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
Responsibilities:
AI Operations, Contractor Delivery & Hands-On Technical Work- Works as part of a team responsible for managing contractors, technical delivery partners, and AI workstreams across applied AI initiatives.
- Supports contractor onboarding, work planning, technical direction, delivery coordination, quality review, and accountability for assigned work.
- Provides hands-on technical direction for AI prototypes, model development, application patterns, data pipelines, and production AI systems.
- Reviews technical designs, architecture decisions, model evaluation plans, code quality, implementation tradeoffs, and production-readiness.
- Contributes to prototypes, proof-of-concepts, notebooks, design documents, technical spikes, and code reviews when needed.
- Promotes scientific rigor, reproducibility, engineering excellence, responsible AI practices, documentation, and maintainable delivery patterns.
- Leads development, evaluation, deployment, and scaling of AI capabilities supporting research, development, clinical, regulatory, safety, and enterprise use cases.
- Applies product thinking to ensure AI solutions address clear user needs, workflow realities, business priorities, adoption goals, and measurable outcomes.
- Partners with Product Management & Experiences to understand user needs, prioritize opportunities, define success metrics, and support adoption.
- Uses experimentation, user feedback, benchmarking, and iterative delivery to validate assumptions and improve AI capabilities over time.
- Identifies opportunities to use emerging AI technologies to accelerate scientific discovery and operational effectiveness.
- Uses experimentation, user feedback, benchmarking, and iterative delivery to validate assumptions and improve AI capabilities over time.
- Identifies opportunities to use emerging AI technologies to accelerate scientific discovery and operational effectiveness.
- Designs and guides AI solution architectures for assigned projects and business domains.
- Guides development of Retrieval-Augmented Generation systems, agentic workflows, prompt and context engineering patterns, evaluation harnesses, model monitoring, and Langfuse-based observability.
- Sets expectations for production-quality code, automated testing, version control, reproducible experiments, scalable deployment patterns, and operational documentation.
- Develops reusable AI frameworks, tools, accelerators, platforms, and services that enable faster delivery across Research, Development, and enterprise functions.
- Helps troubleshoot complex issues across data quality, model behavior, latency, reliability, security, scalability, cost, compliance, and user experience.
- Responsible AI, Governance & Production Operations
- Ensures AI solutions follow applicable governance, privacy, security, regulatory, and responsible AI expectations.
- Implements practical approaches for Large Language Model evaluation, groundedness assessment, hallucination risk management, traceability, and quality measurement.
- Uses platforms such as Langfuse or equivalent approved tooling for LLM tracing, debugging, prompt and response analysis, observability, evaluation workflows, and production monitoring.
- Supports Machine Learning Operations, Large Language Model Operations, continuous integration and delivery, model monitoring, observability, and operational support practices.
- Collaborates with Product Management & Experiences, Business Delivery Excellence, Enterprise AI & Governance Excellence, ARC translational AI teams, and Development partners.
- Partners with scientists, therapeutic area leaders, clinical teams, regulatory functions, Information Technology, Privacy, and Drug Development Systems to prioritize high-impact AI opportunities.
- Communicates technical concepts, product strategy, risks, tradeoffs, and delivery progress clearly to technical and non-technical audiences.
- Contributes to ARC initiatives that advance AI capabilities, governance, adoption, product innovation, and operational excellence.
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Statistics, Engineering, or related discipline with 4+ years of relevant industry experience.
- MS in a related discipline with 8+ years of relevant experience.
- BS in a related discipline with 10+ years of relevant experience.
- Demonstrated expertise in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Generative AI, or related disciplines.
- Experience guiding technical contributors, contractors, or cross-functional project teams, including technical direction, coaching, delivery oversight, and quality review.
- Hands-on experience building, evaluating, and deploying AI or machine learning solutions in applied research, product, or enterprise environments.
- Strong hands-on programming skills in Python and practical experience with modern AI and machine learning libraries such as PyTorch, TensorFlow, or equivalent approved technologies.
- Experience in clinical trial operational data, real-world data, and supporting trial feasibility, site selection and forecasting.
- Experience building Generative AI applications with LangChain, LangGraph, Semantic Kernel, Microsoft Agent Framework, Langfuse, AWS-native AI services, Microsoft Azure services where appropriate, or equivalent approved enterprise technologies.
- Experience designing and implementing Retrieval-Augmented Generation systems, including chunking, embeddings, vector search, reranking, grounding, citation patterns, retrieval evaluation, and response quality measurement.
- Experience developing agentic AI workflows, tool-use patterns, orchestration approaches, guardrails, human-in-the-loop review models, prompt engineering, context engineering, and model evaluation techniques.
- Experience with APIs, microservices, notebooks, Git-based development, automated tests, containerization, deployment patterns, monitoring, and operational support for AI systems.
- Experience deploying AI solutions in regulated environments with appropriate governance, security, privacy, compliance, scalability, reliability, and responsible use controls.
- Strong knowledge of Generative AI, Large Language Models, advanced analytics, and applied machine learning.
- Experience in one or more of the following areas: foundation models, multimodal AI, agentic AI systems, scientific machine learning, knowledge graphs, Retrieval-Augmented Generation, Natural Language Processing, or advanced deep learning.
- Experience designing evaluation frameworks for Large Language Models, including accuracy, groundedness, hallucination risk, robustness, latency, cost, safety, user acceptance, and Langfuse-based tracing or evaluation workflows.
- Experience translating research and experimental AI concepts into scalable production capabilities.
- Extensive experience with Machine Learning Operations, Large Language Model Operations, continuous integration and delivery, cloud-based AI infrastructure, observability, model monitoring, and automated testing.
- Experience working with Amazon Web Services and Microsoft Azure, including AI, machine learning, data, security, and scalable compute services.
- Experience using Langfuse or equivalent approved tooling for LLM application tracing, debugging, prompt and response analysis, production observability, evaluation workflows, and quality measurement.
- Experience applying software engineering methodologies, scalable AI architectures, reusable components, documentation standards, and maintainable production systems.
- Demonstrated product mindset with experience translating technical capabilities into solutions that deliver measurable user and business value.
- Experience partnering with product managers, designers, engineers, scientists, and business stakeholders throughout the product lifecycle.
- Proven ability to align technical strategies with business goals and communicate complex concepts effectively to non-technical stakeholders.
- Demonstrated success working with multidisciplinary teams, managing contractors or technical delivery partners, and mentoring technical contributors.
- Ability to balance experimentation and innovation with execution, adoption, operational impact, and measurable outcomes.
- Proven ability to influence programs, projects, and initiatives in a matrixed environment.
- Experience applying AI in life sciences, drug development, clinical research, healthcare, or regulated industries.
- Experience contributing to publications, patents, open-source projects, technical communities, or internal technical standards.
- Strong analytical, communication, organizational, and stakeholder management skills.
- Ability to travel as needed.
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 [email protected] 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.
Skills Required
- PhD in CS/AI/ML/Computational Biology/Statistics/Engineering or related with 4+ years industry experience (or MS with 8+ years or BS with 10+ years)
- Demonstrated expertise in AI, Machine Learning, Deep Learning, NLP, or Generative AI
- Experience guiding technical contributors, contractors, or cross-functional teams with technical direction and delivery oversight
- Hands-on experience building, evaluating, and deploying AI/ML solutions in applied research, product, or enterprise environments
- Strong programming skills in Python
- Practical experience with modern ML libraries such as PyTorch or TensorFlow
- Experience building Generative AI applications (LangChain, LangGraph, Semantic Kernel, Microsoft Agent Framework, or equivalent)
- Experience with Langfuse or equivalent tooling for LLM tracing, debugging, observability, and evaluation
- Designing and implementing Retrieval-Augmented Generation systems, including embeddings, chunking, vector search, reranking, grounding, and evaluation
- Experience developing agentic AI workflows, prompt/context engineering, guardrails, and human-in-the-loop review models
- Experience with APIs, microservices, notebooks, Git-based development, automated tests, containerization, deployment, monitoring, and operational support
- Experience deploying AI solutions in regulated environments with governance, security, privacy, compliance, and responsible AI controls
- Experience with AWS and Microsoft Azure AI, ML, data, security, and scalable compute services
- Ability to communicate technical concepts to technical and non-technical stakeholders and apply product thinking
- Experience in clinical trial operational data, real-world data, trial feasibility, site selection and forecasting
- Experience applying AI in life sciences, drug development, clinical research, or regulated industries
- Contributions to publications, patents, open-source projects, or technical communities
- Ability to travel as needed
Gilead Sciences Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Gilead Sciences and has not been reviewed or approved by Gilead Sciences.
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Fair & Transparent Compensation — Pay is considered competitive and fair relative to roles, frequently cited as a standout strength. Feedback suggests compensation compares well within biotech and is a notable reason employees feel valued.
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Equity Value & Accessibility — Stock awards and an employee stock purchase program are consistently described as meaningful parts of total compensation. Equity components are seen as accessible and enhance long‑term wealth building.
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Retirement Support — A strong company 401(k) match with immediate vesting is often singled out as a differentiator. This support is perceived to significantly boost long‑term financial security.
Gilead Sciences Insights
What We Do
The way we see it, the impossible is not impossible. It’s simply what hasn’t been achieved yet. For more than 30 years, we’ve pursued it, chased it down, tackled it for answers and surrounded it for a way in. We have worked tirelessly to bring forward medicines for life-threatening diseases. Creating Possible drives everything we do. It’s evident in our mission and core values. This is how we built a culture of excellence that is fueled by a passion for improving lives of people around the world. For us, nothing is impossible – because of the people we work with, the communities we stand with and the partners we push forward with. Our ~12,000 employees band together through science, grit, compassion and courage to prove the impossible wrong. At Gilead, the tangible results of your contributions are evident. Where every individual matters. Where all employees can enhance their skills through ongoing development. And where we start every day with one question: “What’s next?” Social Media Guidelines: https://gilead.inc/3t1m7d5
