Cohere Health is looking to improve lives at scale by promoting the best patient-specific care options using cutting-edge AI combined with deep clinical expertise.
Requirements
- 5+ years of experience in MLOps, ML Engineering, or related roles
- Proven track record of deploying and managing large-scale machine learning models, especially LLMs
- Deep expertise in programming languages such as Python
- Extensive experience with ML frameworks like TensorFlow or PyTorch
- Experience with cloud platforms (AWS preferred, GCP, or Azure) and containerization technologies (Docker, Kubernetes)
- Strong understanding of CI/CD pipelines, automation tools, and infrastructure as code
- Familiarity with big data technologies (Spark, Hadoop) and distributed computing
Responsibilities
- Define and implement the overall MLOps strategy to support the deployment and scaling of ML models
- Lead the architectural design of ML infrastructure, ensuring scalability, reliability, and efficiency
- Oversee the deployment, scaling, and optimization of LLMs
- Develop strategies to reduce latency and manage costs effectively
- Lead the development and improvement of core technology components and system architecture
- Architect and build automated ML pipelines, including data preprocessing, model training, and deployment
- Establish monitoring systems to track model performance, data drift, and system health
Other
- Master's or Ph.D. (preferred) in Computer Science, Engineering, or a related field
- Exceptional problem-solving skills and the ability to navigate complex technical challenges
- Proven leadership skills with experience in mentoring and team development
- Excellent communication skills with the ability to convey complex concepts to non-technical stakeholders
- Experience in the healthcare sector
