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:
- telemetry or sensor data
- anomaly detection
- forecasting systems
- Strong Python and ML framework experience:
- PyTorch
- TensorFlow
- 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