Job Overview

💡 About the Role: This role involved developing and deploying machine learning models to enhance core platform features like matching and recommendations. The engineer researched and implemented AI techniques to solve complex problems and improve user engagement. 🛠️ Tech Stack (previously required): Python, TensorFlow/PyTorch, Scikit-learn, Pandas, NumPy, MLOps tools, SQL/NoSQL, Cloud ML Platforms (GCP AI Platform, AWS SageMaker), Git. 💰 Compensation Note: This position can be paid or unpaid, depending on the number of applications we receive and our current hiring scenario. 👥 Status: We're not accepting applications for this role currently, but feel free to join our waitlist or follow us for future openings.

Responsibilities

• Design, train, and deploy machine learning models.
• Collect and preprocess large datasets for model training.
• Evaluate and improve model performance.
• Integrate ML models into production systems.
• Stay up-to-date with the latest advancements in AI/ML.
• Collaborate with product and engineering teams to define AI-driven features.

Qualifications

• Proven experience as an AI/ML Engineer or similar role.
• Strong understanding of machine learning algorithms and statistical modeling.
• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with MLOps practices and tools.
• Familiarity with data processing and feature engineering.
• Experience with deploying models to cloud environments.