Scientist/Senior Scientist, Multimodal AI Institute of Computation
Listed on 2026-02-17
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IT/Tech
Machine Learning/ ML Engineer, Data Scientist, AI Engineer, Artificial Intelligence
Our Mission
Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.
Diversity at AltosWe believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.
What You Will Contribute To AltosAltos Labs is building a world-class AI ecosystem to solve the most complex problems in human biology. You will directly design and build high-performance, scalable solutions that unify high-dimensional biomedical imaging with molecular and language data.
By implementing large-scale multimodal data fusion, you will move beyond simple image analysis to create predictive models that map across biological domains. You will be hands‑on with the data and the code, collaborating with our engineering team to ensure these models are scalable, efficiently trainable on distributed cloud infrastructure, and accessible to our global research community.
Responsibilities- Model Development:
Design, code, and train large-scale foundation models (e.g., Vision Transformers, Multimodal LLMs) that can embed spatial data and integrate multiple modalities. - Hands‑on Data Fusion:
Implement innovative cross-domain mapping and fusion strategies to synchronize heterogeneous biological datasets. - Scaling & Training:
Build and manage high-performance ML pipelines capable of processing petabyte-scale image repositories and multi‑omics streams in a cloud environment. - Technical
Collaboration:
Work directly in the trenches with experimental scientists and software engineers to translate biological complexity into performant code and reliable distributed systems.
We are looking for a technical specialist who thrives on solving "unsolvable" problems through code and rigorous experimentation. We are open to candidates at the Scientist I, Scientist II, or Senior Scientist level based on technical expertise.
Minimum Qualifications- Education:
PhD in Computer Science, AI/ML, Biomedical Engineering, or a related quantitative field. - Hands‑on CV Expertise:
Deep experience building and deploying modern Computer Vision architectures (Vision Transformers, U‑Nets, Self‑Supervised Learning). - Distributed Training:
Proven experience training and fine-tuning large models at scale using frameworks like PyTorch Distributed, Deep Speed, or Jax. - Programming Mastery:
Expert-level Python skills, with a focus on building production-ready machine learning code and large-scale data management systems. - Scientific Contributions: A track record of technical contributions via high-impact publications (CVPR, ICCV, NeurIPS, etc.) or significant contributions to open-source ML frameworks.
- Direct experience with Multimodal Fusion (e.g., aligning image embeddings with transcriptomic or proteomic data).
- Proficiency with cloud-native AI tools (AWS/GCP, Kubernetes, Docker) and building automated MLOps workflows.
- Experience handling the unique noise and sparsity of biological data.
The salary range for Redwood City, CA:
- Scientist I, Machine Learning
: $211,200 - $257,500 - Scientist II, Machine Learning
: $237,800 - $290,000 - Senior Scientist I, Machine Learning
: $270,600 - $330,000
The salary range for San Diego, CA:
- Scientist I, Machine Learning
: $188,600 - $230,000 - Scientist II, Machine Learning
: $223,900 - $273,300 - Senior Scientist I, Machine Learning
: $251,700 - $307,000
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Exact compensation may vary based on skills, experience, and location.
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We value collaboration and scientific excellence.
We believe that diverse perspectives and a culture of belonging are foundational to scientific innovation and…
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