Designing and operating cloud - based MLOps capabilities supporting analytical and generative AI models. Collaborating with data science and business teams for high - impact AI solutions.
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Hybrid ML Engineer – Early Career, Mid Career
Posted 5 months ago
About the role
- Machine Learning Engineer designing AI automation for healthcare at Infinitus. Mentoring engineers and blending ML, deep learning, and LLM for scalability and performance.
Responsibilities
- Apply **strategic AI thinking** to solution development.
- **Mentor, guide, and influence** teams of engineers.
- Engage in **hands-on, impactful work** that directly benefits customers and the business.
- Blend **traditional machine learning, deep learning, and large language models (LLMs)** to maximize performance and scalability.
Requirements
- 5+ years of hands-on engineering experience, with demonstrated growth.
- 2+ years of experience working in applied ML or NLP in practical, industry settings.
- Experience building and scaling end to end ML models and pipelines in production environments.
- Demonstrated ability to drive projects from concept through completion.
- Expertise in Python.
- Strong communication skills.
- Undergrad, Masters, or equivalent coursework in ML or NLP.
- A curiosity to continue to learn and stay up to date on machine learning, engineering and infrastructure technologies.
Benefits
- Competitive salary, equity, and 401(k)
- Wellness stipend & great benefits (medical, dental, vision)
- Generous PTO & parental leave
- Bi-annual offsites & a collaborative, mission-driven culture
- Hybrid work (SF office Mon/Tues/Thurs) + catered lunches (*Bay Area Positions only)
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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