What You Will Contribute To Altos

An exciting opportunity is available for a Scientist II to join the Larrieu group at Altos Labs, Cambridge Institute of Science (Cambridge, UK). At Altos, the Larrieu lab is exploring both fundamental questions and translational opportunities. We are seeking a very highly motivated, versatile, creative, and collaborative individual, who is passionate and dedicated about employing their expertise to unravel the deep biology of cell health and resilience. This includes the elucidation of the mechanism of action of specific interventions that can reverse, halt or mitigate the effects of ageing on cell health. 

Responsibilities

• Elucidate processes that contribute to the age-related erosion of cell/tissue resilience.
• Engage in ground-breaking and innovative science and in Altos scientific activities.
• Develop project-specific experimental strategies, techniques, and procedures including new assays and pipelines to support translational projects.
• Lead, design and execute in vitro and in vivo experiments for identification and validation of targets with therapeutic potential
• Develop and implement biochemical and cellular assays to support screening and characterization of potential candidate therapies
• Collaborate widely across Altos to multiply efforts, gain insight into the centrality of the nuclear envelope in ageing and identify potential new therapeutic avenues          
• Collaborate with multidisciplinary teams including chemists, pharmacologists, and bioinformaticians to advance drug discovery projects.
• Present data to a variety of audiences including senior executives through entry-level employees.

Who You Are

Minimum Qualifications

• PhD in life sciences with 3-5 years of relevant postdoc/industry experience
• Extensive experience in mammalian cell culture (including primary cells).
• Strong background in molecular and cell biology with experience in assay development and validation, to support pre-clinical studies.
• Experience in small rodent handling, with an ability to independently design and coordinate the execution of complex in vivo studies, including drug administration, tissue harvest and processing.
• Strong sense of collective ownership of projects within the group and Altos.
• Critical, visionary, and creative thinking with an ability to formulate scientific questions, design strategies, and implement plans effectively.
• Strong organizational skills to manage multiple tasks simultaneously, prioritize workloads, and meet deadlines.
• High level of rigor and precision in experimental procedures, data recording, and documentation.
• Problem-solving skills to identify potential issues, test, and develop innovative solutions.
• Excellent writing and communication skills
• Ability to maintain cooperative working relationships with a broad range of people, including staff colleagues, lab members and the community

Preferred Qualifications 

• Understanding of in vivo delivery systems such as AAV, LNP, lentivirus etc.
• Biochemistry skills, including biochemical and enzymatic assay development
• Some proficiency in R and Python to support data analysis
• Prior industry experience

The salary range for Cambridge, UK:

• Scientist II, Biological Sciences: £61,400 - £80,800

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.

Senior Administrative Project Coordinator  / Administrative Project Coordinator 

What You Will Contribute to Altos

An exciting opportunity is available for an experienced Administrative Project Coordinator to join Altos Labs. The position requires advanced organisational, administrative, and analytical skills/support. Duties and tasks are complex in nature where considerable judgment, independent action and a high degree of initiative are required in resolving problems and making recommendations. Work is performed under limited supervision as part of a small team that provides operational support across the Cambridge Institute. 

The responsibilities of the role are split across administrative support for leaders and their teams; Project management and operational support and coordination for Cambridge-based Discovery Science/ IoC/ IoT/ Corporate Function teams; and operational support and project management for initiatives at the Cambridge Institute. The position requires the ability to work with insight, tact, confidentiality, and diplomacy to deal effectively with individuals at all levels.

As part of a small team, the role holder will need to work seamlessly with colleagues across Altos (often globally) and with the Cambridge Admin Team to ensure there is effective support and coverage for the smooth running of the Cambridge site.

Responsibilities

Vice President Administrative Support (25%)

• Provide administrative support for a number of senior leaders (VP/ PI) and limited support for their laboratory teams
• Manage calendar and coordinate scheduling, including lab meetings, internal and external meetings, team offsites/ retreats, conferences, professional engagements, and travel.
• Coordinate domestic and international travel arrangements and prepare travel itineraries.
• Assist with the logistics of the recruitment and onboarding process in partnership with hiring managers and Talent Acquisition Team.
• Process and track reimbursements from multiple sources.

Functional Operational Support, Coordination and Project Management (35%)

Working in close collaboration with the local team to provide support for Cambridge-based functional colleagues (e.g. IoC, IoT, EHS). Example responsibilities may include: 

Local IoC Team

• Administrative and operational support and planning for the Cambridge-based IoC team including coordination of team meetings (Wednesday group meetings, BioML meetings, IoC all-hands follow up in CI), supporting coordination of cross-site meetings (cTRC, cPRC, CSVL), Hackathon planning, team offsites/ retreats, conferences, travel and expenses.
• Provide limited administrative support for the Senior Director, AI/ML Genomics such as complex meeting arrangements.
• Assist with the logistics of the recruitment and onboarding process for new local IoC team members, in partnership with hiring managers and Talent Acquisition Team ON/ offboarding, interview scheduling, placement student recruitment.
• Support local IoC team on tracking and co-ordination of budgets, travel and expenses questions and coordination
• Organise IoC team events at CI (new starters, birthdays, leavers, etc)
• Act as conduit for general Altos and general CI admin comms into IoC teams (e.g. chasing to sign policies, coordinating local events, facilitating Reflections, etc)
• Directing IoC team members to the right people and sources of information company wide
• Act as primary point of contact for IoC visitors to CI and facilitate onsite setup and preparation for CI Leadership Team retreats

Local IoT Team:

• Administrative and operational support and planning for the Cambridge-based IoT team including coordination of team meetings, internal and external meetings, team offsites/ retreats/ events, conferences, travel and expenses.
• Provide limited administrative support for the Chief of Science Operations such as complex meeting arrangements.
• Assist with the logistics of the recruitment and onboarding process for new local IoT team members, in partnership with hiring managers and Talent Acquisition Team. 
• Support local IoT team on tracking and co-ordination of budgets
• Projects - project/process management support for IoT projects including scheduling and tracking actions.

Corporate Functions:

• EHS - Working closely with the Director, Environment, Health & Safety to support CI EHS deliverables and projects/ programmes. Provision of secretariat support for CI Health & Safety Committee.
• Project/process management support for local delivery of corporate projects such as launches, events and communications.
• Events - support for local and Altos-wide corporate events, including seminars, cross-institute meetings and events 
• Communications - assist with local deployment of global / local communications. 

Cambridge Site Operational Support and Project Management (40%)

Collaborating with colleagues locally and across Altos to ensure smooth running of the facility, events and activities, which may include:

• A broad range of office management deliverables including local communications - slack, email, posters, newsletter etc, office supplies, purchase orders for vendors, advising/ helping colleagues with operational processes such as travel booking or expenses claims.

• Support for site committees/ meetings as required, including drafting agendas, taking effective minutes, documenting and tracking actions.
• Events - responsible for supporting organisation and delivery of Cambridge quarterly social events (including the holiday party), cultural events, fortnightly CI Connect and other ad hoc events during the year.
• Provide local operational support for Altos-Wide/ Functional All Hands and Town Hall meetings ensuring they run smoothly including diarising, room bookings, co-ordination of Facilities and IT requirements and support, rehearsal/ testing co-ordination, timely local reminders and supporting those speaking at the site.
• Coordination of internal and external visitors to the site, including sensitive visitor process, organising logistics and arranging transport and accommodation required. Advising on timing of visits and travel requirements, supporting visitor itinerary planning and meetings/ seminars planned.

• Collaborate with administration colleagues across Altos and Cambridge Administration Team on effective processes and procedures, process improvements, operational initiatives, site-wide events and institute activities.
• Work closely with the Social Committee to generate ideas and collect feedback on Cambridge events.
• Maintain a roster of external suppliers for events, onboard new vendors as required, manage bookings and briefing vendors on requirements.
• Plan events and track spend against budget.

Who You Are

Minimum Qualifications

• 5+ years of relevant experience working in similar role(s)
• Exceptional organisational and time management skills with the ability to prioritise a diverse range of tasks and multiple stakeholders
• Excellent verbal and written communications skills. Able to interact professionally across the organisation and with external stakeholders and vendors.
• Strong computer skills, including advanced knowledge of Google Workspace and Microsoft Office Suite (Word, Excel, Outlook) and a willingness to learn new software/ adopt AI tools.
• Experience of project management and delivery, able to drive longer-term project deliverables alongside day-to-day work.
• Ability to pick up new processes and technology quickly and create/ build processes to optimise efficiency and continuous improvements.
• Strong organisation and multitasking skills with a sense of urgency.
• High level of discretion and confidentiality when handling sensitive information.
• Approaches new challenges and high-pressure situations with a positive attitude and calm demeanor
• Proactive and resourceful with strong attention to detail.
• A positive, can-do attitude with the ability to work independently and as part of a team

Senior Admin Project Administrator

Hiring Range: £47,100- £62,000

Admin Project Administrator

Hiring Range: £42,600- £56,000

Level will depend on experience

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