Artificial Intelligence Engineer

Job Title

"LLM Engineer at Qure.ai, based out of Bengaluru - Full-Time Role"

Company Details

Qure.AI is an applied healthcare AI company solving high stakes problems in global healthcare. With 18 FDA and 62 CE marking clearances to date, we create innovative solutions that significantly improve patient outcomes across various care domains, including lung cancer, tuberculosis, and stroke, impacting ~15 million patients annually in over 100 countries.

Our teams are empowered by a strong infrastructure, state-of-the-art tools, and resources, enabling them to tackle real-world problems efficiently. Each contribution you make becomes part of a global diagnostic network, influencing the lives of over 32 million people.

At Qure AI, we are dedicated to cultivating a diverse and inclusive environment and take pride in being an equal-opportunity employer.

Job Roles & Responsibilities

- Develop and deploy scalable AI applications using AWS and GCP to enhance healthcare solutions.

- Implement and optimize large language models (LLMs), focusing on tasks like Retrieval-Augmented Generation (RAG) and multimodal prompting.

- Integrate OpenAI and Anthropic Claude tools into existing healthcare frameworks for improved diagnostic accuracy.

- Collaborate on open-source projects to innovate health tech solutions.

- Use Docker and LangChain for efficient AI model deployment and management.

- Work closely with cross-functional teams to deliver accessible AI-driven healthcare solutions, ensuring they meet technical and clinical requirements.

Cultural Expectations

- Collaborate in a diverse team, promoting inclusivity and open-mindedness

- Proactively innovate and think outside the box for AI solutions

- Passion for advancing healthcare accessibility

- Adapt and respond to dynamic challenges with a solutions-oriented mindset

- Commit to lifelong learning and sharing knowledge within the team

Hiring Process

- Technical assignment tailored for the role.

- Interview with hiring manager to assess technical skills.

- Live coding task to evaluate coding proficiency.

- Technical interview with senior member from the technical team.

- Final interview with Tech Lead/CTO