Start searching
Back to Jobs
Recently postedRemoteTechnology

Senior Data Scientist / ML Engineer

Rivago infotech incUnited States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeRemote
LocationUnited States
Apache SparkAWSDeep LearningHadoopHiveLLMPyTorchExpressIAM

Job description

Role: Senior Data Scientist / ML Engineer with AWS

Location: Remote

Summary: Works on data to build, train and deploy next-generation LLM-based recommender systems. The role covers the full path from raw customer data to a deployed model.
Responsibilities:

  • 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.

Similar jobs

Apply