Staff Machine Learning Engineer

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 Senior Staff Machine Learning Engineer, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology. We are looking for a hands-on, senior level creative and collaborative person 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

• Partner with world-class scientists across Altos to help generate biological insights with the goal of developing novel therapies;
• Design and implement large-scale machine learning algorithms and systems applied to biological datasets;
• Train, evaluate, and optimize machine learning models at scale;
• Communicate effectively with internal and external collaborators to meet ambitious research and development goals.

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; 
• 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;
• Growth mindset - the desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Excitement about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Masters or Ph.D. degree in a quantitative/computational field such as computer science, artificial intelligence, mathematics, statistics, physics, or computational biology, or equivalent experience;
• 8+ years experience in developing machine learning models;
• Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX;
• Experience in large-scale distributed optimization of machine learning models across multiple GPUs and nodes.

Preferred Qualifications

• Familiarity with biological data formats, concepts, and computational models;
• Experience in cell health and rejuvenation-related research area;
• Experience with identification and assessment of drug targets and/or therapeutic compounds;
• Experience in the application of machine learning methods to biological data, including genomics, transcriptomics, epigenetics, proteomics, and imaging;
• Track record in open-source software development, e.g., demonstrated by high-impact GitHub repository;
• Track record of high-caliber scientific work, e.g., demonstrated through publications in peer-reviewed scientific journals or major ML conferences;
• Experience with one lower level language (not limited to, but such as C++, Rust);
• Experience with large scale data processing and database tools such as MapReduce, Dask, SQL, Hugging Face Datasets, TileDB, Ray.

The salary range for Redwood City, CA:

• Staff Machine Learning Engineer: $232,900 - $315,100
• Senior Staff Machine Learning Engineer: $255,000 - $345,000

The salary range for San Diego, CA:

• Staff Machine Learning Engineer: $221,000 - $299,000
• Senior Staff Machine Learning Engineer: $243,950 - $330,050

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_KM1

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/