Sr. ML Ops Engineer

Deep 6 AI is a fast-growing tech startup headquartered in Los Angeles, California looking for talented, dynamic team members who want to help shape our groundbreaking artificial intelligence platform. We are transforming and accelerating clinical trials, to help get life-saving treatments to patients faster and accelerate innovation in healthcare. To that end, we build a cutting-edge software suite that connects all clinical research stakeholders, from research teams to treating physicians, patients, and study sponsors on a real-time, real-world data SaaS platform, powered by AI.

What You'll Do

• 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.

About You

• 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

Bonus Points

• 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
• Familiarity with performance and load testing automation tools (e.g., Gatling, K6, Jmeter) and methodologies