Senior Data Scientist / ML Engineer with AWS

Valiant Technologies LLC; San Jose (CA); Presencial; USD 150.000 - 210.000; Jornada completa

Descripción de la vacante

Valiant Technologies LLC is seeking a Senior Data Scientist / ML Engineer with AWS expertise in San Jose, CA. The role focuses on building large-scale AI pipelines, from data curation to model fine-tuning and deployment on SageMaker.

You will lead distributed training, RLHF-style methods, and ensure data privacy and secure production inference while communicating clearly with stakeholders.

Formación

• Experience with PySpark and Hadoop for large corpora.

Responsabilidades

• Turn unstructured and structured traveler and catalog data into narrative text documents and synthetic data at scale (millions of docs).
• Feature and context engineering: decide what information goes into each document.
• Large-scale distributed training on Amazon SageMaker AI (HyperPod).
• Fine-tuning: LoRA/QLoRA adapters; supervised training; reinforcement learning for ranking.
• Deep learning modeling: architectures, ranking heads, multi-task setups.
• Inference and deployment: low-latency, cost-efficient serving on AWS.
• Evaluation and error analysis: create evaluation sets and report findings to customer and AWS team.
• Data privacy: handling customer data safely including removals.

Conocimientos

Spark PySpark

Hadoop Hive

SageMaker

LoRA/QLoRA

PyTorch

LLM inference

Data privacy AWS

Communication

MLOps

Herramientas

HyperPod

Bedrock

IAM

KMS

Lake Formation

Descripción del empleo

Senior Data Scientist / ML Engineer with AWS

Location:

Duration:

16Months+ Extension

Domain Exposure:

Oil & Gas

Work Authorization:

• Data to training sets: turn unstructured and structured traveler and catalog data into narrative text documents and synthetic data, at a scale of tens of millions of documents.


• Feature and context engineering: decide what information goes into each document and how to express it, such as market-relative price, tier and trip context.


• Large-scale distributed training on Amazon SageMaker AI, including HyperPod.


• Fine-tuning: LoRA/QLoRA adapters, supervised training, and reinforcement learning for ranking and reasoning.


• Deep learning modeling: model architecture, ranking heads, co-training and multi-task setups.


• Inference and deployment: low-latency, cost-efficient serving, including quantization, distillation and profiling.


• Evaluation and error analysis: build evaluation sets, run ablations and catch data leakage. Write up findings clearly for the customer and the AWS science team.


• Data privacy: handle customer data safely, including removing per

Required skills:

• Spark (PySpark) and the Hadoop ecosystem (Hive, HDFS) on corpora of tens of millions of documents.


• Amazon SageMaker AI: processing, training, distributed training (HyperPod), deployment.


• LLM fine-tuning (LoRA/QLoRA) and reinforcement learning (e.g. GRPO/PPO-style methods).


• Strong deep learning fundamentals in PyTorch: architectures, training dynamics, co-training.


• Large-scale batch LLM inference and production inference (vLLM, Amazon Bedrock batch).


• Data privacy and security on AWS: personal-data removal, IAM, KMS, Lake Formation.


• Clear written communication with customer and science stakeholders.

Preferred skills:

• AWS Trainium / Inferentia (Neuron SDK).


• Recommender systems: ranking metrics (NDCG, MRR), sequential and generative recommenders.


• Embedding quantization or semantic IDs.


• Experience in a customer-facing or embedded role.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.