Applied AI Engineer
Core
Senior Applied AI Engineer translating cutting-edge AI research into real scientific and business impact for drug discovery and personalized medicines.
Role type
Senior hands-on IC Applied AI Engineer
Builds
Production-ready ML models, agentic AI systems, multi-agent architectures, and LLM-based tools for scientific domains.
Domain
Biopharma / Drug Discovery / Life Sciences
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, JAX, scikit-learn, pandas, numpy, GCP/AWS/Azure, Docker, Kubernetes, supervised/unsupervised learning, deep learning, feature engineering, experiment tracking, healthcare/pharma domain knowledge
Preferred skills
LLM-based applications, agentic AI systems, RAG pipelines, multi-agent architectures, knowledge graph construction, causal inference, single-cell RNA-seq, spatial transcriptomics, CRISPR assay data, MLOps, CI/CD for ML, model monitoring, MLflow, Weights & Biases, Git/GitHub, third-party AI/ML vendor tools integration
Technologies
LangChain, LangGraph, AutoGen, MLflow, Weights & Biases, GCP, AWS, Azure, Docker, Kubernetes, PyTorch, TensorFlow, JAX, scikit-learn, pandas, numpy
Responsibilities
Evaluate use-case feasibility and prototype solutions rapidly; Build, train, evaluate, and iterate on ML models for scientific problems; Package trained models into production-ready services; Run workshops and training sessions to increase AI literacy; Embed within business/research units for time-limited engagements to transfer skills
Seniority
Senior, hands-on IC
