We are looking for a hands-on Data Scientist with strong experience building and training deep learning models for time-series and sensor data applications.

This is NOT a reporting, analytics, or pipeline-only role. We are specifically looking for candidates who have personally trained, fine-tuned, validated, and deployed machine learning and deep learning models.

What You’ll Work On

• Build and train deep learning models for time-series and multi-modal sensor data
• Develop forecasting, anomaly detection, and predictive maintenance systems
• Work with large-scale operational telemetry data including pressure, temperature, vibration, and sequential sensor streams
• Experiment with and fine-tune Transformer-based architectures and modern AI/LLM systems
• Design and evaluate models using frameworks such as PyTorch or TensorFlow
• Collaborate with domain experts and engineering teams on production AI systems

Required Experience

• Strong hands-on experience training deep learning models (not just integrating APIs or building pipelines)
• Experience building models using:
• Transformers
• LSTMs
• CNNs
• Time-series forecasting architectures
• Experience working with:
• sequential/time-series data
• telemetry or sensor data
• anomaly detection
• forecasting systems
• predictive maintenance
• Strong Python and ML framework experience:
• PyTorch
• TensorFlow
• HuggingFace
• Experience fine-tuning or implementing transformer/LLM models
• Experience validating and optimizing models using real-world datasets

Strong Plus

• Experience training or contributing to foundation-style models
• Industrial AI, drilling, manufacturing, IoT, robotics, or operational telemetry experience
• Experience with distributed training, GPU optimization, or large-scale inference systems
• RAG, embeddings, or vector database experience