AI / ML Engineer

Neuron Factory Inc.; Redwood City (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Neuron Factory Inc. is seeking an AI/ML Engineer to lead the design, prototyping, and deployment of core machine learning systems for the AI Co-Worker platform.

You’ll own the lifecycle from data pipelines to production deployment, partnering with the founding team on architecture and product direction. You will advance state-of-the-art ML techniques, scale pipelines, and mentor future ML/AI hires in a fast-paced startup setting.

Qualifications

• 8+ years of experience in Artificial Intelligence, Machine Learning and Software Engineering.
• Strong foundation in ML/DL algorithms, statistical modeling, and data processing.
• Deep experience with modern ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
• Hands-on experience with LLMs, transformers, or other foundation models.
• Proven experience building and deploying production-grade ML systems.
• Strong software engineering skills (Python, APIs, cloud infra, containerization).
• Familiarity with ML pipelines and platforms (e.g., Airflow, MLflow, SageMaker, Vertex AI).
• Startup mindset: ownership, bias for action, comfort with ambiguity, and a builder mentality.

Responsibilities

• Design, build, and deploy scalable ML systems that power our core product.
• Own end-to-end development: problem formulation, data pipelines, model training, evaluation, and production deployment.
• Collaborate with product and engineering to translate business goals into ML solutions.
• Evaluate and apply state-of-the-art techniques in LLMs, deep learning, classical ML, and generative AI.
• Establish best practices for model reproducibility, monitoring, and performance tracking.
• Build and scale our MLOps infrastructure (training pipelines, experiment tracking, deployment tooling).
• Recruit and mentor future ML/AI hires and help grow the team and culture.

Skills

Python

APIs

Cloud infrastructure

Containerization

PyTorch

TensorFlow

JAX

LLMs / Transformers

MLOps pipelines

Team leadership

Education

CS/ML/Math degree

Tools

Airflow

MLflow

SageMaker

Vertex AI

Docker

Job description

As anAI/ML Engineer, you’ll lead the creation of cutting-edge machine learning systems, transforming complex data into powerful, scalable AI solutions that drive our AI Co-Worker platform’s impact across industries.

We’re a software company on a mission to build the AI Co-Worker, a powerful platform designed to learn complex jobs and deploy intelligent agents to solve them at Scale.
Our technology sits at the intersection of AI and human productivity, enabling businesses to automate sophisticated workflows like never before.

About the Role

As anAI/ML Engineer, you’ll play a key role in building our core machine learning systems from the ground up. You’ll own the entire lifecycle; from prototyping models to deploying production-grade systems while working closely with the founding team to influence product direction and technical architecture.

Requirements

• Design, build, and deploy scalable ML systems that power our core product.
• Own end-to-end development: problem formulation, data pipelines, model training, evaluation, and production deployment.
• Collaborate with product and engineering to translate business goals into ML solutions.
• Evaluate and apply state-of-the-art techniques in LLMs, deep learning, classical ML, and generative AI.
• Establish best practices for model reproducibility, monitoring, and performance tracking.
• Build and scale our MLOps infrastructure (training pipelines, experiment tracking, deployment tooling).
• Recruit and mentor future ML/AI hires and help grow the team and culture.

Qualifications

• 8+ years of experience in Artificial Intelligence, Machine Learning and Software Engineering.
• Strong foundation in ML/DL algorithms, statistical modeling, and data processing.
• Deep experience with modern ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
• Hands-on experience with LLMs, transformers, or other foundation models.
• Proven experience building and deploying production-grade ML systems.
• Strong software engineering skills (Python, APIs, cloud infra, containerization).
• Familiarity with ML pipelines and platforms (e.g., Airflow, MLflow, SageMaker, Vertex AI).
• Startup mindset: ownership, bias for action, comfort with ambiguity, and a builder mentality.
• Degree in Computer Science, Machine Learning, Mathematics, or related field.

Desired Skills

Nice to Have: Computer Science PhD or MS preferred (but not required with equivalent experience).

Preconstruction that reasons, not just retrieves.