Applied AI Engineer

Fundamental

Job Overview

Location

Europe

Job Type

Full-time

Full Job Description

📋 Description

• Develop and optimize a large neural network-based tabular model implemented in Python, focused on structured enterprise data that drives business decision-making
• Profile and analyze training and inference pipelines to identify and resolve performance bottlenecks in latency, memory usage, and throughput
• Rewrite performance-critical components of the model pipeline from Python into Rust using PyO3 or custom extensions, with C++ via PyBind11 or similar tools as a secondary option when necessary
• Enhance memory efficiency and computational throughput across the entire ML system while maintaining numerical stability and reproducibility as the model evolves
• Collaborate directly with ML researchers to productionize novel capabilities, translating research prototypes into scalable, reliable systems
• Design and maintain clean software abstractions, comprehensive test suites, and clear technical documentation for ML infrastructure components
• Shape architectural decisions for ML systems handling tabular data at scale, ensuring systems are robust, maintainable, and aligned with enterprise-grade requirements
• Ensure model correctness and consistency across environments, versions, and data distributions through rigorous validation and monitoring practices
• Optimize end-to-end workflows for both training and inference, including data loading, batching, preprocessing, and model serving
• Work within a fast-moving, mission-driven team to build foundational AI technology used by Fortune 100 companies to unlock trillions of dollars in enterprise value
• Engage in peer code reviews, system design discussions, and cross-functional alignment with research, data, and infrastructure teams
• Continuously improve tooling and development practices to support high-fidelity experimentation and production deployment of large-scale tabular models
• Maintain awareness of advancements in neural architectures for tabular data and apply relevant innovations to improve model performance and scalability
• Participate in debugging complex system-level issues involving Python-Rust-C++ interoperability, memory leaks, or GPU/CPU resource contention

🎯 Requirements

• Strong software engineering fundamentals with expert-level Python and Rust
• Hands-on experience bridging Python and Rust (PyO3, maturin, or custom extensions)
• Working proficiency in C++ and experience bridging Python and C++ (PyBind11, Cython, or custom extensions)
• Experience developing and maintaining ML models in production
• Strong understanding of neural networks
• Track record of optimizing performance-critical code
• Strong profiling and debugging skills (CPU, memory, latency)

🏖️ Benefits

• Competitive compensation with salary and equity
• Comprehensive health coverage, including medical, dental, vision, and 401K
• Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
• Relocation support for employees moving to join the team in one of our office locations
• A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

Skills & Technologies

Python

Rust

PyTorch

Data Science

Hybrid

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About Fundamental

Fundamental is a company focused on providing innovative solutions and services. They aim to empower businesses by leveraging cutting-edge technology and expert insights. Their offerings span various sectors, addressing complex challenges with tailored approaches. The company is committed to driving growth and efficiency for its clients through a blend of strategic planning and practical execution. With a strong emphasis on research and development, Fundamental continuously seeks to advance its capabilities and deliver value-added services. Their client-centric model ensures that solutions are aligned with specific business objectives, fostering long-term partnerships and mutual success. Fundamental strives to be a reliable partner in navigating the evolving business landscape.

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