Machine Learning Engineer, Applied AI

Role Overview

• 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.

Tech Stack

• AWS
• Cloud
• Python

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)