About the job

Neuralk-AI is looking for an experienced Full-Stack ML Engineer to build our AI embedding platform and work hand in hand with our science team to accelerate research.

You will report to the CSO of Neuralk and will be located in our Paris offices.

‍

About Neuralk

We are a passionate team leading the way in AI innovation, committed to driving the rapid adoption of transformative AI applications. Our focus is on developing the technical tools to allow any company to build AI applications that natively interact with their structured databases (tabular or graph databases). Specifically, we develop a modern AI embedding platform to convert any structured database to a vectorstore that can later be combined with classic Machine Learning models for classification, regression or clustering purposes.

As an early-stage AI-driven startup backed by significant funding (>3m), we base our approach on state-of-the-art academic research to drive practical business solutions. We value clear communication and simplicity in our approaches, promoting a constant optimization mindset.

Join Neuralk to be part of a growing team, eager to learn and adapt, united by the belief that our technology can make a significant positive impact and contribute to transforming the AI industry.

Co-founders: Alexandre Pasquiou (CSO) & Antoine Moissenot (CEO).

Neuralk is dedicated to equal opportunity employment and fosters an environment that is open and respectful of diversity. All applicants are encouraged to apply, even if you don’t meet all requirements. If you have passion for our mission, learn quickly and believe you can contribute, we want to hear from you.

Mission Highlights

As a Full-Stack ML Software Engineer, your role will be to drive the development and optimization of our AI Embedding model platform from a software perspective. You will drive the very core of our platform with a focus on high quality software engineering, code parallelization, optimizing scientific computing tasks, and deploying robust cloud infrastructure. You will collaborate closely with our research and engineering teams (~5 people) to enhance the performance, scalability and efficiency of our AI-driven solutions. In particular, you will contribute to open-source projects by developing tools that accelerate research experiments and monitoring.

‍

Role & Responsibilities

This position is the keystone to our company’s core initiative to build a platform that automates representation tasks on structured datasets. You will lead the architectural choices and software developments in close collaboration with other ML engineers in the team.  You will be responsible for:

• Software Development: Develop and maintain high-quality code, implementing best practices for software development, including code reviews, testing, and version control.
• Open-Source: Champion the company's open-source ethos by fostering the development and sharing of internally created tools, driving collaboration and innovation within the broader community.
• Data Management: Develop and implement robust systems for efficient data processing, storage, retrieval, and streaming, optimized for handling large datasets essential to machine learning models. This includes establishing procedures to ensure full traceability of data, models, and training pipelines, ensuring integrity and reproducibility throughout the workflow.
• Parallelization and Performance Optimization: Design and implement parallelized code to speed-up CPU- and GPU-bound tasks. Optimize existing code for performance, particularly in training and inference environments.
• Computational infrastructure: Design and deploy cloud-based HPC-like/bare-metal infrastructure. Set up and maintain DevOps/MLOps pipelines for ML projects. Implement and manage distributed training workflows and tools. Ensure scalability and cost-effectiveness.
• Support for ML Engineers: Assist other ML engineers with performance issues, including GPU performance, particularly those related to deep learning frameworks. Provide support for optimizing and debugging code where necessary.‍
• Collaboration and Communication: Work closely with other engineers and scientists in the team to foster a collaborative environment through clear documentation and mutual learning. Participate in team meetings and strategic discussions.

Profile

• PhD or M.S in Computer Science, Machine Learning or a closely related field, with a focus on deep learning.
• 5+ years of experience with software development, with a deep understanding of scientific computing and low-level optimizations.
• Demonstrated machine learning experience in open-source.
• Excellent communication skills in English.
• Proven ability to work with interdisciplinary teams.
• Thrives in a fast-paced, evolving startup environment.
• Self-starter and autonomous.

‍

Bonuses

• You have demonstrated experience in designing and running large-scale ML experiments.
• Track record of translating research into business impact.
• Experience in developing and debugging in C/C++, Python.

Expertise

• Software Development: Excellent software engineering skills in Python and C/C++, with experience in software development best practices, semantic versioning and version control systems such as Git.
• Machine Learning Frameworks: Proficiency in PyTorch and familiarity with JAX and frameworks like PyTorch Lightning, Torch Fabric, DeepSpeed, etc.
• Scientific Computing: Experience with HPC infrastructure, numerical simulations or large-scale parallel computing.
• Data Management and Storage: Knowledge of various database formats (including SQL and NoSQL databases), data warehousing solutions, and data management best practices.‍
• GPU Optimization: Experience in optimizing GPU utilization and performance in the context of deep learning training tasks. Experience developing and optimizing CUDA code for GPU acceleration is a plus.

Compensation & Benefits

We are a fast-pace startup, yet, we favor a good work-life balance and interesting compensations. We offer:

• A competitive salary
• Equity (BSPCE), to reflect the value you bring to Neuralk and to foster a shared journey
• Comprehensive health insurance
• French level paid leave and time-off work
• Dynamic work setting. Although our preference is for in-person collaboration, we will be flexible with occasional remote work arrangements.
• and more to come as we grow