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Synthio Labs

Applied AI Engineer, Life Sciences

Posted 7 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in India
Mid level
Remote
Hiring Remotely in India
Mid level
Build production-grade AI applications for pharmaceutical commercial, medical, and patient workflows using LLMs, retrieval, agents, structured data, and multimodal AI. Develop scientific knowledge systems, evaluation frameworks, and reliable, safe AI solutions using healthcare and life sciences datasets. Collaborate with pharma customers and domain experts to translate complex workflows into scalable technical products.
The summary above was generated by AI
We’re building the next generation of conversational voice and video AI for life sciences—intelligent with 100% regulatory compliance. Our AI medical experts help pharma teams engage doctors, support patients, and unlock insights faster than ever before. We’ve just raised our seed, signed our first customers, and are scaling fast. If you're excited about building real-world AI in an early stage startup and shape not just our product, but our identity and culture —this is your moment.

We move like owners. Everyone at SynthioLabs has the autonomy and the responsibility to drive projects, challenge decisions, and push things forward. We don’t wait for permission. If you see a gap, you fill it. If you see a better way, you try it.

We ask “why” until we get to the root. We explore new ideas, research papers, every single edge case and anything that sharpens our understanding.

We use AI like a second brain. From writing code to writing docs, debugging flows to exploring new ideas, AI is part of our daily rhythm. Everyone here gets hands-on with the tools, learns how to prompt better, and treats AI as a teammate.

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

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