Senior Machine Learning Operations Engineer

Summary

Join a fast-growing tech startup in Los Angeles, California, as we transform clinical trials with groundbreaking artificial intelligence platform.

Requirements

• Deep knowledge of traditional ML concepts (e.g., LSTMs, RNNs, GMMs, SVMs, trees, boosting) as well as more recent deep learning fundamentals and NLP-related experience with word embeddings
• Proficiency in JVM languages
• Familiarity with CI/CD tools and methodologies
• Proficiency with containerization (e.g., Docker) and orchestration tools
• Experience with cloud-based ML platforms (e.g., Amazon Sagemaker)
• Experience with common JVM search, linguistics, and other language frameworks (e.g., Lucene, StanfordNLP, OpenNLP, SparkNLP, ANTLR)
• Experience using a Deep Learning Framework (e.g., Tensorflow, PyTorch, Keras)
• Mature theoretical grasp of different neural networks on large-scale datasets
• Deep and Fundamental understanding in signal processing concepts
• A positive, collaborative, can-do attitude and a strong sense of ownership
• Familiarity with clinical data, concepts and language
• Experience in model training automation with a combination of Supervised, Unsupervised, and Reinforcement methods

Responsibilities

• Develop and Maintain ML Pipelines: Design, implement, and manage scalable machine learning pipelines to support various ML models from development to production
• Automate Workflows: Create automated workflows for data preprocessing, model training, evaluation, and deployment
• Monitor and Optimize: Continuously monitor the performance of ML models in production, ensuring they meet performance and accuracy standards. Optimize models and pipelines for efficiency
• Collaborate with Teams: Work closely with data scientists, software engineers, and other stakeholders to integrate ML solutions into existing systems and applications
• Ensure Compliance and Security: Implement best practices for data security and compliance, ensuring that all ML operations adhere to relevant regulations and standards
• Documentation and Reporting: Maintain comprehensive documentation of ML processes, workflows, and systems. Provide regular reports on model performance and system health

Preferred Qualifications

• Prior remote working experience
• Worked in the healthcare domain. Experience with healthcare clinical data modeling a strong bonus (e.g., OMOP, FHIR)
• Experience with Transfer Learning, Transformers (e.g., BERT & ELMO), and Multilingual NLP

Benefits

• Competitive salary
• Unique opportunity to thrive at a growing company
• Employer-paid medical, dental, vision, life insurance and long-term disability coverage
• 401k plan
• Generous PTO plan which includes sick and vacation days