Machine Learning Engineer II

Glidewell Dental • Irvine, CA

95d • $117,000 - $140,000

About The Position

The position involves designing, developing, and deploying machine learning models for real-world applications. The candidate will build scalable pipelines for data ingestion, pre-processing, training, and inference. They will own the end-to-end development of machine learning algorithms, which includes data analysis, feature engineering, model development, training, validation, and performance evaluation. Additionally, the role requires designing, implementing, and optimizing retrieval-augmented generation (RAG) pipelines that combine large language models (LLMs) with vector search/retrieval systems. The candidate will also build data ingestion and embedding pipelines for efficient indexing and retrieval, fine-tune and adapt LLMs for domain-specific tasks, and engage in both engineering and research to explore the latest ML algorithms and solution architectures. Collaboration with stakeholders to translate business requirements into technical solutions is essential, as is working with engineering teams to scale and advance machine learning across the organization. The candidate will identify new opportunities to apply ML technology to improve business workflows and processes, and will build a deep understanding of the company’s products, services, data, and customers to deliver impactful solutions. Other related duties and projects may be assigned as business needs require.

Requirements

• 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 machine learning or equivalent education/experience.
• Understands fundamental concepts, practices, and procedures of machine learning.
• 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 experience in developing data-driven, scalable, and reliable applications with Amazon Web Services (AWS).
• Applying machine learning algorithms to solve 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 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Master's degree
• Number of Employees: 1,001-5,000 employees