Description
Seeking a Machine Engineer to Train and optimize a financial quant AI black box for stock trading. The role involves working with PyTorch, PEFT, and understanding model weights, ranks, and tuning techniques. The LoRA will need another stacked LoRA. Model is already trained and tuned for April 2026. It sat on a shelf since then that time so it will need to fed back data and news from April 2026 - present. Hence it will need additional training (stacked LoRa) and tuning. Current model performs but has memory gaps that need to be filled and to get certainty rate back to original levels. Currently subject to less than certain known rates due to lack of and missing data sources. Not looking for improvement of model but rather ingestion of new data, the gaps, and necessary training and tuning with current data to get back to the known accuracy rate. Comes with open weights and adjustmnets though with limited internal documentation. Unique, propietary model. Ability to save token utilization is a plus. Intermediate to Intermediate Plus to Expert: PyTorch, Model Weights, Ranks, PEFT, Knowledge of Finance is a Plus, VIX and Volatility, Backtesting, LA Bias, Tech Indicators, Knowledge of Quant Finance, Time Series Analysis, Train Validation Testing and Market Data API's. Knowledge of financial news sources, social media API's and scrapes, and Polygon, Massive tick by tick,time-series, is a plus. This model will need to ingest copious amounts of known and esoteric API's and scrapes. We