Senior Data Scientist: ML/LLM & Model Optimization

Testing Site - JPMC; Buenos Aires; On-site; ARS 90,873,000 - 151,455,000; Full time

Job summary

Testing Site - JPMC is seeking a Machine Learning Data Scientist Specialist to lead development, deployment, and optimization of ML models across applications/web interfaces. The role emphasizes training, fine-tuning, evaluating, and integrating language models using Infinite AI Training/serving architecture to accelerate predictive capabilities within the Technology Governance Risk and Execution Team.

The candidate should have expertise in ML, AI model fine-tuning, and prompt engineering for

Qualifications

• Experience with ML algorithms, statistical modelling, and predictive analytics.
• Proficiency in Python and R with libraries such as scikit-learn, pandas, NumPy.
• Hands-on experience with cloud computing and MLOps tools.
• LLM prompt engineering and familiarity with OpenAI tooling and agents.

Responsibilities

• Research, develop, and optimize machine learning models for various applications/web interfaces.
• Fine-tune pre-trained models using domain-specific datasets and LLM architectures (e.g., GPT, LLaMA).
• Implement, evaluate, and improve ML pipelines to enhance model performance.
• Design efficient training workflows and optimize inference performance.
• Work with cross-functional teams to integrate ML and LLM capabilities into products.
• Conduct rigorous testing and benchmarking of ML and LLM models.
• Utilize OpenAI libraries to experiment with and deploy LLM-based solutions.

Skills

ML algorithms

Statistical modelling

Predictive analytics

Data preprocessing

Feature engineering

Model evaluation

Python

R

scikit-learn

TensorFlow

PyTorch

pandas

NumPy

OpenAI SDKs

caret

Tools

OpenAI SDKs

TensorFlow

PyTorch

Job description

Testing Site - JPMC is seeking a Machine Learning Data Scientist Specialist to lead development, deployment, and optimization of ML models across applications/web interfaces. The role emphasizes training, fine-tuning, evaluating, and integrating language models using Infinite AI Training/serving architecture to accelerate predictive capabilities within the Technology Governance Risk and Execution Team.

The candidate should have expertise in ML, AI model fine-tuning, and prompt engineering for