
Biopharmaceutical company
Senior Scientist, Machine Learning (Biologics Design)
At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.
Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.
We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.
Job Description
Gilead’s Research Data Sciences is seeking a Senior Scientist to develop and apply machine learning methods for the design and optimization of large molecules, including antibodies, multispecifics, and other complex formats. This role sits at the intersection of machine learning, structural biophysics, and protein therapeutics, with direct impact on lead optimization and pipeline programs.
You will build predictive and generative models that guide sequence and structure design, integrate diverse experimental and structural datasets, and work in close partnership with experimental teams. A key emphasis is data-efficient learning, using limited and noisy experimental data to make high-confidence design decisions.
Key Responsibilities
- Develop and apply ML models for biologics design, including sequence-to-function, structure-aware, and multi-objective models that support lead optimization decisions
- Implement data-efficient modeling strategies (e.g., active learning, Bayesian optimization, experimental design) to prioritize designs and guide iterative experimentation
- Apply and extend modern deep learning approaches relevant to biologics, including protein language models, geometric deep learning, and generative methods (e.g., diffusion, inverse folding, ProteinMPNN-style approaches)
- Perform structure-based modeling and analysis of antibodies and multispecifics.
- Partner closely with protein therapeutics, structural biology, assay, and engineering teams to translate computational results into experimental decisions
Required Qualifications
- PhD in Computational Biology, Computer Science, Mathematics, Physics, Chemistry, Bioengineering, or a related quantitative discipline, and 2+ years of experience
- Strong proficiency in Python and deep learning frameworks such as Py Torch (and/or JAX), plus standard scientific libraries (Num Py, pandas, etc.)
- Demonstrated experience architecting, training, and evaluating deep learning models, such as representation learning, multimodal learning, geometric deep learning, or generative modeling
- Solid understanding of protein structure, antibody architecture, and biophysical principles relevant to large-molecule therapeutics
- Demonstrated research productivity (e.g., first-author publications), and ability to communicate clearly to diverse audiences
Preferred Qualifications
- Experience with molecular modeling or simulations (e.g., Amber, OpenMM, Rosetta, CHARMM, coarse-grained or multi-scale methods)
- Experience developing production-grade ML tooling: experiment tracking, model registries, CI/testing, containerization, workflow orchestration
- Prior industry experience in biologics discovery, protein engineering, or therapeutic protein development
The salary range for this position is: $169,320.00 - $219,120.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans.
For additional benefits information, visit:
https://www.gilead.com/careers/compensation-benefits-and-wellbeing
- Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
For jobs in the United States:
Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact [Applicant Accommodations@gilead.com](mailto:Applicant Accommodations@gilead.com) for assistance.
For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster.
NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT
YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT
Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, (c) consistent with the legal duty to furnish information; or (d) otherwise protected by law.
Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team.
Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion.
For Current Gilead Employees and Contractors:
Please apply via the Internal Career Opportunities portal in Workday.
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Gilead Sciencesについて

Gilead Sciences
PublicGilead Sciences, Inc. is an American biopharmaceutical company headquartered in Foster City, California, that focuses on researching and developing antiviral drugs used in the treatment of HIV/AIDS, hepatitis B, hepatitis C, influenza, and COVID-19, including ledipasvir/sofosbuvir and sofosbuvir.
10,001+
従業員数
Foster City
本社所在地
$85B
企業価値
レビュー
10件のレビュー
3.7
10件のレビュー
ワークライフバランス
2.8
報酬
4.2
企業文化
3.1
キャリア
3.4
経営陣
2.5
65%
知人への推奨率
良い点
Good people and friendly colleagues
Competitive compensation and benefits
Career growth opportunities
改善点
Management issues and difficult leadership
Poor work-life balance
Toxic culture and workplace stress
給与レンジ
44件のデータ
Junior/L3
Senior/L5
Senior
Director
L3
L5
Junior/L3 · Data Science Associate
1件のレポート
$100,887
年収総額
基本給
$77,605
ストック
-
ボーナス
-
$100,887
$100,887
面接レビュー
レビュー42件
難易度
3.2
/ 5
期間
14-28週間
内定率
41%
体験
ポジティブ 64%
普通 21%
ネガティブ 15%
面接プロセス
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
よくある質問
Technical skills
Past experience
Team collaboration
Problem solving
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