Designing, developing, and implementing machine learning models and algorithms at PayPal. Collaborating with data scientists and software engineers to enhance services through innovative AI/ML solutions.
About the role
- Machine Learning Engineer developing AI workflows for healthcare tech company. Collaborating on product features and data-driven innovations to improve clinician efficiency and care quality.
Responsibilities
- Develop AI workflows, customize data pipelines, tune models, and engineer prompts to bring idea to prototype
- Work with subject matter experts to set up evaluation for AI workflows, ensuring rigor, quality and safety of content output
- Work with eng partners to integrate AI workflows into production
- Build and configure AI performance monitoring with proper reporting and alerts
- Optimize and maintain AI workflows for performance, reliability, and long-term scalability
- Start with the Job-to-be-done, dive deep into the domain and understand the problem from user perspective
- Decompose problems into conquerable pieces. Design solutions to address each with cross-disciplinary thinking and big picture in mind.
- Conduct exploratory data analysis to answer key questions and test assumptions. Design experiments and build prototypes for proof-of-concept.
- Build artifacts to illustrate the findings with rigor and how they inform the roadmap and decisions
- Provide AI expert advice to product and eng partners in shaping product roadmap
- Partner closely with software eng, product, data eng, ML platform teams to scope and plan in execution
- Communicate timeline, milestones, findings w/ internal stakeholders
- Guide less experienced team members, sharing knowledge on LLM workflows and AI/ML model lifecycle
- Champion a culture of experimentation, continuous learning, and proactive problem-solving
- Stay current with emerging ML tools and technologies, integrating new techniques that elevate our product capabilities
- Look for creative ways to leverage data to make clinicians’ lives easier, more efficient, and more effective
Requirements
- BS or above in Computer Science, Statistics or a related technical field
- 5+ years of experience in Machine Learning, with proven track record of bringing ideas to life, from prototype to productized features
- Strong proficiency in Python and hands-on with advanced data analysis tools
- Strong skills in data engineering and self-sufficient in data pipelines for the AI workflow
- Experience with AWS (or other cloud platforms) for model deployment
- Comfortable designing and evaluating LLM-driven workflows
- Familiarity with retrieval pipelines and vector databases
- Problem-oriented mindset with strong cross-disciplinary thinking and a bias toward simplicity and clarity in solving problems
- Comfortable working with remote teams, using GitHub, Slack, Notion, and Zoom
- Proficiency in English with strong communication and collaboration skill.
Benefits
- Privatized Medical, Dental & Vision Coverage
- Work From Home stipend
- Flexible Time Off (FTO), wellbeing days, paid holidays, and Summer Fridays
- Monthly Meal Reimbursement
- Holiday Bonus, 15-day Aguinaldo
- Hybrid Work Schedule & Catered Lunch
- A relocation bonus for candidates joining us from a different city
- Employee Resource Groups (ERGs)
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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