Staff Machine Learning Engineer
New
C
Cohere HealthClinical Intelligence
United StatesFull-TimeStaff
Salary225,000 - 240,000 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- AWSPythonPyTorchData scienceDeep LearningNLP
Requirements
- Master’s degree (PhD preferred) in Computer Science, Data Science, Machine Learning, or a closely related quantitative field.
- 8+ years of professional experience in applied machine learning or data science, including ownership of production ML systems.
- Deep expertise in Python and modern deep learning frameworks (e.g., PyTorch).
- Hands-on experience building and deploying deep learning models (e.g., transformers) for NLP tasks.
- Strong understanding of experimental design, model evaluation, and optimization for real-world production environments.
- Experience leveraging cloud platforms (AWS preferred) across the ML lifecycle (training, deployment, monitoring).
- Proven ability to collaborate with product, business, and clinical partners to drive data-informed decision-making.
- Excellent written and verbal communication skills, with experience presenting to both technical and non-technical audiences.
Responsibilities
- Design, build, and deploy advanced machine learning systems for retrieval, classification, prediction, and generative use cases.
- Apply advanced statistical and ML techniques to extract insights from large-scale structured and unstructured healthcare datasets.
- Lead model development across the ML lifecycle, including experimentation, training, evaluation, deployment, monitoring, and iteration.
- Develop and oversee scalable, reusable codebases and ML infrastructure to support production use cases.
- Collaborate cross-functionally with product managers, clinicians, data engineers, BI engineers, and design teams to translate business and clinical needs into robust ML solutions.
- Drive experimentation by defining problem statements, forming falsifiable hypotheses, and designing rigorous evaluation frameworks tied to business outcomes.
- Review, communicate, and present ML insights and results to technical and non-technical stakeholders, including executive leadership.
- Serve as a technical mentor and advisor to junior engineers, providing guidance on ML best practices, experimentation, and system design.
- Contribute as an expert advisor across multiple initiatives, helping shape ML strategy and performance tracking across the organization.
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