What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing unified, multi-modal generative foundation models for multiscale biology. You will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission.

In this role, you will partner and collaborate with other multidisciplinary Scientists and Engineers across the Institute of Computation to design, build, and scale state-of-the-art foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. You will focus on the synthesis of unstructured multimodal signals with the structured relational data and knowledge graphs that represent biological reality.

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

As a Staff Machine Learning Scientist, you will use your experience to focus on designing, developing, and evaluating state-of-the-art foundation models, at scale, to benefit the research.

• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data, natural language, and structured relational inputs.   
• Architect and implement novel hybrid models that integrate Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs .
• Develop Relational Foundation Models (RFMs) that enable zero-shot predictive tasks over heterogeneous, multi-table biological datasets.   
• Lead the design of efficient data loading strategies and distributed training recipes (e.g., FSDP, DeepSpeed) to train models across multiple GPU nodes.   
• Gain insights into model performance based on theory, deep research, and the mathematical underpinnings of set-invariant and graph-structured architectures .
• Apply strong coding experience to model development and deployment, ensuring research prototypes transition into reliable, scalable production systems.
• Stay up-to-date on the latest developments in deep learning—including native early-fusion and Mixture-of-Experts (MoE) architectures—and apply this knowledge to Altos' research .
• Mentor junior staff while maintaining a high individual technical contribution to the core research ecosystem and peer-reviewed publications.

Who You Are  

We are looking for someone who is:

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.
• Highly collaborative in mindset and ways of working across research and engineering boundaries.
• Self-motivated to drive and deliver on long-term technical projects and scientific goals.
• Demonstrates the desire to grow professionally and expand their skillset in biology, machine learning, and/or drug development.
• Able to communicate and explain the design, results, and impact of complex AI architectures to both scientific and non-scientific staff.
• Keen to contribute to seminars and scientific initiatives within Altos and the broader AI research community.

Minimum Qualifications

• PhD in Computer Science, Machine Learning, or a similar quantitative field with 5+ years of relevant work experience in academic or industry settings.
• Prior experience in developing and implementing novel generative AI models, specifically in multimodal integration, GraphRAG, or relational deep learning .
• Deep understanding of Machine Learning principles and how they apply to diverse architectures like Transformers, GNNs, and diffusion models .
• Very strong programming skills in Python and deep learning libraries (e.g., PyTorch, JAX, Hugging Face Transformers/Accelerate).   
• Proven experience with multi-GPU and distributed training at scale (e.g., DDP, FSDP, DeepSpeed, Megatron, or Ray).   
• Strong track record of published, peer-reviewed innovative AI/ML research at top-tier conferences (NeurIPS, ICML, ICLR, CVPR).

Preferred Qualifications

• Familiarity with tabular foundation models (e.g., TabPFN) and in-context learning strategies for structured data .
• Specific experience in native multimodal modeling (early-fusion) or the synthesis of LLMs and Knowledge Graphs .
• Track record of ML applied to biological data, such as NGS data (RNA-seq, ATAC-seq), biological imaging (microscopy, IF), or spatial transcriptomics.
• Experience in optimizing large-scale inference via quantization, distillation, or memory-efficient attention mechanisms.

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in agentic AI methods for biological and clinical data curation and analysis.

In this role, you will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. You will collaborate with biomedical research experts as well as other machine learning scientists and engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem, focusing on designing and building state-of-the-art agentic AI systems and workflows that tackle biological questions, accelerate clinical data analysis, and aid in the discovery of novel interventions for aging and disease.

The successful candidate will combine deep expertise in agentic AI methods with a strong foundation in bioinformatics and/or clinical R&D. You will work closely with domain experts to translate complex biological and clinical data challenges into intelligent, automated solutions. You will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Design and develop agentic AI workflows for biological and clinical data curation tasks
• Research and implement advanced context engineering techniques (RAG, agentic RAG, graph RAG) tailored to biomedical data
• Develop and optimize prompts and agent architectures for reliability, accuracy, and scientific rigor
• Build LLM-based tool-use systems and integrations relevant to bioinformatics and clinical R&D pipelines
• Collaborate with bioinformatics scientists, clinical researchers, and domain experts to identify automation opportunities and translate them into agentic solutions
• Evaluate and benchmark agentic systems, establishing rigorous metrics for performance and correctness in scientific contexts
• Stay current with the rapidly evolving landscape of agentic AI methods and contribute to internal best practices

Who You Are 

• Proven track record leveraging machine learning and AI to solve real-world problems
• Expertise in agentic AI methods development, including prompt optimization, LLM-based tool use, context engineering (RAG, agentic RAG, graph RAG), and agent evaluation
• Experience writing production-quality code with agentic frameworks (e.g., LangGraph, Pydantic-AI, DSPy, or similar)
• Deep familiarity with bioinformatics and/or clinical R&D, with the ability to engage meaningfully with domain experts on biological and clinical questions
• Proficiency with AI-assisted development tools (e.g., Claude Code, Cursor) to iterate rapidly
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focused on professional growth
• Able to advise others across the wider function / company on cutting edge agentic AI practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, machine learning, and medicine
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities

Minimum Qualifications

• PhD in Computer Science, Machine Learning, Bioinformatics, or a related field
• Demonstrated experience developing agentic AI systems, including LLM-based tool use, prompt engineering, and context engineering techniques
• Strong foundation in machine learning principles and their application to real-world problems
• Strong background in bioinformatics, computational biology, or clinical R&D
• Familiarity with MCP server development and agent skill creation
• Very strong programming skills in Python, with experience writing production-quality, well-documented code
• Strong track record of published peer-reviewed research in AI/ML and/or computational biology

Preferred Qualifications

• Experience with AWS services (S3, Bedrock, Lambda) in the context of AI/ML workflows
• Experience with clinical trial data, regulatory data curation, or biomedical ontologies (e.g., CDISC, SNOMED, MedDRA)
• Track record working with NGS data (e.g., RNA-seq, ATAC-seq, DNA methylation) or other biological data modalities
• Experience designing evaluation frameworks and benchmarks for agentic AI systems
• Familiarity with knowledge graph construction and graph-based retrieval methods

The salary range for Redwood City:

• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego:

• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

Altos 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.

Who You Are

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, DeepSpeed, 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.

Preferred Qualifications

• 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: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

#LI-NN1

Exact compensation may vary based on skills, experience, and location.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. We are open to hiring either a Machine Learning Scientist or Machine Learning Engineer.

In either role, you will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem. Focussing on designing and building state-of-the-art multimodal foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity. 

Responsibilities

Machine Learning Engineer

• As a Machine Learning Engineer you will focus on building, deploying and optimizing machine learning models at scale. 
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• Develop efficient data loading strategy and performance tracking to train large models with distributed training across multiple nodes 
• Ability to apply software engineering skills to develop reliable, scalable, performant distributed systems in a cloud environment.

Machine Learning Scientist

• The ideal candidate will be able to use their experience to focus on designing, developing and evaluating state of the art foundation models, at scale, to benefit the research.
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• You will be able to gain insights, based on theory, deep research and the mathematical underpinnings of your work.
• Be experienced in using AI as a tool to accelerate your research.
• Can apply strong coding experience to model development using existing languages(s) and framework(s)

Who You Are

We are looking for someone who is :

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities and how they can contribute
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Demonstrates the desire to grow professionally and expand their skillset and knowledge;  is keen to learn more about biology, computational science, and drug development.
• Ability to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Is able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

Machine Learning Engineer

• MS in Computer Science, Statistics, Machine Learning, Artificial Intelligence, or a related discipline
• 0-5 years of relevant work experience in either an academic or industry setting
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Ideally, experience in a distributed training framework, like DDP, FSDP, Deepspeed, Megatron, or HuggingFace Accelerate, Ray.
• Expertise in a subset of the following: transformers, natural language processing, multi-modality in language and/or in biology, diffusion models.

Machine Learning Scientist

• PhD in Computer Science / Machine Learning or similar fields 
• 0-5 years of relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Strong track record of published peer reviewed innovative AI/ML research 
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Familiarity with multimodal data integration, including early and/or late fusion strategies.
• Track record of ML applied to NGS data (e.g.RNA-seq, ATAC-seq, ChIP-seq, DNA methylation), biological imaging modalities (e.g. microscopy, H&E, IF), and/or spatial transcriptomics.

The salary range for Machine Learning Engineer position in San Diego

• Machine Learning Engineer I: $140,000 - $179,500
• Machine Learning Engineer II: $158,300 - $203,000

The salary range for Machine Learning Engineer position in Redwood City

• Machine Learning Engineer I: $152,600 - $195,600
• Machine Learning Engineer II: $174,200 - $223,300

The salary range for Machine Learning Scientist position in San Diego

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000

The salary range for Machine Learning Scientist  position in Redwood City

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000

Exact compensation may vary based on skills, experience, and location.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasizes teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Redwood City, CA:

• Senior Scientist I, Machine Learning: $257,400 - $330,000
• Senior Scientist II, Machine Learning: $290,900 - $373,000
• Principal Scientist, Machine Learning: $330,800 - $424,100

The salary range for San Diego, CA:

• Senior Scientist I, Machine Learning: $239,500 - $307,000
• Senior Scientist II, Machine Learning: $262,100 - $336,000
• Principal Scientist, Machine Learning: $312,100 - $400,100

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasises teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Senior Scientist I, Machine Learning: £115,600 - £152,100
• Senior Scientist II, Machine Learning: £131,900 - £173,500
• Principal Scientist, Machine Learning: £173,700 - £228,600

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute to Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Scientist I, Machine Learning: £74,900 - £98,500
• Scientist II, Machine Learning: £107,900 - £142,000
• Senior Scientist I, Machine Learning: £115,600 - £152,100

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source softwar

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior Project Manager at Altos, you will act as an operational anchor with a big-picture mindset for the Institute of Computation (IoC). Leveraging your own background in science, you will bridge the gap between complex biological questions and rigorous operational execution using project management. You will not just track tasks; you will actively shape how cross-functional teams of biologists, data scientists, and machine learning scientists and engineers collaborate to achieve ambitious goals. This role is designed for an operational expert who excels at translating abstract scientific goals into actionable project plans, connecting the dots between daily tasks and broader program objectives, and ensuring alignment across computational, scientific, and business units.

Responsibilities:

• Plan & Execute: Translate high-level scientific intent into actionable project plans for 4-6 multidisciplinary projects. Maintain and track visibility on goals, milestones, dependencies, and timelines to ensure delivery within scope and budget.
• Operational Execution & Big Picture Alignment: Collaborate closely with scientific leads to translate their vision into reality. You will ensure the team understands how their daily tasks contribute to the broader mission, proactively identify risks, and drive the accountability needed to ensure research milestones are met on time and within scope.
• Operational Coordination: Coordinate team operations, including meeting cadence, agendas, and workflows. Ensure meetings are effective, focused, and result in clear action items.
• Documentation & Knowledge Management: Own the "single source of truth" for projects. Document meeting notes, key decisions, and lessons learned, ensuring they are accessible to all stakeholders.
• Cross-Functional Communication: Serve as the bridge between diverse disciplines to ensure seamless handoffs between scientific, computational, and business units.
• Process Improvement: Design and implement pragmatic workflows that improve operational efficiency without creating unnecessary bureaucracy.

Who You Are

Minimum Qualifications:

• Education: BS or MS in life sciences, computational biology, business, or a related field.
• Experience: 
• 5+ years of project management experience within biotechnology, computational biology, AI/ML, or pharmaceuticals. 
• Experience managing large-scale data generation (omics, imaging) and machine learning model development is highly preferred. 
• You started your career 'at the bench' (wet lab or computational) and made a deliberate pivot into professional Project Management.
• PMP, PRINCE2, or Agile certifications are a plus, but real-world experience managing complex R&D portfolios is prioritized.
• Deep Project Management Toolbox: You are an expert in a range of project management methodologies (Agile, Waterfall, Kanban, Hybrid) and know exactly when to deploy which tool. You don't force "process for process's sake"; you pragmatically select the right framework to fit the ambiguity of early-stage discovery.
• Strategic & Tactical: You function at dual altitudes - comfortable understanding the broader roadmap one hour, and deep-diving into Jira tickets, meeting minutes, or resource allocation the next.
• Communicator & Influencer: You can translate complex technical goals for diverse audiences and have the confidence to influence stakeholders without formal authority.
• Operational Mindset: You are an analytical problem-solver who is results-driven, detail-oriented, and able to work autonomously with minimal supervision.
• Tool Proficiency: High proficiency in project management platforms (e.g., Jira, Smartsheet) and Google Suite.

The hourly range for remote in the UK only:

• Hourly rate range: £29.00 - £36.00

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior Project Manager at Altos, you will act as an operational anchor with a big-picture mindset for the Institute of Computation (IoC). Leveraging your own background in science, you will bridge the gap between complex biological questions and rigorous operational execution using project management. You will not just track tasks; you will actively shape how cross-functional teams of biologists, data scientists, and machine learning scientists and engineers collaborate to achieve ambitious goals. This role is designed for an operational expert who excels at translating abstract scientific goals into actionable project plans, connecting the dots between daily tasks and broader program objectives, and ensuring alignment across computational, scientific, and business units.

Responsibilities:

• Plan & Execute: Translate high-level scientific intent into actionable project plans for 4-6 multidisciplinary projects. Maintain and track visibility on goals, milestones, dependencies, and timelines to ensure delivery within scope and budget.
• Operational Execution & Big Picture Alignment: Collaborate closely with scientific leads to translate their vision into reality. You will ensure the team understands how their daily tasks contribute to the broader mission, proactively identify risks, and drive the accountability needed to ensure research milestones are met on time and within scope.
• Operational Coordination: Coordinate team operations, including meeting cadence, agendas, and workflows. Ensure meetings are effective, focused, and result in clear action items.
• Documentation & Knowledge Management: Own the "single source of truth" for projects. Document meeting notes, key decisions, and lessons learned, ensuring they are accessible to all stakeholders.
• Cross-Functional Communication: Serve as the bridge between diverse disciplines to ensure seamless handoffs between scientific, computational, and business units.
• Process Improvement: Design and implement pragmatic workflows that improve operational efficiency without creating unnecessary bureaucracy.

Who You Are

Minimum Qualifications:

• Education: BS or MS in life sciences, computational biology, business, or a related field.
• Experience: 
• 5+ years of project management experience within biotechnology, computational biology, AI/ML, or pharmaceuticals. 
• Experience managing large-scale data generation (omics, imaging) and machine learning model development is highly preferred. 
• You started your career 'at the bench' (wet lab or computational) and made a deliberate pivot into professional Project Management.
• PMP, PRINCE2, or Agile certifications are a plus, but real-world experience managing complex R&D portfolios is prioritized.
• Deep Project Management Toolbox: You are an expert in a range of project management methodologies (Agile, Waterfall, Kanban, Hybrid) and know exactly when to deploy which tool. You don't force "process for process's sake"; you pragmatically select the right framework to fit the ambiguity of early-stage discovery.
• Strategic & Tactical: You function at dual altitudes - comfortable understanding the broader roadmap one hour, and deep-diving into Jira tickets, meeting minutes, or resource allocation the next.
• Communicator & Influencer: You can translate complex technical goals for diverse audiences and have the confidence to influence stakeholders without formal authority.
• Operational Mindset: You are an analytical problem-solver who is results-driven, detail-oriented, and able to work autonomously with minimal supervision.
• Tool Proficiency: High proficiency in project management platforms (e.g., Jira, Smartsheet) and Google Suite.

The hourly range for remote hires:

• Hourly rate range: $70.00 - $90.00 / hr.

Exact compensation may vary based on skills, experience, and location.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

We’re looking for a Strategy & Operations Manager / Senior Manager to work directly with the Chief of Staff, Director to build the strategic planning and operational backbone for the Institute of Computation, which serves as the AI and data science organization at Altos Labs. The IoC develops and advances AI tools, models and technology to unravel the mechanisms behind aging to develop therapeutic ways to reverse it. This role sits at the intersection of strategy and business operations, technical program management, and product-minded thinking.

You’ll work closely with the Chief of Staff, SVP, engineering  and AI leaders, Director of Program Management, and our data and computing infrastructure teams to drive strategic projects often requiring both deep business judgement and technical understanding, own and improve key operational systems, and help serve as a connective tissue and partnership manager between AI research, engineering, data, portfolio management team, wetlab experimentation, People, Finance, Legal, and external partners. 

This is a great fit for someone with a technical program management, technical product management, consulting, strategy and operations or similar background who can just as easily get down to the weeds and roll their sleeves up to dive into problems, as well as can operate at the 10,000 foot level and think at a systems-level view and bridge between AI, engineering and the business. 

Responsibilities

• Strategic Initiatives & SVP / Leadership Support: Lead and/or support special projects that can cover a wide breadth of topics including data strategy, talent strategy, IP strategy and contribute to SVP/Leadership Team operations, potentially including facilitating Leadership Team meetings. 
• Strategic Planning: Help design and execute on IoC strategic planning and rhythm of business as part of the Office of the SVP and Institute Director of the IoC.
• Partnership Strategy & Alliance Management: Support partnership strategy development and act as a de‑facto alliance manager for key external platform and data generation partners in the AI and biotech landscape, ensuring clear goals, aligned timelines, regular check‑ins, and smooth coordination with internal teams.
• Budget & Resource Management: Own day‑to‑day budget operations for the org in partnership with Finance and the Chief of Staff, including tracking spend, forecasting, approvals, and AWS billing and cost reporting/optimization.
• Engineering Operations: Act as the technical program manager point person between our data science / modeling, wetlab experimentation, and our computing and data infrastructure engineering teams. This may include managing modeling team user experience, access, usage forecasting, managing requests, dependencies and prioritization for data generation or curation needs from the central Data Infrastructure teams, and migration/cutover planning and communications.
• Business Operations & Process Improvement: Analyze and improve core operational processes (e.g., AWS billing, central resourcing, intake/prioritization) using a structured, data‑driven approach and latest AI technologies to design lightweight, scalable workflows. 

Who You Are 

• Demonstrated experience leading cross-functional teams and driving strategic and cross‑functional projects end‑to‑end: developing strategies, aligning stakeholders, and rolling out initiatives. 
• Strategic and analytical thinker with strong problem-solving abilities and ability to navigate white-space problems, complex organizations, and ambiguous settings to drive buy-in. 
• Results-driven and detail-oriented with a proactive approach.
• Combination of grit and intellectual curiosity that enables you to dig into messy, complex problems and recommend solutions that bring simplicity 
• Understands how to think backwards from first principles, but also has operated in environments where they can bring best practices 
• Growth-oriented and eager to learn in a fast-paced environment.
• Operational excellence at the 1-foot and 50K foot levels

Minimum Qualifications

• 4-7 years of experience (for Manager) and 7+ years of experience (for Senior Manager) in any of the following: technical program management, technical product management, technical / product operations, strategy & operations, management consulting, or similar role
• Familiarity operating in a product or software engineering organization 
• Demonstrated ability to work credibly with engineers, data scientists, and/or ML researchers 
• Excellent communication and stakeholder management skills: can tailor level of detail from SVP to IC.
• Comfortable giving structure to ambiguous problems and pushing for clarity
• Strong operational and analytical skills, cross-functional stakeholder engagement and relationship building 

Preferred Qualifications

• Familiarity operating within an AI / ML or data science organization and/or highly technical R&D environment (e.g., biotech with strong computational components).
• No prior direct modeling experience needed, but needs to understand the concepts well enough to translate between technical and non‑technical stakeholders and shape initiatives involving complex AI or technical concepts. 
• Direct experience of close partnership or managing teams of AI / ML scientists and engineers or software engineers and experience with Agile 
• Experience working in fast-paced startup, MBA or technology companies

The salary range for the Redwood City, CA site:

• Strategy & Operations Manager: $74 - $90 / hr.
• Senior Strategy & Operations Manager: $91 - $111 / hr.

The salary range for the San Diego, CA site:

• Strategy & Operations Manager: $66 - $80 / hr.
• Strategy & Operations Manager: $83 - $101 / hr.

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.