Applied AI Engineer, Life Sciences
Salary not listed • Remote • India - Remote • Full-time
Posted 1mo ago
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
AI Engineer
About the job
Synthio is seeking an Applied AI Engineer with a strong blend of AI engineering expertise and a deep understanding of the life sciences domain. This role is crucial for building next-generation conversational voice and video AI solutions tailored for the life sciences industry, ensuring 100% regulatory compliance. You will develop AI systems for healthcare professional (HCP), patient, medical, and commercial workflows, focusing on areas where scientific accuracy, reliability, and domain context are paramount. This is an opportunity to contribute to a fast-scaling, early-stage startup, shaping not only the product but also the company's identity and culture.
Responsibilities
- Build production-grade applications leveraging LLMs, retrieval, agents, structured data, and multimodal AI.
- Design AI workflows for pharmaceutical commercial, medical, and patient use cases.
- Develop retrieval and knowledge systems for scientific, medical, and enterprise data.
- Create evaluation frameworks to assess accuracy, reliability, safety, and domain-specific failure modes.
- Work with diverse pharma datasets including CRM, claims, sales, HCP, patient, clinical, and scientific data.
- Prototype rapidly, rigorously evaluate different approaches, and productionize successful solutions.
- Collaborate directly with domain experts and customers to translate complex workflows into technical solutions.
Requirements
- 3+ years of experience in AI/ML, applied machine learning, or software engineering.
- Strong Python skills and proven experience building production AI systems.
- Hands-on experience with LLMs, embeddings, retrieval, agentic workflows, or similar applied AI systems.
- Prior experience working directly with pharmaceutical companies, pharma teams, or life sciences products.
- Solid fundamentals in AI system experimentation, evaluation, and debugging.
- Excellent communication skills for interacting with both technical and non-technical stakeholders.
- High sense of ownership and comfort in solving ambiguous problems.