AWS-native HPC and data platforms for life sciences research
Clovertex builds high-performance computing and data infrastructure on AWS for biotech and pharma R&D teams. The stack reveals a working ML/analytics shop—TensorFlow, PyTorch, SageMaker, Hugging Face—actively adopting generative AI tooling (Bedrock, Textract) alongside container orchestration (EKS, Kubernetes). Project velocity is split between AI/ML expansion in life sciences and cloud-native HPC environment design, while hiring friction (candidate pipeline gaps, high-growth demand) suggests they're scaling faster than recruiting can keep pace.
Clovertex specializes in migrating and building scientific computing platforms for biotech and pharmaceutical companies on AWS. The company supports established research applications—Single Cell Sequencing, GROMACS, NAMD, ANSYS, RELION, cryo-EM, cryoSPARC, NONMEM—and manages large-scale data lakes, warehouses, and ML frameworks. They operate on a services model, advising customers on optimal price-performance tradeoffs between all-cloud and hybrid architectures. Founded in 2018 and based in Boston, the company employs 51–200 people with an engineering-heavy hiring focus and active recruiting in India.
AWS (core), Kubernetes/EKS, Docker, TensorFlow, PyTorch, Hugging Face Transformers, SageMaker, Python, C++, Terraform, and Slurm for workload scheduling. Currently adopting SageMaker Studio, Bedrock, and Step Functions.
Builds AWS HPC and data platforms for biotech/pharma research. Services include cloud migration for scientific computing applications, data lake design, ML frameworks, and cost/performance optimization on AWS.
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