What are the responsibilities and job description for the Sr. ML Ops Engineer position at Deep 6 AI?
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. 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.
- 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
- 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
Salary : $160,000 - $190,000