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STATION F

INTERN ML ENGINEER/DATA SCIENTIST

STATION F
France · Internship · Internship
À propos

Opale is a GenAI platform for investment funds and M&A deals. We are reimagining the future of investment strategies by unlocking human-like syntheses at scale. Our platform leverages proprietary technology and state-of-the-art LLM models to uncover rich insights and produce deep analysis in a few seconds.

Descriptif du poste

Within the AI Engineering squad, you'll work on state-of-the-art models, retrieval and optimization techniques. Leveraging those, you'll contribute to the next features that we're integrating into the platform and our production environment. 🚀

Here are some topics that we're actively working on :

👁️ Develop and implement fine-tuned vision models (YOLO, multi-modal transformers) for specific tasks within our pipelines

  • You will be responsible for creating and integrating advanced vision models such as YOLO and multi-modal transformers. These models will be tailored to perform specific tasks within our data processing pipelines, ensuring high accuracy and efficiency.

🦀 Optimize model inference for blazingly-fast performance

  • Your role will involve collaborating on enhancing the speed and efficiency of model inference. This includes implementing techniques to reduce latency and increase throughput, ensuring that our AI models can process data and deliver results in real-time and explore a few of the new frameworks that we're aiming at working with.

📊 Contribute to building market studies, landscape analysis, and risk identification agents

  • You will play a key role in developing tools and systems for market studies and landscape analysis. This involves creating AI-driven agents that can identify market trends, analyze competitive landscapes, and detect potential risks. These insights will help inform strategic decisions and mitigate risks for our platform users.

🔍 Work on a building a LLM validation framework

  • We're building capabilities to ensure that these models function correctly and produce reliable, accurate outcomes. You'll be assessing the model's performance, integrity, and practical applicability.

📋 Internship Details

  • ⏳ Duration: 6 months.
  • 🗓️ Start Date: Starting from March 2025.
  • 📍 Location: Paris (Station F).
  • 💰 Compensation: Commensurate with experience and internship duration.

Profil recherché

🦄 Ideal Candidate

  • 📚 Currently pursuing an advanced degree in Data Science, Machine Learning, or any related field.
  • 💻 You have strong software engineering skills to bring ideas to life in production.
  • 🔬 Proactive, detail-oriented engineer who delivers clean, maintainable, and high-performance code with a focus on quality.
  • 🏎️ Passion for optimizing model performance and inference speed.
  • 🧪 Scientific mindset with insatiable intellectual curiosity.
  • 🤝 Ability to work collaboratively in a fast-paced startup environment.
  • 🐍 Proficiency in Python and relevant ML libraries (PyTorch, Hugging Face).

✨ Bonus Skills

  • 🦀 You're familiar with Rust.
  • 📈 Experience with financial data or investment analysis.
  • 🌐 Familiarity with any cloud computing platforms (AWS, GCP, Azure).

Process de recrutement

  • First, we'll schedule a 30-minute video call to get to know you and skills better, as well as give you insights about the job and the company.
  • Next, we’ll schedule a 1h30 live coding interview with a senior member of the team.
  • Finally, we'll invite you for a last round on-site interview so you can meet the team and we'll give you a sneak peek into our daily routine.

Informations complémentaires

  • Type de contrat : Stage (6 à 6 mois)
  • Lieu : Paris
  • Niveau d'études : Bac +5 / Master
  • Télétravail partiel possible

Key Skills

Ranked by relevance

ai machine learning pytorch python cloud aws gcp
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Country Guide

France

Large economy with strong startup and AI ecosystem

Posted
Feb 06, 2025
Type
Internship
Level
Internship
Location
Paris
Company
STATION F

Industries

Technology Information Internet

Categories

Engineering Information Technology

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