At Evidently, we are changing the way doctors work with patients by giving them the tools to better understand patients' history, symptoms, and data. We have a unique Cognitive AI platform, a strong engineering & design team, and an awesome product.
Learn more about Evidently at our website: evidently.com
Who We’re Looking For
We are looking for an experienced machine learning engineer who can design/implement core components powering our healthcare applications and improve the quality and performance of our Cognitive AI platform.
Who You’ll Work With
You will join a small yet mighty team, working closely with a handful of fellow software engineers on data, application backend/frontend, that shares the goal of delivering the power of Cognitive AI technology to our users by building great products.
You will work directly with domain experts (medical doctors) to deepen the understanding of the users’ needs/problems to shape the direction of our Cognitive AI platform’s development.
Some of the team meets in person in Palo Alto, CA once a week, but we mainly work remotely. Relocating is not required but recommended. You must be able to work during the Pacific Time work hours. For compliance reasons, we cannot employ you outside the United States.
What You'll Do
- Build clinical/health information extractors, summarizers, directly powering our end-user products, and improve their quality/performance.
- Lead and drive the co-development of core components in our Cognitive AI platform with software engineers.
- Build/improve supporting data/ML systems and automations.
- Mine structured/unstructured datasets to expand/refine knowledge graph.
- A healthy mix of software engineering, ML/NLP engineering, and data analytics/engineering.
- Develop and deploy secure code, and maintain confidentiality, integrity, and availability of the information systems and processes in compliance with our information security and privacy policies, including HIPAA and SOC 2.
What You'll Bring
- 4+ years of experience and knowledge in machine learning software engineering.
- Fluent Python, SQL, Gsheets, Notebook/Streamlit, Git workflow.
- Actionable knowledge and experience in the state of the art NLP techniques and libraries.
- Experience in Deep Learning frameworks, such as Tensorflow or PyTorch.
- Excellent data munging/wrangling/exploration/analysis skills.
- Rigor in assessing data and system quality.
- Ability to design/implement efficient algorithms.
- Good taste in data model and software API design.
- Clear documentation/presentation skills to articulate complex ideas and results.
- Open and responsive communication with your cross-functional team members.
Bonus Points
- Understanding of data curation/annotation process and best practices.
- Experience in building/using tooling for ML workflows.
- Experience in building, deploying, maintaining ML models (ML Ops).
- Resourceful with Google Cloud services and Linux systems, scaling compute.
- Backend/full-stack software engineering (familiar with Django, GraphQL, React).
- Familiar with health and biomedical domains.
