🛠 Tech Stack

💼 About This Role

You'll design, develop, and maintain scalable machine learning models and pipelines. You'll collaborate with cross-functional teams to translate business problems into data-driven solutions. This role offers the opportunity to work with cloud platforms and MLflow for end-to-end ML lifecycle management.

🎯 What You'll Do

• Design, build, and deploy scalable ML models and pipelines
• Develop and optimize data processing workflows using Python, SQL, and PySpark
• Deploy and monitor ML models in cloud environments
• Collaborate with cross-functional teams on data-driven solutions

📋 Requirements

• 5+ years of experience as a Machine Learning Engineer
• Strong proficiency in Python, SQL, and PySpark
• Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost
• Experience deploying models in cloud platforms such as AWS, GCP, Azure, or Databricks

✨ Nice to Have

• Experience with MLflow or similar pipeline tools
• Experience with Kubernetes for ML workloads
• Experience with CI/CD and MLOps practices

🎁 Benefits & Perks

• 💻 Remote Work (Hybrid model)
• 📈 Professional Development opportunities
• 🌍 Global Company culture
• 🏖️ Flexible Time Off

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min