Radical Numerics

Radical Numerics

Member of Technical Staff, ML Product Engineer

San Francisco · Staff+

Sponsorship not specified$26k-$42kDetected 19 days ago
PythonDistributed SystemsMachine LearningNLPLLMsBioinformaticsCRISPRResearch

About the role

  • This role sits close to our product and data-partnership functions and our modeling team.
  • As a Member of Technical Staff, ML Product

Responsibilities

  • Design the compute and orchestration layer: job queues, autoscaling GPU inference, retries, fault tolerance, and the observability to run all of it against real SLAs.
  • Build the developer-facing product: the API surface, SDKs, and documentation that let an outside team depend on Omnii without hand-holding.
  • Drive down cost and latency per inference, and make performance predictable enough to price and guarantee.
  • Work directly with our scientists and partners to shape the API around real inference workloads.
  • You would build for our scientists and for the partners and developers who build on Omnii, our next-generation genome language model.
  • You translate between what the science needs, what partners can consume, and what the infrastructure can deliver.

Requirements

  • You have built and operated backend or distributed systems at production scale, and you owned their reliability.
  • You have shipped a model as a service that other people depended on.
  • You have built asynchronous or batch job systems at scale.
  • You write production code in Python and at least one typed language, and you are comfortable with containers and infrastructure as code.
  • You have product judgment.
  • You can decide what to expose, what to hide, and how an API should feel to the person calling it.
  • You care about throughput, latency, cost, and uptime, and you have real opinions about what a good developer experience feels like.

Nice to have

  • GPU inference internals: vLLM, TensorRT-LLM, or Triton, with hands-on performance tuning.
  • Experience deploying software into locked-down environments such as enterprise VPC, on-prem, or air-gapped.
  • Familiarity with genomics or computational biology, or a real appetite to learn it fast.
  • Experience standing up an external API product from the first endpoint forward.
  • It also prohibits unlawful discrimination based on the perception that anyone has any of those characteristics, or is associated with a person who has or is perceived as having any of those characteristics.
  • Radical Numerics participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
  • real-time serving plus large batch scoring for genome- and variant-scale workloads, where a single job can be millions of sequences, latency-tolerant and cost-sensitive.

Compensation

  • $26k-$42k

Benefits

  • The platform you build is how Omnii reaches the people using it to advance human health and biosecurity.
  • Package the platform to run inside partner environments that cannot let data leave, including on-prem and air-gapped installs.

Company info

  • Radical Numerics http://radicalnumerics.ai is an AI research lab building general biological intelligence. Our mission is to master the code of life, and our purpose is to reduce human suffering.
  • Our team created Evo, and started the field of generative genomics. Our work was featured on the cover of Science https://www.science.org/doi/10.1126/science.ado9336, and presented by our CEO on the main stage of TED2025 https://www.youtube.com/watch?v=EnbfoFUFm2s. Evo was used to create the first AI gene therapy tool CRISPR-Cas9, and the first AI whole genome https://www.biorxiv.org/content/10.1101/2025.09.12.675911v1 from scratch. Evo 2 https://www.nature.com/articles/s41586-026-10176-5, featured in Nature, is the largest fully open source AI project across any domain.
  • Radical Numerics is bringing the rigor of distributed systems, model architecture, and numerics research to the challenges of biology. We've redesigned the foundation model training stack to turn the world's raw scientific data (e.g. biological sequences, experiments, and physical processes), into intelligible, generative models that can expand and accelerate what humanity can understand, design, and cure.
  • The same generative breakthroughs that enable life-saving cures also lowers the barrier to creating engineered threats and AI-generated bioweapons. We believe these forces are inseparable. Radical Numerics was founded to develop both the power to design and the responsibility to defend.
  • Radical Numerics http://radicalnumerics.ai is an AI research lab building general biological intelligence.
  • Our mission is to master the code of life, and our purpose is to reduce human suffering.
  • Our team created Evo, and started the field of generative genomics.
  • Our work was featured on the cover of Science https://www.science.org/doi/10.1126/science.ado9336, and presented by our CEO on the main stage of TED2025 https://www.youtube.com/watch?v=EnbfoFUFm2s.
  • Evo was used to create the first AI gene therapy tool CRISPR-Cas9, and the first AI whole genome https://www.biorxiv.org/content/10.1101/2025.09.12.675911v1 from scratch.
  • Evo 2 https://www.nature.com/articles/s41586-026-10176-5, featured in Nature, is the largest fully open source AI project across any domain.
  • Radical Numerics is bringing the rigor of distributed systems, model architecture, and numerics research to the challenges of biology.
  • We've redesigned the foundation model training stack to turn the world's raw scientific data (e.g. biological sequences, experiments, and physical processes), into intelligible, generative models that can expand and accelerate what humanity can understand, design, and cure.
  • The same generative breakthroughs that enable life-saving cures also lowers the barrier to creating engineered threats and AI-generated bioweapons.
  • We believe these forces are inseparable.
  • Radical Numerics was founded to develop both the power to design and the responsibility to defend.

Visa & Work Authorization

  • Radical Numerics participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
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This listing is sourced directly from Radical Numerics's careers page and normalized into a canonical job model.