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Neural Network Engineer Jobs (NOW HIRING)

Dayhoff Labs

AI Research Engineer

Cambridge, MA · On-site

Train large models across three threads: enzyme-substrate prediction, neural network potentials ... Strong ML engineering fundamentals: architectures, training dynamics, data pipelines, and ...

New

femtoAI

Hardware Engineer

San Bruno, CA · On-site

$147K - $194K/yr

As a Hardware Engineer, you will join femtoAI's hardware team to help design and build our novel neural network accelerator. Working in a small, highly collaborative group, you will contribute ...

Apple Inc.

Video Machine Learning Engineer

San Diego, CA · On-site

$139.50 - $258.10/hr

Design and develop novel machine learning algorithms and neural network architectures for video ... Strong programming skills in Python and/or C/C++, with demonstrated ability to debug and solve ...

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How much do neural network engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for neural network engineer in the United States is $109,040.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,000.00 and $133,500.00 per year, depending on experience, location, and employer.

What does a neural network engineer do?

A Neural Network Engineer designs, develops, and optimizes machine learning models, particularly artificial neural networks, to solve complex problems. They work with deep learning frameworks like TensorFlow and PyTorch, train and fine-tune models, and optimize them for performance and efficiency. Their role often involves preprocessing data, selecting appropriate architectures, and deploying models in real-world applications such as computer vision, natural language processing, or autonomous systems.

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

To thrive as a Neural Network Engineer, you need a strong background in machine learning, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in programming languages like Python or C++. Experience with GPU computing, cloud-based machine learning platforms, and relevant certifications (e.g., TensorFlow Developer Certificate) is often valuable. Strong problem-solving skills, teamwork, and effective communication help you excel when collaborating on complex AI models and projects. These abilities are essential for designing effective neural networks, integrating them into products, and driving innovation in real-world applications.

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Neural Network Engineer jobs near you
Infographic showing various Neural Network Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, and 6% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $109,040 per year, or $52.4 per hour.

Research Engineer, Accelerated Quantum Chemistry

Dayhoff Labs

Cambridge, MA • On-site

$140 - $200/hr

Other

Posted 3 days ago

New

Job description

About us

We're reverse-engineering the origin of life — one of the great unsolved problems in science, and one we think AI finally makes tractable. We believe that understanding this transition, from geochemistry to biochemistry, will let us orchestrate molecular networks and build systems that are more capable, adaptive, efficient, and intelligent.

If we succeed, the applications are vast: from catalysis and green synthesis to ab initio synthetic biology and programmable matter. Understanding and harnessing these processes could let ten billion of us thrive on this planet — and let us dream that diverse life keeps evolving and thriving beyond it.

We're a small, diverse team of AI engineers, computational scientists, and bench scientists. We hold ourselves to the rigor of a research institute, but we ship like an engineering firm. Global team, HQs in Cambridge, MA and London, UK.

The role

You'll build simulation pipelines that fuse conventional computational chemistry with AI-accelerated models, in a setting where the simulation and the experiment are on the same clock. Build it, deploy it, watch it get tested — often in the same month.

What you'll do
  • Run QM/MD simulations combining standard packages with AI-accelerated models
  • Build reproducible pipelines and benchmarking protocols across QM, MD, and ML
  • Deploy simulation tools for internal teams; work with software and product on external deployment
  • Integrate neural network potentials into traditional QM/MD workflows with the ML team
Essential experience
  • PhD in computational chemistry, chemical physics, materials science, or related field — or a Master's with 3+ years relevant experience
  • Hands‑on experience with QM and MD packages (e.g., VASP, Gaussian, ORCA, GROMACS, LAMMPS, CP2K)
  • Track record of building computational pipelines and reproducible workflows
  • Proficiency in Python and scientific computing libraries (NumPy, SciPy, computational chemistry libraries)
  • Experience with ML frameworks (PyTorch, TensorFlow) and their integration into computational chemistry workflows
Highly preferred
  • Neural network potentials and modern AI models for molecular simulation (e.g., graph neural networks, transformer models)
  • HPC environments and workflow management systems
  • Containerization (Docker) and deployment pipelines
  • Benchmarking and statistical validation of computational methods
  • Translating computational insights into practical applications
Logistics

Compensation is highly competitive. We're also able to sponsor visas for the right candidate.

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