Machine Learning Engineer for French AI startup

About Nica Recruiting

Welcome to Nica Recruiting – your solution for challenging candidate sourcing and hiring. We use an embedded recruiting approach. This means we work closely with your team to solve hiring challenges and uncover exceptional candidates. Unlike traditional agencies, we're not just about candidates. Unlike typical consulting firms, we don't just advise. And we're more than an RPO – we dive into the heart of recruiting challenges.

Position

Join our team as a Machine Learning Research Engineer and play a key role in the development and maintenance of our AI-based systems. From conceptualizing experiments to implementing innovative ideas, you will be responsible for all an AI/ML project’s life cycle. You will have the opportunity to impact the industry in a meaningful way, by participating in its transformation with AI. More concretely, our projects predominantly focus on text and speech data, emphasizing Natural Language Processing (NLP) and speech processing, including ASR, speech analysis, and denoising systems.

As an ML Engineer, your responsibilities encompass a broad spectrum of tasks:

• Conceiving and developing end-to-end AI systems, from data collection and processing to module development, and evaluation methods and metrics

• Defining and implementing AI systems, creating data pipelines, and incorporating features based on infrastructure and performance requirements

• Establishing a benchmarking system to compare and select system evolutions using tools like Hydra, Metaflow/MLFlow, Weight&Biases, etc

• Defining data collection, annotation, and processing protocols, developing processing pipelines, and creating datasets for specific applications

• Managing data collection and processing for training and testing machine learning-based systems

• Analyzing data to optimize products, adapting models, reconsidering modalities, and creating new user behavior metrics

• (Optional) Contributing to publications such as blogs, scientific articles, and interviews

What You Will Use:

• Python

• Machine learning libraries like TensorFlow, PyTorch, ONNX and huggingface's transformers library

• Database technologies like MongoDB and SQL

• MLOps platforms

• Dependency management tools like Docker

• Version control tools: git/github

Your qualification

• Excellent proficiency in Python coding

• Proven experience in implementing machine learning systems

• Capability to work with popular machine learning frameworks and libraries such as TensorFlow, PyTorch, ONNX, huggingface's transformers library, and MLOps platforms. Proficiency with both TensorFlow and PyTorch is preferred

Will be a plus

• Background in NLP or speech processing (ideally both)

• Strong theoretical foundation

• Experience with NLP libraries and generative models

• Familiarity with ASR, speaker recognition, speech synthesis, and speaker diarization

• Proficiency in Docker for efficient deployment

• Knowledge of MLOps methodology and implementation

• Familiarity with database technologies (SQL or NoSQL) for effective data management