🛠 Tech Stack

💼 About This Role

You'll build, train, and deploy ML models and data pipelines for fast-growing global companies. You'll own the full ML lifecycle from data sourcing to production deployment. The role combines strong data engineering foundations with cutting-edge AI work, offering competitive pay and remote flexibility.

🎯 What You'll Do

• Design, build, and maintain robust data pipelines for ingestion and transformation
• Develop, train, evaluate, and iterate on ML models across various tasks
• Fine-tune and adapt pre-trained LLMs for specific use cases
• Build and manage MLOps infrastructure including experiment tracking and deployment

📋 Requirements

• Strong Python skills with hands-on ML libraries (scikit-learn, PyTorch, TensorFlow)
• Solid data engineering experience with SQL, ETL, and large-scale datasets
• Practical experience with model training, evaluation, hyperparameter tuning, and deployment
• Prior remote work experience and fluency with remote collaboration tools

✨ Nice to Have

• Experience with distributed data processing (Spark, Dask)
• Familiarity with vector databases and embedding-based retrieval
• Background with real-time or streaming data pipelines (Kafka, Flink)

🎁 Benefits & Perks

• 💰 Competitive pay with multiple ranges
• 🏡 Fully remote work in US time zones
• 🚀 Real growth opportunities with fast-growing companies

📨 Hiring Process

Estimated timeline: 1-2 weeks · AI estimate

1. 1Application form with video recording· 15 min
2. 2Recruiter call· 30 min
3. 3Technical interview· 60 min