Data Scientist Associate Sr - Prompt Engineering

Testing Site - JPMC; Buenos Aires; Presencial; ARS 90.873.000 - 151.455.000; Jornada completa

Descripción de la vacante

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

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

ML algorithms

Statistical modelling

Predictive analytics

Data preprocessing

Feature engineering

Model evaluation

Python

R

scikit-learn

TensorFlow

PyTorch

pandas

NumPy

OpenAI SDKs

caret

Herramientas

OpenAI SDKs

TensorFlow

PyTorch

Descripción del empleo

Machine Learning Data Scientist Specialist to drive the development, deployment, and optimization of machine learning models. The ideal candidate will have expertise in data science, machine learning (ML), and AI model fine-tuning. You will be responsible for training, fine-tuning, evaluating, and integrating language models into various applications/web user interfaces using Infinite AI Training/serving architecture to accelerate our ability to deliver predictive data capabilities in the Technology Governance Risk and Execution Team.

The role also involves applying experience with large language models (LLMs), including prompt engineering and leveraging OpenAI libraries and tools to build, deploy, and monitor intelligent applications and agents.

Job Responsibilities

• Research, develop, and optimize machine learning models for various applications/web user 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 and frameworks to experiment with and deploy LLM-based solutions

Required qualifications, capabilities, and skills

• Experience with ML algorithms, statistical modelling, and predictive analytics
• Proficiency in data preprocessing, feature engineering, and model evaluation
• Strong coding skills in Python and R, along with experience using relevant libraries such as scikit-learn, TensorFlow, PyTorch, pandas, NumPy, caret, and OpenAI SDKs
• Experience in data visualization and exploratory data analysis (EDA)
• Hands-on experience with cloud computing services (AWS, GCP, Azure) and MLOps tools
• Experience in LLM prompt engineering and familiarity with concepts related to LLM agents (e.g., tool use, memory, agent frameworks

Preferred qualifications, capabilities, and skills

• Strong written and verbal communication skills.
• Excellent problem-solving skills with a natural inclination towards data-driven decision-making.
• Ability to work independently and take initiative in a fast-paced environment.
• Strong customer service orientation with the ability to build positive working relationships with stakeholders.
• Teamwork and cooperation – ability to work effectively in a team-oriented environment.