Job Details

Machine Learning Engineer, Multi Modality

Our Mission

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

Diversity at 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 part of our team, you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. As a ML Engineer you will be an integral part of our multidisciplinary teams 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

• Applying software engineering skills to develop reliable, scalable, performant distributed systems in a cloud environment.
• Develop efficient data loading strategy and performance tracking to train large models with distributed training across multiple nodes.
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• Partner with other machine learning scientists and engineers to establish automated, robust, and efficient analytical pipelines for reproducible research.
• Stay up-to-date on the latest developments in deep learning, particularly in the areas of Transformers, NLP, Reinforcement Learning, and DDPMs.
• Contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Who You Are

Minimum Qualifications

• 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, explainability, diffusion 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.

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.

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.

J-18808-Ljbffr