Machine Learning Engineer II at Glidewell Dental Irvine, CA

Shell Lubricants Hub Hamburg; Irvine (CA); On-site; USD 117,000 - 146,000; Full time

Job summary

Shell Lubricants Hub Hamburg is seeking a Machine Learning Engineer II based in Irvine, CA. The role involves designing, developing, and deploying machine learning models for real-world applications, as well as building scalable data pipelines.

The ideal candidate will have a Master's degree in Machine Learning or a related field and at least three years of relevant experience. Strong skills in Python and AWS are required, along with knowledge of various machine learning libraries.

Qualifications

• 3+ years of experience in machine learning or related field.
• Proficient in SQL for data handling.
• Experience with deploying ML models in production environments.

Responsibilities

• Design and optimize ML models for real-world applications.
• Build data ingestion and embedding pipelines.
• Work with stakeholders to deliver technical solutions.

Skills

Machine learning algorithms

Data aggregation

Python programming

AWS services

Feature engineering

Education

Master’s degree in Machine Learning or related field

PhD preferred

Tools

TensorFlow

scikit-learn

AWS RedShift

pandas

pytorch

Job description

Machine Learning Engineer II job at Glidewell Dental. Irvine, CA.

Job Description

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