Research Scientist, Machine Learning, Multi Modality

San Francisco Bay Area, CA;San Diego, CA

Altos Labs

Altos Labs is a biotechnology company focused on restoring cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that occur throughout life. Learn more about Altos.

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Our Mission

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.

For more information, see our website at altoslabs.com.

Our Value

Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission.

Diversity at Altos

We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.

What You Will Contribute To Altos

As a Scientist, Machine Learning, you will help to accelerate and optimize our progress in developing foundation models for multiscale biology, in multi-modal biological generative modeling. We are looking for a creative and collaborative individual to join our multidisciplinary team of scientists and engineers building the computational platforms that will enable Altos to achieve its mission. The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

  • Work on a team of engineers and scientists to train and optimize large-scale machine learning systems using multimodal biological data and natural language data.
  • Help discover and develop new exciting applications of the models that we develop to health and biology.
  • Collaborate closely with experimentalists to design and execute on data collection efforts to be used in computational modeling efforts.
  • Continuously learn and stay up-to-date on the latest developments in deep learning for biological discovery.
  • Partner with other machine learning scientists and engineers to establish automated, robust, and efficient analytical pipelines for reproducible research.
  • Contributes to seminars and other scientific initiatives within Altos and the broader scientific community.

Who You Are

Minimum Qualifications

  • PhD 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, explainability, diffusion models.
  • Proven track record in training and developing deep learning models.
  • Someone with a highly collaborative mindset, who is self-motivated
  • Ability to communicate and explain the design, results, conclusions and the impact of findings to both scientific and nonscientific staff.
  • Deep analytical thinker and problem solver.

Preferred Qualifications

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

 

The salary range for Redwood City, CA:

  • Scientist I, Machine Learning: $200,600 - $271,400
  • Scientist II, Machine Learning: $236,000 - $330,000

The salary range for San Diego, CA:

  • Scientist I, Machine Learning: $187,000 - $253,000
  • Scientist II, Machine Learning: $220,000 - $300,150

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

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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 We Want You To Know

We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation.

Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. 

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. 

Altos currently requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions (e.g., due to a medical condition or sincerely-held religious belief).

Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.

Note: Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at https://www.linkedin.com/pulse/how-spot-avoid-online-job-scams-biron-clark/

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Tags: Biology Computer Science DDP Deep Learning Diffusion models FSDP Generative modeling HuggingFace Machine Learning NLP PhD Pipelines Privacy Python PyTorch Research Statistics Transformers

Perks/benefits: Transparency

Region: North America
Country: United States

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