Curai Health is an AI-powered virtual clinic on a mission to improve access to care at scale. As the pioneer in deploying machine learning into clinical workflows, Curai Health enables its dedicated, specially trained clinicians to deliver primary care to more people at a fraction of the cost. Easy-to-use and convenient, Curai Health partners with insurers and health systems to keep patients engaged in their care over time, improving health outcomes and reducing costs. Our company is remote-first and we consider candidates across the United States. Our corporate office is located in San Francisco. Machine Learning Engineering at Curai We are looking for a ML Engineer to join our AI team. Our team is responsible for Curai’s ML/automation technology. Your work will have a tremendous direct impact on provider and patient-facing ML-augmented applications, thereby providing low-friction, high-quality care to patients of Curai Health. We are primarily a text-based service and NLP is at the core of our ML work. With recent advances in large language models, we see a tremendous acceleration in capabilities. A non-trivial part of our work involves appropriately leveraging and building on top of these models thoughtfully (and with scaffolding) to our use cases and backing them up with a sound automated evaluation. In addition, we use the in-house deidentified data as robust feedback data for continuously improving the ML models. Who You Are
- A self-starter and have a growth mindset
- Enjoy tackling complex problems in a scientific and data-driven way
- Thrive in ambiguity and love tackling complex problems that span multiple systems
- Enjoy thinking through trade-offs with mindfulness of near-term needs and Curai’s long-term strategy
- Are collaborative and appreciate working with people with diverse expertise
What You’ll Do
- Develop and improve our AI systems used in our patient and physician-facing product features in collaboration with our product, clinical, engineering, and design teams. Includes fine-tuning large language models, developing model evaluations, and dealing with hard engineering constraints like latency and expensive model inference,
- Design offline and online evaluations to test ML product features, and perform data-driven analysis of the results to find actionable insights.
- Enable rapid and rigorous scientific innovation by a multidisciplinary team of Curai clinicians, engineers, and researchers, through platform, tools, and documentation.
- Interview diverse talent to build and grow a strong ML team.
What You’ll Need
- 2+ years of industry experience in ML/NLP including building production systems.
- “End-to-end” experience building ML production systems: Along with strong ML fundamentals, you will need exposure to the entire lifecycle of machine learning production systems, such as data processing, modeling, deployment, monitoring, maintenance, and improving the models over time using feedback loops.
- “Product sense” or intuition on what to build: With guidance, you will need to be able to translate product intuition into data-driven hypotheses that result in impactful machine learning/engineering solutions.
- Strong communication skills: This role involves collaboration with product, engineering, clinical, and research teams. Understanding the mental models of the audience and communicating ideas crisply to this diverse set of stakeholders will be a vital part of the role. • You should be comfortable leading cross-functional machine learning product initiatives, from conception to successful product outcomes.
Our interview process typically consists of an initial call to meet your future manager and a technical phone call with two future teammates. The next round is a series of four technical phone calls where you meet cross-functional partners and other teammates at the company. These interviews are set up in such a way as to allow you to learn more about us (mission, product, company culture, and vision) and for us to know more about you (your superpowers and strengths). We tailor our interview process to your background and interests. What We Offer
- Culture: Mission-driven talent with great colleagues committed to living our values, collaborating, and driving performance
- Pay: Competitive compensation and stock
- Wellness: Unlimited PTO, flexible working hours and remote working options
- Benefits: Excellent medical, dental, vision, flex spending plans, and paid parental leave
- Financial: 401k plan with employer matching
The annual base salary range for this position is between $150,000 – $200,000. annually. Stock grants also play a key part in any offer, they increase your overall compensation package significantly based on company success. Please note that the base salary range is a guideline, and individual total compensation will vary based on qualifications, skill level, competencies, and work location. Curai Health is a startup with a small but world-class team from high-tech companies, AI researchers, and practicing physicians to team members from non-traditional career paths and backgrounds. We also have research partnerships with leading universities across the country and access to medical data that facilitates research in this space. We are a highly collaborative, data-driven team, focused on delivering our mission with funding from top-tier Silicon Valley investors, including Morningside, General Catalyst, and Khosla Ventures. At Curai Health, we are highly committed to building a diverse and inclusive environment. In keeping with our beliefs and values, no employee or applicant will face discrimination or harassment based on race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. To promote an equitable and bias-free workplace, we set competitive compensation packages for each position and do not negotiate on our offers. We are looking for mission-driven teammates, who embody our core values, and appreciate our transparent approach. #J-18808-Ljbffr
conducting interviews Natural language processing (NLP) Artificial intelligence (AI) performance medical Production environments Maintenance modeling Communication Collaboration Machine Learning monitoring data-processing vision deployment Stock market Engineering