Machine Learning Engineer II

Glidewell Dental offers a comprehensive benefits package, an onsite Irvine workplace, and a diverse, collaborative culture designed to support professional growth. You’ll join a team that values practical ML solutions, thoughtful experimentation, and measurable impact, backed by strong wellness and family-friendly benefits.

Benefits

• Medical, dental, and vision coverage
• 401(k) with company match
• Company-paid life insurance
• Paid time off including vacation, holidays, and sick days
• Employee gym with fitness classes and a meditation room
• On-site medical and wellness center offering massage therapy and acupuncture
• Company-subsidized cafes and public internet cafes
• Employee lounges with big screen TVs and game tables
• Company-sponsored events and a diverse work environment with over forty nationalities represented
• Employee discounts and a flexible spending account
• Retirement plan with ongoing benefits

Responsibilities

• Design, develop, and deploy machine learning models for real-world applications
• Build scalable pipelines for data ingestion, pre-processing, training, and inference
• Own end-to-end development of ML algorithms, including data analysis, feature engineering, model development, training, validation, and performance evaluation
• Design, implement, and optimize retrieval-augmented generation pipelines that fuse large language models with vector search
• Construct data ingestion and embedding pipelines to enable efficient indexing and retrieval
• Fine-tune and adapt LLMs for domain-specific tasks via instruction tuning, prompt engineering, and low-rank adaptation techniques
• Engage in both engineering and research to explore cutting-edge ML methods and architectures to boost retrieval and generation performance
• Collaborate with stakeholders to translate business requirements into robust technical solutions with measurable impact
• Partner with engineering teams to scale and advance ML initiatives across the organization
• Identify new opportunities to apply ML to improve business workflows and processes
• Develop a deep understanding of Glidewell's products, data, and customers to deliver impactful solutions
• Contribute to related duties and projects as business needs require

Requirements

• Master's degree in Machine Learning, Deep Learning, or a computer science related field; PhD preferred
• Minimum three years of relevant work experience, or equivalent education/experience
• Strong grasp of fundamental ML concepts, practices, and procedures
• Experience with data discovery, data aggregation, and feature engineering using SQL
• Experience training, evaluating, optimizing, deploying, and maintaining ML models in production
• Ability to log, track, A/B test, and analyze performance of ML algorithms in production
• Proficient Python development and a track record of building data-driven, scalable, reliable applications on AWS
• Applied ML to a variety of optimization problems such as sales forecasting, recommendation systems, sentiment analysis, computer vision and NLP, clustering, and object detection
• Experience with open-source ML/DL libraries including LangChain, HuggingFace, TensorFlow, scikit-learn, pandas, PyTorch, and Keras
• Experience with relational, non-relational, and high-scale data processing/storage frameworks (SQL, AWS Redshift, Aurora, S3, DynamoDB, MySQL, PostgreSQL)
• Experience with AWS Serverless architecture and native services such as Bedrock, EC2, Lambda, Step Functions, SageMaker, Rekognition, Comprehend, Lex/Polly, and Transcribe

Technologies

• Python
• Amazon Web Services (AWS)
• LangChain
• HuggingFace
• TensorFlow
• scikit-learn
• pandas
• PyTorch
• Keras
• SQL
• AWS Redshift
• AWS Aurora
• AWS S3
• DynamoDB
• MySQL
• PostgreSQL
• AWS Bedrock
• EC2
• Lambda
• Step Functions
• SageMaker
• Rekognition
• Comprehend
• Lex
• Polly
• Transcribe

Role details

• Location: Irvine, CA, onsite
• Job type: Full-time
• Salary: USD 122,000 - 160,000 per year
• Education: Master’s degree required
• Experience: Minimum three years required
• Work location: In person

Application questions

• How many years of experience do you have with Amazon Bedrock?
• Do you have experience deploying Machine Learning models from end to end?
• Do you have experience with serverless deployment?
• Will you now, or in the future, require sponsorship for employment visa status (e.g., H-1B visa status)?

Experience

• Amazon SageMaker: 2 years (Required)
• Python: 2 years (Required)