Applied AI Engineer, Life Sciences

synthio-labs; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Synthio is seeking an Applied AI Engineer who blends strong AI engineering skills with a deep understanding of life sciences. The role involves building AI systems across HCP, patient, medical, and commercial workflows with an emphasis on reliability and domain context.

You will work with pharma datasets, prototype rapidly, and collaborate with domain experts to translate complex workflows into robust technical solutions. Strong Python, LLMs, and ownership are essential.

Qualifications

• 3+ years of experience in AI/ML, applied machine learning, or software engineering.
• Strong Python skills and experience building production AI systems.
• Hands-on experience with LLMs, embeddings, retrieval, agentic workflows, or related applied AI systems.
• Prior experience working directly with pharmaceutical companies, pharma teams, or life sciences products.
• Strong fundamentals in experimentation, evaluation, and debugging AI systems.
• Excellent communication with technical and non-technical stakeholders.
• High ownership and comfort solving ambiguous problems.

Responsibilities

• Build production-grade applications using LLMs, retrieval, agents, structured data, and multimodal AI.
• Design AI workflows across pharmaceutical commercial, medical, and patient use cases.
• Build retrieval and knowledge systems over scientific, medical, and enterprise data.
• Develop evaluation frameworks for accuracy, reliability, safety, and domain-specific failure modes.
• Work with pharma datasets including CRM, claims, sales, HCP, patient, clinical, and scientific data.
• Prototype quickly, evaluate approaches rigorously, and productionize what works.
• Work directly with domain experts and customers to translate complex workflows into technical solutions

Skills

AI/ML

Python

LLMs

Retrieval

Embeddings

Pharma experience

Experimentation

Communication

Ownership

Job description

About the Role

Synthio is looking for an Applied AI Engineer who combines strong AI engineering skills with a deep understanding of life sciences. Prior experience working directly with pharmaceutical companies, pharma teams, or life sciences products is required. You will build AI systems across HCP, patient, medical, and commercial workflows, working on problems where scientific accuracy, reliability, and domain context matter

What You’ll Do

• Build production-grade applications using LLMs, retrieval, agents, structured data, and multimodal AI.
• Design AI workflows across pharmaceutical commercial, medical, and patient use cases.
• Build retrieval and knowledge systems over scientific, medical, and enterprise data.
• Develop evaluation frameworks for accuracy, reliability, safety, and domain-specific failure modes.
• Work with pharma datasets including CRM, claims, sales, HCP, patient, clinical, and scientific data.
• Prototype quickly, evaluate approaches rigorously, and productionize what works.
• Work directly with domain experts and customers to translate complex workflows into technical solutions

What We’re Looking For

• 3+ years of experience in AI/ML, applied machine learning, or software engineering.
• Strong Python skills and experience building production AI systems.
• Hands-on experience with LLMs, embeddings, retrieval, agentic workflows, or related applied AI systems.
• Prior experience working directly with pharmaceutical companies, pharma teams, or life sciences products.
• Strong fundamentals in experimentation, evaluation, and debugging AI systems.
• Excellent communication with technical and non-technical stakeholders.
• High ownership and comfort solving ambiguous problems.

Why This Role Matters

At Synthio, we build software that directly supports patients, physicians, and pharma teams. This is production software, not prototypes or demos. The systems you build will be used in real workflows, under real constraints, and at real scale. You’ll have meaningful ownership and a clear line of sight from your code to real-world impact.

Strong Plus

• Pharma commercial, medical affairs, patient services, clinical, or market access experience.
• Experience with healthcare datasets, scientific literature, or medical knowledge systems.
• Experience with voice AI, speech systems, or regulated AI deployments