Maze Therapeutics Logo

Maze Therapeutics

Machine Learning Application Engineer II

Sorry, this job was removed at 10:15 p.m. (PST) on Wednesday, Jun 03, 2026
In-Office
South San Francisco, CA, USA
In-Office
South San Francisco, CA, USA
The Position

At Maze Therapeutics, we believe precision medicine has the power to transform the lives of patients with both common and rare diseases. As a Machine Learning Application Engineer II, you will play a hands‑on role in delivering high‑impact, production‑grade solutions that advance our drug discovery programs. You will design, build, and scale data and machine learning infrastructure across early research, lead optimization, and development stages of the drug discovery pipeline. In this role, you will enable data‑driven science while upholding strong engineering standards and FAIR data principles. 

This position reports to a Senior Data Engineer. 


The Impact You’ll Have
  • Support management of biobank scale datasets in Polaris, Maze’s internal platform supporting Compass, by building scalable data ingestion, cleaning, processing, and validation pipelines. 
  • Work with scientific compute teams to design and deploy machine learning models to support workflows in research and small molecule drug discovery (compound property prediction, assay data prediction, data analysis). 
  • Lead the evaluation and integration of Large Language Models (LLMs) to automate data ingestion workflows, enhance intelligent querying, and support user-facing variant association and scientific visualization platforms. 
  • Design and operate scalable ML and data platforms leveraging Terraform (IaC) and Git-based CI/CD pipelines, incorporating workflow orchestration, automated model lifecycle management, and production-grade monitoring and reliability. 
  • Collaborate with development organization to evaluate and deploy ML tools that support workflows across Regulatory, Clinical Operations, and Medical Affairs. 
  • Collaborate cross-functionally translate scientific requirements into production-grade systems. 
What We’re Looking For
  • Master’s degree in Computer Science, Machine Learning, Bioinformatics, Data Engineering, or related fields. 
  • 3+ years of industry experience building production-grade data and ML pipelines, preferably in life sciences supporting drug discovery. 
  • Hands-on experience deploying AI/ML models in drug discovery applications (e.g., computational biology/chemistry workflows). 
  • Experience with FAIR data principles and strong programming skills in Python and SQL (R is a plus). 
  • Proven experience in deploying and maintaining ML systems, including CI/CD, workflow orchestration, and monitoring. 
  • Experience with workflow orchestration tools (e.g., Airflow, Prefect). 
  • Experience with containerization and cloud infrastructure (Docker, Kubernetes, AWS or similar). 
About Maze Therapeutics

Maze Therapeutics is a clinical-stage biopharmaceutical company harnessing human genetics to develop precision medicines for patients with kidney and metabolic diseases. Our clinical pipeline is anchored by two small molecule programs: MZE829, an APOL1 inhibitor for patients with APOL1‑mediated kidney disease, and MZE782, which targets genetic drivers of disease in phenylketonuria (PKU) and chronic kidney disease. We are also advancing a preclinical pipeline through our Compass platform, which links human genetic variants to the biological pathways that drive disease.

Our People

Maze is comprised of a team of passionate and creative professionals committed to discovering and delivering transformative medicines to patients suffering from both rare and common genetic diseases. We are fostering a culture that encourages vision, initiative and the development of talent. Our supportive work environment inspires creative thinking and freedom of expression, resulting in a stimulating atmosphere where people enjoy coming to work. While we have a passion for advanced science and pride ourselves on excellence in execution, ultimately, everything we do is about patients. 

Our Core Values

Further Together – Our path is paved with challenges, but with resilience and a team-first mentality, we’ll achieve our mission. 

Impact Obsessed – We embrace the bold, take calculated risks, and learn from our mistakes to improve the lives of others.

Stand True – Our integrity is foundational; it guides us no matter the obstacle.

The expected annual salary range for employees located in the San Francisco Bay Area is $154,000 - $188,000. Additionally, this position is eligible for an annual performance bonus.

Maze performs position-based compensation benchmarking to industry market data to ensure we pay competitive wages. Determination of starting salary will depend upon a variety of job-related factors, which may include professional experience, skills, and job location. The expected salary range for this role may be modified in the future.

Maze offers a robust benefits package to our eligible employees including competitive medical, dental, and vision insurance, mental health offerings, equity incentive plan, 401(k) program with employer match and a generous holiday and PTO policy.


#LI-Hybrid

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account