Senior Data Scientist (AWS SageMaker) – ML Engineer

Cloud Analytics Technologies, LLC; San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Cloud Analytics Technologies, LLC seeks a Senior Data Scientist / ML Engineer with AWS expertise to build and deploy large-scale NLP/data processing solutions. You will handle data-to-text conversion, feature engineering, and distributed training on SageMaker AI, including HyperPod.

Responsibilities include fine-tuning LLMs (LoRA/QLoRA), RL for ranking, and developing production-grade inference with cost efficiency. Strong communications with customers and AWS teams are essential.

Qualifications

• Experience with Spark/PySpark and Hadoop ecosystems handling large corpora.
• Proficient with SageMaker AI: processing, training, distributed training, deployment.
• Experience with fine-tuning LLMs (LoRA/QLoRA) and RL methods.
• Strong understanding of PyTorch, model architectures, and training dynamics.
• Experience with large-scale batch LLM inference and production serving (vLLM, Bedrock batch).
• Knowledge of data privacy and security on AWS (IAM, KMS, Lake Formation).
• Clear written communication with customers and stakeholders.

Responsibilities

• Data to training sets: convert unstructured and structured data into narrative documents at scale.
• Feature and context engineering: define information to include in documents.
• Conduct large-scale distributed training on SageMaker AI (HyperPod).
• Fine-tune models using LoRA/QLoRA and reinforcement learning for ranking.
• Develop deep learning models and multi-task setups.
• Implement low-latency, cost-efficient inference and deployment strategies.
• Perform evaluation, error analysis, and documentation for customers.

Skills

PySpark

Hadoop/Hive

SageMaker

LoRA/QLoRA

PyTorch

LLM inference

AWS IAM/KMS

Technical communication

Education

Bachelor's in CS/Math/Stats

Tools

SageMaker

Bedrock

PyTorch

Spark/Hadoop

IAM/KMS

Job description

Cloud Analytics Technologies, LLC seeks a Senior Data Scientist / ML Engineer with AWS expertise to build and deploy large-scale NLP/data processing solutions. You will handle data-to-text conversion, feature engineering, and distributed training on SageMaker AI, including HyperPod.

Responsibilities include fine-tuning LLMs (LoRA/QLoRA), RL for ranking, and developing production-grade inference with cost efficiency. Strong communications with customers and AWS teams are essential.