Machine Learning Scientist

Palo Alto, CA - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

About Us

Our mission is to cure cancer through high performance accessible early cancer detection. That means saving lives.

Delfi Diagnostics is a Johns Hopkins spinoff focused on the non-invasive detection of cancer at earlier stages when it is most curable. DELFI uses artificial intelligence and whole-genome sequencing to detect unique patterns of DNA fragmentation in the blood of patients with cancer. These analyses are performed through simultaneous examination of millions of DNA sequences using machine learning to identify tumor-specific abnormalities.

In our passionate pursuit to radically improve health outcomes we serve humanity when we:

Lead with Science Anchor in Pragmatism: We pioneer life-changing science by ensuring quality transparency and rigor at all times.

Build With & For All: We embrace diverse backgrounds to innovate and achieve together. We are not just building a productwe aim to disrupt the path of cancer for all no matter geography or socioeconomic class.

Put We over I: We are a home for high-performing people. Through teamwork we build collective intelligence. Each of us wins when those we serve and those who serve with us win. We show up with empathy humility and integrity at every step of the journey.

About the Role

In this role you will develop tune and advance Delfis machine learning models for early cancer detection. Youll focus on improving model performance through structured experimentation creative modeling strategies and rigorous benchmarkingpushing models up internal leaderboards and identifying what drives improvement.

Youll also explore how the raw intelligence of large language models (LLMs) can be applied to improve model performance and feature representationsleveraging their reasoning capabilities. Working closely with bioinformaticians software engineers and data scientists youll operate at the intersection of machine learning and biology translating genomic signals into clinically meaningful insight.

This role is ideal for a scientist who enjoys hands-on modeling thrives on iteration and discovery and seeks to combine deep technical understanding with curiosity about new forms of machine intelligence.

What Youll Do

Youll design implement and optimize machine learning models for genomic and fragmentomic data perform systematic benchmarking to assess model quality and analyze the factors that drive predictive improvements.
Youll explore the use of LLMs to enhance feature representations and model architectures.
Youll ensure robust reproducible experimentation through sound data practices and MLOps best practices such as versioning model tracking and environment management.
Youll collaborate closely with teams across computational biology bioinformatics and software engineering to build shared understanding and integrate insights from data.

What Youll Have Accomplished 12 Months From Now

You will have led multiple modeling efforts that improved performance on Delfis internal leaderboards through careful experimentation and analysis.
You will have evaluated and demonstrated how LLMs can strengthen feature representations or model architectures to achieve measurable performance gains.
You will be recognized as a rigorous and creative contributorsomeone who combines scientific depth with curiosity and collaboration to drive the frontier of ML for early cancer detection.

What Youll Bring to DELFI

PhD in Computer Science Machine Learning Computational Biology Applied Mathematics or a related field
2 or more years of relevant industry or post-doctorate experience
Experience developing and evaluating ML models in applied or collaborative research settings with a demonstrated ability to deliver high-quality maintainable code and reproducible results
Experience working in team-based environments with shared codebases and version control practices
Proficiency in Python including use of ML frameworks such as PyTorch TensorFlow or scikit-learn
Experience applying MLOps best practices for experiment tracking model versioning or data pipeline reproducibility (e.g. MLflow Weights & Biases or equivalent)
Demonstrated success improving model performance through experimentation architecture design or advanced optimization methods
Familiarity with large language models (LLMs) including APIs frameworks and fine-tuning methods
Strong grounding in statistics data analysis and reproducible experimentation
Excellent communication skills and the ability to collaborate effectively across scientific and technical disciplines
A demonstrated record of scientific communication including at least one peer-reviewed publication in a recognized ML conference or scientific journal

Preferred

Experience with genomic sequencing or other biological data
Exposure to cloud-based ML environments (AWS GCP) or large-scale data pipelines
Background in deep learning probabilistic modeling or ensemble methods

$150000 - $180000 a year

Total Compensation at DELFI is a combination of salary bonus equity and benefits. Actual compensation packages are based on a wide array of factors unique to each candidate including but not limited to skillset years & depth of experience certifications & relevant education geography.

An Equal Opportunity Employer

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race religion color national origin gender sexual orientation age marital status veteran status or disability status.

We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.

About UsOur mission is to cure cancer through high performance accessible early cancer detection. That means saving lives.Delfi Diagnostics is a Johns Hopkins spinoff focused on the non-invasive detection of cancer at earlier stages when it is most curable. DELFI uses artificial intelligence and who...