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Neural Network Jobs (NOW HIRING)

Train large models across three threads: enzyme-substrate prediction, neural network potentials, and inverse design of reaction networks * Own models end to end - architecture, data pipelines ...

Train large models across three threads: enzyme-substrate prediction, neural network potentials, and inverse design of reaction networks * Own models end to end - architecture, data pipelines ...

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Neural Network information

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$22K

$106.6K

$162.5K

How much do neural network jobs pay per year?

As of Sep 9, 2026, the average yearly pay for neural network in the United States is $106,570.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $128,000.00 per year, depending on experience, location, and employer.

What are neural networks?

Neural networks are a type of machine learning model inspired by the structure and function of the human brain. They consist of interconnected layers of nodes, or 'neurons,' that process data and learn to make predictions or decisions based on input data. Neural networks are widely used in applications such as image recognition, natural language processing, and autonomous systems. Their ability to learn complex patterns makes them powerful tools for solving problems that are difficult to program explicitly.

What are the key skills and qualifications needed to thrive as a neural network engineer, and why are they important?

To thrive as a Neural Network Engineer, you need a solid background in mathematics, machine learning theory, and programming, often backed by a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience in data preprocessing, and knowledge of cloud computing platforms are typically required. Strong problem-solving abilities, collaboration, and effective communication skills distinguish top professionals in this role. These competencies are vital for developing, optimizing, and deploying neural network models that drive innovation in AI-powered solutions.

What are some common challenges neural network engineers face when deploying models to production environments?

Neural network engineers often encounter challenges such as model optimization for efficient inference, managing hardware constraints, and ensuring scalability during deployment. Addressing issues like latency, memory usage, and compatibility with production infrastructure is crucial, especially when models are resource-intensive. Collaborating closely with DevOps and software engineering teams is common to streamline deployment pipelines, monitor model performance, and quickly resolve issues that arise post-launch.

What is the difference between Neural Network vs Data Scientist?

AspectNeural NetworkData Scientist
Required CredentialsKnowledge of machine learning, programming skills, often a degree in computer science or related fieldsDegree in statistics, computer science, or related fields; strong analytical skills
Work EnvironmentResearch labs, tech companies, AI development teamsBusiness environments, consulting firms, research institutions
Industry UsageDeveloping AI models, deep learning applicationsData analysis, predictive modeling, business insights

Neural networks focus on building and training AI models using complex algorithms, while data scientists analyze data to extract insights and inform decisions. Both roles often collaborate but serve different functions within the AI and data analysis ecosystem.

What is the main job of a neural network?

A neural network job involves designing, training, and optimizing artificial models that mimic the human brain's neural connections to recognize patterns, make predictions, or classify data. This role requires knowledge of machine learning, programming skills, and experience with tools like TensorFlow or PyTorch.
More about Neural Network jobs

What states have the most Neural Network jobs?

States with the most job openings for Neural Network jobs include:

Infographic showing various Neural Network job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 11% Part Time, and 6% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $106,570 per year, or $51.2 per hour.

Software Engineer I, Perception (New Grad)

Laguna Beach, CA • On-site

Menlo Ventures
Investment Clubs and Venture Capital Companies • 11 - 50 employees

Other

Posted 5 days ago


Job description

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.

OUR MISSION

True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors — enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.

OUR VALUES
  • Be the offset.We create asymmetric advantages with creativity and ingenuity.
  • What would it take? We challenge assumptions to deliver ambitious results.
  • Its the people. Our team is our competitive advantage and we are better together.
YOUR MISSION

You'll work on hybrid perception systems combining classical computer vision with modern deep learning for autonomous spacecraft: building multi-object tracking pipelines that fuse neural network detections with Kalman filtering, developing coordinate transformation chains from pixels to orbital frames, training models on synthetic space imagery, and deploying algorithms onboard under strict compute/power constraints.
Your work enables spacecraft to detect objects against star fields, track multiple targets through occlusions, discriminate threats from decoys, and generate angle measurements for navigation — using both classical geometric methods and learned representations where each approach excels. This is entry-level work blending traditional robotics perception with modern ML. You'll implement Extended Kalman Filters, train neural networks in PyTorch, write C++ flight code, and see your algorithms operate in orbit.

This is a 3 month temporary employment engagement. There is potential to convert to regular employment based on performance and business need.

RESPONSIBILITIES
  • Implement classical tracking algorithms: Extended Kalman Filters for state estimation, Hungarian algorithm for data association, track management logic (tentative/confirmed/coasted tracks)
  • Train neural networks for detection and classification: YOLO for object detection, ResNet-based classifiers for threat discrimination, learned appearance features for re-identification
  • Build hybrid perception pipelines: neural network detections -> classical tracking -> coordinate transformations -> angle-only measurements for navigation
  • Develop image processing chains: hot pixel filtering, adaptive thresholding, centroiding, connected component analysis, star catalog matching
  • Deploy models to edge hardware: quantize neural networks (INT8), integrate with C++ inference engines (ONNX Runtime, TensorRT), optimize for space-qualified processors
  • Implement coordinate transformations: pixel -> camera frame -> body frame -> Earth-Centered Inertial (ECI), accounting for lens distortion and attitude uncertainty
  • Generate synthetic training data: render spacecraft in Blender with domain randomization (lighting, attitudes, backgrounds), create labeled datasets for rare scenarios
  • Validate end-to-end performance: software-in-the-loop simulation, processor-in-the-loop testing, hardware-in-the-loop with real camera feeds
QUALIFICATIONS
  • Currently pursuing or recently completed Bachelor's or Master's degree in computer science, electrical engineering, robotics, aerospace engineering, or related technical field
  • Coursework in both computer vision and estimation theory (or willingness to learn both)
  • Proficiency in Python; some exposure to C++ (we'll teach you more)
  • Familiarity with either classical tracking (Kalman filters, data association) OR deep learning (PyTorch, training neural networks)
  • Understanding of linear algebra, probability, and coordinate transformations
  • Ability to read research papers from both robotics (ICRA, IROS) and ML venues (CVPR, NeurIPS) and implement algorithms
  • Strong debugging skills: tracking down lost tracks, numerical instability, and model failure modes
  • Eagerness to learn the intersection of classical perception and modern ML
  • U.S. Citizen (required for facility access and government contracts)
PREFERRED SKILLS AND EXPERIENCE
  • Experience with Extended Kalman Filters, multi-object tracking, or state estimation
  • Familiarity with neural network training in PyTorch or TensorFlow: object detection (YOLO, Faster R-CNN), classification, or segmentation
  • Understanding of coordinate frames: camera intrinsics/extrinsics, quaternions, rotation matrices, ECI/LVLH/RIC frames
  • Exposure to model optimization for edge deployment: quantization (INT8, FP16), ONNX, TensorRT
  • Experience with OpenCV, image processing pipelines, or classical feature extraction
  • Coursework in optimal estimation, sensor fusion, or probabilistic robotics (Kalman/particle filters)
  • Prior work with synthetic data generation, Blender/Unreal for rendering, or domain randomization
  • Understanding of data association algorithms: Hungarian algorithm, auction algorithm, JPDA
  • Familiarity with tracking-by-detection pipelines: detection -> association -> update -> track management
  • Experience debugging visual systems: false positives, missed detections, track ID switches, covariance tuning
  • Prior internship or project deploying algorithms to embedded systems (Jetson, mobile, ROS)
  • Exposure to multi-modal perception: fusing camera + IMU, camera + lidar, or learned sensor fusion
COMPENSATION
  • Base Salary:
    • Denver: $75,000
    • Long Beach: $80,000

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience.

ADDITIONAL REQUIREMENTS
  • Work Location—Successful candidates will be located near Centennial, CO or Long Beach, CA.
  • Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
  • Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.

True Anomaly is committed to equal employment opportunity on any basis protected by applicable state and federal laws. If you have a disability or additional need that requires accommodation, please do not hesitate to let us.

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