AI Scientist, Agentic AI Discovery
$135,000–$160,000 year
On-siteParamus, New Jersey, United States
Job Summary
Evaluate emerging AI techniques, reproduce state-of-the-art research approaches, and build experimental prototypes for agentic AI systems and multi-agent workflows. Develop reusable AI architectures that integrate large language models to accelerate drug discovery and improve R&D efficiency. Collaborate with cross-functional teams to translate new ideas into scalable, production-ready solutions for pharmaceutical research. Requires a Master's degree in AI or related fields, 3+ years of experience, and strong Python skills with PyTorch or LangChain. Salary range $135,000 - $160,000. Visa sponsorship not available.
Required Qualifications
- Master's degree or higher in AI-related fields, Computer Science, Computational Biology, Bioinformatics, Machine Learning, or related disciplines
- At least 3 years of relevant experience in AI, machine learning, or applied research environments
- Applicants must be legally authorized to work in the United States
- Visa sponsorship is not available for this position
- Strong AI engineering and coding skills
- Hands-on experience building scalable and production-ready AI applications and systems
- Strong programming skills in Python
- Familiarity with modern AI/ML frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar ecosystems
- Ability to quickly learn and understand drug discovery and pharmaceutical R&D domains and connect them with AI solutions
- Professional-level English communication skills
Desired Qualifications
- Experience with AI-assisted development and rapid prototyping workflows ('vibe coding')
- Strong interest or hands-on experience in agentic AI systems, multi-agent orchestration frameworks, AI reasoning workflows, and LLM-based applications
- Experience working with biomedical or life science datasets and AI-driven scientific research platforms
- Experience working with modern large language model ecosystems, prompt engineering, retrieval-augmented generation (RAG), or AI workflow orchestration frameworks
- Experience applying AI within drug discovery, healthcare, or life sciences
- 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
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