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Drug Discovery Ai Jobs (NOW HIRING)

Gidget Foundation Australia

$120 - $180/hr

AI DRUG DISCOVERY SCIENTIST Lantern Pharma is seeking talented and highly motivated AI Drug Discovery Scientists to develop innovative approaches supporting Lantern's internal drug development ...

Transcripta Bio

Scientist, Drug Discovery

Palo Alto, CA · On-site

$120 - $180/hr

About this position About Transcripta Bio Transcripta Bio is a preclinical-stage AI drug discovery company pioneering a patient-first approach to therapeutics. Headquartered in Palo Alto, CA, we have ...

Transcripta Bio

Scientist, Drug Discovery

Palo Alto, CA · On-site

About Transcripta Bio Transcripta Bio is a preclinical-stage AI drug discovery company pioneering a patient-first approach to therapeutics. Headquartered in Palo Alto, CA, we have built a proprietary ...

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How much do drug discovery ai jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for drug discovery ai in the United States is $61.42, according to ZipRecruiter salary data. Most workers in this role earn between $42.55 and $73.80 per hour, depending on experience, location, and employer.

What is Drug Discovery AI?

Drug Discovery AI refers to the use of artificial intelligence technologies to accelerate and enhance the process of discovering new pharmaceutical drugs. AI algorithms can analyze large datasets, predict the effectiveness of compounds, identify potential drug targets, and optimize clinical trial designs. By leveraging machine learning and deep learning, Drug Discovery AI helps reduce the time and cost involved in bringing new drugs to market while increasing the chances of finding effective therapies. This approach is transforming traditional drug discovery by improving accuracy and efficiency at every stage.

How does a Drug Discovery AI professional typically collaborate with multidisciplinary teams during a drug development project?

Drug Discovery AI professionals often work closely with biologists, chemists, pharmacologists, and data scientists to integrate computational models with experimental data. They collaborate by interpreting complex datasets, suggesting new molecular candidates, and refining predictive algorithms based on laboratory results. Effective communication and teamwork are essential, as AI insights must align with laboratory findings and regulatory requirements. Regular meetings and cross-functional discussions ensure that AI-driven recommendations are actionable and valuable to the overall drug development process.

What are the key skills and qualifications needed to thrive as a Drug Discovery AI specialist, and why are they important?

To thrive as a Drug Discovery AI Specialist, you need a strong background in computational biology, machine learning, and drug discovery processes, typically supported by an advanced degree in a relevant field. Expertise in programming languages like Python or R, experience with bioinformatics tools, and familiarity with platforms such as TensorFlow or PyTorch are commonly required. Strong problem-solving, collaboration, and communication skills help bridge gaps between multidisciplinary teams and translate complex data into actionable insights. These skills are crucial for accelerating drug development, improving accuracy, and enabling innovative solutions in pharmaceutical research.

What is the difference between Drug Discovery Ai vs Data Scientist in the pharmaceutical industry?

AspectDrug Discovery AiData Scientist
Required credentialsDegree in bioinformatics, computational biology, or related fields; knowledge of AI/MLDegree in computer science, statistics, or related fields; strong programming skills
Work environmentPharmaceutical R&D, biotech companies, research labsTech companies, research institutions, healthcare analytics
Employer and industry usagePrimarily in pharma and biotech for drug developmentAcross various industries including healthcare, finance, tech

Drug Discovery Ai specialists focus on applying AI and machine learning to identify new drug candidates, working mainly within pharmaceutical and biotech R&D environments. Data Scientists have broader roles across industries, analyzing large datasets to inform decision-making. While both roles require strong analytical skills and programming knowledge, Drug Discovery Ai professionals specialize in drug development processes, making their expertise more specific to the pharmaceutical industry.

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Drug Discovery Ai jobs near you
Infographic showing various Drug Discovery Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, 2% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $127,745 per year, or $61.4 per hour.

Agentic AI Scientist: Drug Discovery & Scientific Reasoning

Korean American Society in Biotech and Pharmaceuticals

Paramus, NJ • On-site

Other

Posted 17 days ago

Key responsibilities

  • Design, prototype, and advance AI systems for drug discovery and pharmaceutical research.

  • Evaluate emerging AI techniques, reproduce and extend state‑of‑the‑art research approaches, and develop reusable AI system architectures.

  • Collaborate with cross‑functional teams to identify opportunities where AI can improve discovery efficiency and insight generation.

Job description

SK Life Science AI Scientist, Agentic AI Discovery

AI Scientist, Agentic AI Discovery (1 position)

  • Work location: Paramus, New Jersey
  • Employment type: Full‑time
Role Description

The AI Scientist will design, prototype, and advance next‑generation AI systems for drug discovery and pharmaceutical research. This role focuses on exploring and applying emerging AI methodologies to accelerate scientific discovery, support data‑driven decision‑making, and improve R&D workflows across drug discovery programmes.

The AI Scientist will contribute to the development of agentic AI systems, multi‑agent workflows, and AI‑driven scientific reasoning platforms that integrate advanced machine learning, large language models, and biomedical research applications. The role requires a strong balance of AI research understanding, hands‑on prototyping ability, and engineering execution to rapidly evaluate new ideas and translate them into scalable, production‑ready solutions.

Responsibilities include evaluating emerging AI techniques, reproducing and extending state‑of‑the‑art research approaches, building experimental prototypes, and developing reusable AI system architectures that can support scientific exploration and therapeutic discovery. The AI Scientist will collaborate closely with cross‑functional research and engineering teams to identify high‑impact opportunities where AI can meaningfully improve discovery efficiency and insight generation. The ideal candidate is highly technical, deeply curious about frontier AI capabilities, and excited about applying advanced AI systems in real‑world drug discovery environments.

Qualifications
  • Education: Master’s degree or higher in AI‑related fields, Computer Science, Computational Biology, Bioinformatics, Machine Learning, or related disciplines.
  • Experience: At least 3 years of relevant experience in AI, machine learning, or applied research environments.
  • Work Authorization: Applicants must be legally authorized to work in the United States. Visa sponsorship is not available for this position.
  • AI Engineering Skills: Strong AI engineering and coding skills, with hands‑on experience building scalable and production‑ready AI applications and systems.
  • AI‑Assisted Development: Experience with AI‑assisted development and rapid prototyping workflows (“vibe coding”) is highly desirable.
  • Agentic AI: Strong interest or hands‑on experience in agentic AI systems, multi‑agent orchestration frameworks, AI reasoning workflows, and LLM‑based applications.
  • Biomedical Research: Experience working with biomedical or life science datasets and AI‑driven scientific research platforms is highly desirable.
  • Generative AI & LLMs: Experience working with modern large language model ecosystems, prompt engineering, retrieval‑augmented generation (RAG), or AI workflow orchestration frameworks is a plus.
  • Technical Stack: Strong programming skills in Python and familiarity with modern AI/ML frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar ecosystems.
  • Domain Knowledge: Ability to quickly learn and understand drug discovery and pharmaceutical R&D domains and connect them with AI solutions.
  • Other Skills: Strong strategic thinking, problem‑solving, interpersonal, and communication skills. Ability to excel in a fast‑paced, startup‑like environment with a focus on innovation and adaptability.
  • Track Record: Experience applying AI within drug discovery, healthcare, or life sciences is advantageous.
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