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Machine Learning Engineer II

Machine Learning Engineer II

Glidewell DentalIrvine, California, US
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Essential Functions :

  • Designs, develops, and deploys machine learning models for real-world applications.
  • Builds scalable pipelines for data ingestion, pre-processing, training, and inference.
  • Owns end to end development of machine learning algorithms including data analysis, feature engineering, model development, training, validation, and performance evaluation.
  • Designs, implements, and optimizes retrieval-augmented generation (RAG) pipelines that combine large language models (LLMs) with vector search / retrieval systems.
  • Builds data ingestion and embedding pipelines for efficient indexing and retrieval.
  • Fine-tunes and adapts LLMs for domain-specific tasks such as instruction tuning, prompt engineering, low-rank adaptation (LoRA), etc.
  • Engages in both engineering and research, exploring latest ML algorithms, solution architectures, and cutting-edge approaches to improve retrieval and generation performance.
  • Works with stakeholders to translate business requirements into robust technical solutions that deliver measurable impact.
  • Works with engineering teams to continuously scale and advance machine learning across the organization.
  • Identifies new opportunities of applying ML technology to improve business workflows and processes.
  • Builds a deep understanding of the company's products, services, data, and customers to deliver impactful solutions.
  • Performs other related duties and projects as business needs require at direction of management.

Education and Experience :

  • Master's degree in Machine Learning, Deep Learning, or a computer science-related field. PhD preferred.
  • Minimum three (3) years of relevant work experience in the areas below, or any equivalent education and / or experience from which comparable knowledge, skills and abilities have been demonstrated / achieved :
  • Understands fundamental concepts, practices, and procedures of machine learning field.
  • Data discovery, data aggregation, and feature engineering with SQL query writing skills.
  • Training, evaluating, optimizing, deploying, and maintaining machine learning models on production systems.
  • Logging, tracking, A / B testing, evaluating and analyzing the performance of different machine learning algorithms and models in production.
  • Strong development skills in Python programming language and have experience in developing data-driven, scalable, and reliable applications with Amazon Web Services (AWS).
  • Applying machine learning algorithms to solve a wide range of optimization problems like customer sales prediction, recommendation engine, sentiment analysis, deep learning with image and natural language, customer segmentations / clustering, and object detection.
  • Utilization of popular open-source machine learning / deep learning libraries like LangChain, HuggingFace, Tensorflow, scikit-learn, pandas, pyTorch, and Keras.
  • Experience working with relational, non-relational, and high-scale data processing and storage frameworks like Structured Query Language (SQL), AWS RedShift, Aurora, S3, DynamoDB, MySQL, PostgreSQL.
  • Experience with AWS Serverless architecture and AWS native services like BedRock, EC2, Lambda, Step Functions, SageMaker, Rekognition, Comprehend, Lex / Polly, and Transcribe.
  • Pay Range : $117,000 - $146,000 / YR

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