Senior Data Scientist | AWS SageMaker ML Engineer

Artifintech; San Jose (CA); Presencial; USD 140.000 - 210.000; Tempo integral

Resumo da vaga

Artifintech in San Jose, CA is seeking a Senior Data Scientist / ML Engineer with AWS experience to lead large-scale data processing and model deployment.

You will work on data-to-text pipelines, feature engineering, and distributed training using SageMaker, with a focus on LoRA/QLoRA fine-tuning and reinforcement learning for ranking and reasoning.

The role emphasizes production-grade ML, secure data handling, and clear communication with customers and the AWS science team.

Qualificações

• Experience with Spark (PySpark) and Hadoop ecosystem including Hive and HDFS at scale.
• Proficiency in Amazon SageMaker, training, distributed training, and deployment.
• Hands-on ML with PyTorch, model tuning (LoRA/QLoRA) and RL for ranking/decision.
• Strong data privacy and secure AWS practice; clear stakeholder communication.

Responsabilidades

• Transform unstructured and structured data into narrative documents and synthetic data at scale.
• Design features and context for documents, including market-relative pricing context.
• Perform large-scale distributed training on SageMaker AI (HyperPod).
• Fine-tune and train with LoRA/QLoRA and RL methods for ranking and reasoning.
• Develop deep learning models, architectures, and co-training setups.
• Implement low-latency, cost-efficient inference and monitoring.
• Evaluate results, write customer-ready findings, and ensure data privacy.

Conhecimentos

PySpark

Hadoop

Hive

HDFS

SageMaker

LoRA/QLoRA

PyTorch

LLM

ML Deployment

Reinforcement learning

Descrição da vaga

Artifintech in San Jose, CA is seeking a Senior Data Scientist / ML Engineer with AWS experience to lead large-scale data processing and model deployment.

You will work on data-to-text pipelines, feature engineering, and distributed training using SageMaker, with a focus on LoRA/QLoRA fine-tuning and reinforcement learning for ranking and reasoning.

The role emphasizes production-grade ML, secure data handling, and clear communication with customers and the AWS science team.