Machine Learning Engineer

Location: Palo Alto, CA (Strongly Preferred) or Remote

Level: Staff & Senior

About the Organization

This company is pioneering a new frontier by building the world's first safety-focused Large Language Model specifically designed for healthcare. The mission is audacious: to radically expand global access to high-quality healthcare and improve patient outcomes by democratizing deep medical expertise. The work at the intersection of cutting-edge AI and human health represents a generational opportunity for technological and societal impact.

Founded by a coalition of leading physicians, hospital administrators, and AI researchers from top-tier institutions and technology companies, the organization is built on a foundation of real-world clinical wisdom. This ensures that safety and efficacy are engineered into the product from the ground up. With significant backing from premier venture capital firms and strategic health systems, the company is equipped with the resources, network, and credibility to achieve its ambitious goals.

The culture is built on rigorous collaboration and a shared commitment to building technology that matters.

Overview of the Role

Machine Learning Engineers are the cornerstone of our efforts to design, deploy, and optimize the advanced ML systems that power our safety-first generative AI platform. In this role, you will bridge the gap between foundational research and real-world product application, building the scalable infrastructure and models that enable robust, real-time conversational AI for healthcare.

This is a strategic, hands-on leadership role, ideal for an expert who is passionate about solving complex technical challenges and driving the productionization of models that will directly influence healthcare delivery and patient care on a global scale.

The Technical Challenges You Will Tackle

1. Architecting and implementing scalable, high-performance infrastructure for the training, fine-tuning, and inference of large-scale models.
2. Building robust ML pipelines and developer tooling that accelerate experimentation, rigorous evaluation, and reliable deployment.
3. Optimizing model latency, throughput, and computational efficiency in production environments.
4. Collaborating cross-functionally with research, product, and engineering teams to integrate sophisticated ML solutions into user-facing applications.
5. Upholding the highest standards of safety, privacy, and reliability required for healthcare applications.

Required Qualifications

1. A Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field; a PhD is advantageous.
2. 7+ years of industry experience building, deploying, and maintaining production-grade machine learning systems, with a significant focus on LLMs or other deep learning architectures.
3. Strong software engineering fundamentals and proficiency in Python.
4. Deep, hands-on experience with ML frameworks such as PyTorch or TensorFlow.
5. Familiarity with distributed training techniques and frameworks (e.g., DeepSpeed, Fully Sharded Data Parallel, Horovod).
6. A proven track record of designing, implementing, and scaling ML pipelines for large-scale models.
7. Experience with major cloud platforms (AWS, GCP, or Azure) and container orchestration technologies like Kubernetes and Docker.
8. Exposure to healthcare, clinical, or life sciences data is a significant plus.

Your Impact

As a ML Engineer, you will have a central voice in technical decision-making and architectural direction. You will partner closely with research and product leadership to define the roadmap for scalable, safe, and impactful ML systems. This role offers a unique opportunity to be at the heart of a world-class team that is shaping the future of AI in healthcare, with your contributions directly affecting the well-being of millions.