Machine Learning Engineer/Machine Learning Scientist , Multi Modality

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)

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.

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;

• 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.

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