AI Engineer III – Computational Drug Discovery AI Model Development

Sam Quest Solutions Inc. is hiring an AI Engineer III to support computational drug discovery through AI model development, fine-tuning, and rigorous benchmarking. This is a remote role with an hourly compensation range of $70.00 to $100.00, focused on building practical workflows that connect protein and ligand inputs to reliable 3D structure and affinity predictions.

What you’ll build and improve

You will develop and evaluate AI/ML models for multiple lead optimization programs, including the data and tooling needed to move from sequence-level inputs to single prediction outputs. The goal is to produce accurate results while assessing model applicability domains, performance tradeoffs, and runtime efficiency.

Responsibilities

• Fine-tune pre-trained foundation models (for example, Boltz-2 and AISB) using domain-specific project data
• Compile and curate datasets across multiple LO projects, including experimental protein-ligand complex structures and potency or affinity measurements
• Analyze dataset variation to test and challenge where models do and do not apply (applicability domains)
• Benchmark performance against established methods such as DeepAutoQSAR, GatorAffinity, MPNN, MM-GBSA, FEP, and others as appropriate
• Compare pose generation approaches, including co-folder pose generation versus docking-based methods
• Measure ranking quality using recall and precision with project-specific thresholds, and build model rankings based on confidence and applicability domain
• Decide deployment strategy for whether a single fine-tuned co-folder model can cover multiple projects or whether project-specific models are required
• Design an automated end-to-end workflow that produces single predictions in under a minute using GPU or CPU resources

Requirements

• Strong experience in machine learning, computational chemistry, cheminformatics, or related scientific data science domains
• Experience training and fine-tuning models on domain-specific scientific datasets
• Knowledge of 3D modeling workflows, pose generation, or docking-based comparison studies
• Working understanding of benchmarking methodologies and model performance evaluation
• Strong Python skills plus scripting and automation experience
• Ability to design reproducible, scalable workflows with runtime efficiency in mind
• Collaboration and communication skills across scientific and technical teams

Tools and technologies

Python, GPU, CPU, Boltz-2, AISB, DeepAutoQSAR, GatorAffinity, MPNN, MM-GBSA, FEP.

Location: Remote

Compensation: USD 70 - 100 per hour