Jecona
We are partnering with an AI software platform company that is dedicated to addressing the critical challenges associated with healthcare administration, allowing providers to focus their energy on delivering high-quality patient care. Its solution delivers AI teammates for every patient touch-point to better empower providers and engage patients.
They cannot provide sponsorship. This role is hybrid from Sunnyvale and can go up to 250k in base with an additional 150-250k in equity for a total compensation of 500k.
Responsibilities
Design and deploy production-grade systems that integrate machine learning models into scalable pipelines. Develop features that leverage ML to solve real-world optimization and prediction problems, working with modern infrastructure. Approach problems with a software engineer’s mindset—prioritizing robustness, maintainability, and performance at scale. What We Value
6+ years of overall machine learning experience Proficiency in Python, including FASTAPI server coding and core Python libraries Experience with production ML tooling and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Familiarity with LLM operations, LLM APIs, tool use, agentic AI, evaluations, and simulation Strong understanding of data structures, algorithms, and software engineering best practices Familiarity with classical ML, deep learning, and MLOps concepts Experience building and maintaining scalable, reliable systems that include ML components A bias for simplicity and clarity in solving complex problems Intellectual curiosity and willingness to collaborate Clear communication and collaboration across cross-functional teams
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Design and deploy production-grade systems that integrate machine learning models into scalable pipelines. Develop features that leverage ML to solve real-world optimization and prediction problems, working with modern infrastructure. Approach problems with a software engineer’s mindset—prioritizing robustness, maintainability, and performance at scale. What We Value
6+ years of overall machine learning experience Proficiency in Python, including FASTAPI server coding and core Python libraries Experience with production ML tooling and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Familiarity with LLM operations, LLM APIs, tool use, agentic AI, evaluations, and simulation Strong understanding of data structures, algorithms, and software engineering best practices Familiarity with classical ML, deep learning, and MLOps concepts Experience building and maintaining scalable, reliable systems that include ML components A bias for simplicity and clarity in solving complex problems Intellectual curiosity and willingness to collaborate Clear communication and collaboration across cross-functional teams
#J-18808-Ljbffr