Advanced AI Software Engineer

Our platform enables CNC machines to self-measure, self-correct, and continuously improve - transforming conventional machine tools into autonomous precision systems.

4MP is backed by a prestigious institutional investor and is fully funded at the Seed stage. We are moving from early software development into the design and implementation of complex AI and software systems that connect machines, sensors, geometry, physics, CNC programs, and real-world manufacturing behavior.

We are building a system where AI does not live only in software. It must reason over physical systems, 3D geometry, sensor data, machine behavior, uncertainty, and correction loops.

The Mission

We are seeking a hands-on Physical AI Principal Software Engineer to help build the intelligence layer of 4MP’s autonomous manufacturing platform.

This person will design and develop AI systems that enable machines to interpret manufacturing intent, understand deviations between nominal and measured reality, reason about physical behavior, and generate corrective actions.

This is not a research-only role, and it is not a generic AI application role.

This is not e-commerce AI, ad-tech optimization, web personalization, generic SaaS analytics, or chatbot-only AI.

This is a builder role for someone who can turn AI, software engineering, physical systems, 3D data, metrology, sensors, robotics principles, and manufacturing context into working software that performs in the real world.

What You Will Build

· AI systems that interpret manufacturing intent from CNC programs, CAM outputs, CAD geometry, sensor data, metrology data, and machine behavior

· Physical AI capabilities that connect perception, geometry, machine state, process context, uncertainty, and corrective action

· Learning and reasoning frameworks that combine AI with physics-based models, engineering constraints, real-world feedback, and validation data

· Closed-loop correction systems that improve machining outcomes through measurement, diagnosis, and adaptation

· AI methods for understanding deviations between nominal geometry, measured geometry, and actual machine behavior

· Sensor-driven intelligence systems using machine telemetry, optical sensor data, metrology data, and production context

· 3D data and geometry intelligence pipelines for point clouds, surfaces, meshes, feature extraction, registration, deviation analysis, and error mapping

· Simulation and validation environments for testing autonomous correction models before and after physical experiments

· Data pipelines and model architectures that support multi-modal manufacturing intelligence across machines, sensors, parts, materials, and production environments

· Scalable AI components that can eventually operate across different machine tools, part families, measurement strategies, and correction workflows

Role Nature: Principal-Level Physical AI Engineering

This is a principal individual contributor role with platform-level technical influence.

You will work directly with the founding team and collaborate across AI, software, robotics, metrology, machine physics, sensing, geometry, and manufacturing domains.

You will help define how AI becomes a core layer of the 4MP platform - not as a standalone model, but as an intelligence system connected to physical machines, 3D measurements, and real-world correction loops., · Design and develop AI systems for autonomous manufacturing, machine understanding, and closed-loop correction

· Build models and algorithms that interpret CNC programs, CAM logic, CAD geometry, machining context, and operator variability

· Develop methods to connect sensor data, 3D geometry, machine telemetry, metrology results, and physics-based models

· Create AI systems that identify deviations, reason about likely causes, estimate uncertainty, and support corrective actions

· Build learning loops that improve from experiments, inspection results, machine corrections, and production outcomes

· Support simulation and virtual validation environments for testing AI behavior before expensive physical experiments

· Translate complex physical behavior into robust software architectures, data models, and scalable AI systems

· Help define data requirements, validation metrics, model evaluation methods, and system-level performance expectations

· Contribute to AI architecture decisions that will shape the long-term 4MP platform

· Mentor other technical contributors and help shape the future AI team

Who You Are

You are a deeply technical AI/software engineer who is excited by systems that interact with the physical world.

You are not limited to model development in isolation. You understand that real-world AI requires sensing, uncertainty, calibration, noisy data, physical constraints, geometry, system behavior, and validation.

You are comfortable working across software and hardware boundaries. You can reason about machines, sensors, metrology, robotics, geometry, control, perception, data pipelines, and platform architecture.

You are hands-on, practical, and able to move from concept to working prototype. You are comfortable with ambiguity, but you bring technical structure and engineering discipline to complex problems.

You want to build AI that changes how physical systems perform - not AI that only ranks products, optimizes clicks, or summarizes text.

What We Require

· 8+ years of experience in AI/ML, physical AI, robotics, autonomous systems, intelligent systems, controls, perception, optimization, simulation, industrial AI, or related technical fields

· Strong hands-on software engineering experience building AI, ML, robotics, optimization, perception, control, or data-driven systems

· Experience working with real-world physical data, sensor data, machine telemetry, robotics data, metrology data, manufacturing data, or other complex multi-modal datasets

· Experience building AI systems where outputs influence real-world decisions, correction strategies, inspection decisions, control behavior, or automation workflows

· Strong programming skills in Python and experience with production-oriented AI/ML, data, simulation, optimization, or robotics software

· Strong understanding of model development, data pipelines, system architecture, validation, deployment, observability, and reliability

· Experience translating ambiguous technical problems into working models, algorithms, tools, or systems

· Ability to work closely with software, hardware, testing, and domain experts

· Strong mathematical and technical foundation in areas such as optimization, statistics, geometry, robotics, controls, simulation, uncertainty, or physics-based modeling

· Bachelor’s degree in Computer Science, Robotics, Engineering, Physics, Mathematics, or a related technical field - or equivalent practical experience

What Will Set You Apart

· Direct experience with physical AI, robotics, autonomous systems, industrial AI, or machine intelligence connected to real-world equipment

· Experience with CNC machining, CAM systems, G-code, machine tools, metrology, manufacturing data, or industrial automation

· Experience with geometry processing, 3D data, point clouds, meshes, CAD data, optical sensing, machine vision, or metrology systems

· Experience combining AI with physics-based models, digital twins, simulation, controls, sensor fusion, or engineering constraints

· Experience with model validation against experimental data, production data, metrology data, or physical test results

· Advanced degree in Computer Science, Robotics, Engineering, Physics, Mathematics, or a related field

· Startup or scale-up experience where speed, ownership, and ambiguity are part of the job

· Proven ability to turn unsolved technical problems into reliable working systems

Important Clarification

We are not looking for someone whose experience is primarily e-commerce, ad-tech, marketing optimization, web personalization, recommendation engines for consumer products, generic BI/analytics, or chatbot-only applications.

Those backgrounds can be useful only if they are combined with meaningful experience in physical systems, sensors, robotics, industrial systems, 3D data, metrology, simulation, or closed-loop real-world decision-making.

The right candidate has built AI or software systems that must survive contact with physical reality: noisy measurements, calibration problems, changing machine behavior, geometric complexity, incomplete data, and real validation requirements.