transformation through DevSecOps, AI/ML, and cloud-first innovation.

Our teams solve high-impact problems that advance federal missions and strengthen national readiness.

Join us to help shape the future of secure, scalable data systems supporting mission success.