Pay Rate Low: 60 | Pay Rate High: 70
Our client is a leading biotech company seeking a highly motivated
AI/ ML Scientist to join their innovative research organization focused on applying artificial intelligence and machine learning to
drug discovery and molecular design.
Title: Machine Learning Scientist - Drug Discovery
Location: Remote - United States (PST preferred)
Schedule: Full-Time, 40 hours/week
Contract Duration: 12 months, with a strong possibility of extension
Employment Type: W-2 + Benefits
Compensation: $60-$70/hour, depending on experience and qualifications
Job Details: This role will focus on designing, developing, training, and deploying advanced machine learning models and computational engines that support
lab-in-the-loop molecular design and optimization. Areas of focus include sequence modeling, molecular structure, conformational ensembles, molecular property prediction, natural language processing, computer vision, and robotics. The successful candidate will work in a highly collaborative, multidisciplinary environment alongside
ML scientists, ML engineers, computational scientists, and drug design experts to develop next-generation solutions at the intersection of AI and life sciences.
Key Responsibilities - Design, develop, optimize, evaluate, and deploy advanced deep learning models, including large language models, multimodal transformers, and generative AI models.
- Build and optimize scalable data pipelines supporting machine learning and scientific applications.
- Optimize model training and inference for performance, scalability, and accuracy using multi-GPU and cloud-based infrastructure.
- Develop and maintain MLOps workflows covering model deployment, version control, monitoring, reproducibility, and ongoing model performance.
- Develop machine learning approaches that connect diverse datasets, including genomics, transcriptomics, imaging, molecular, and clinical data.
- Partner with scientists and engineers across disciplines to translate innovative machine learning methods into practical applications for drug discovery, disease research, and biomedical applications.
- Independently troubleshoot complex modeling, software, and infrastructure challenges and drive solutions from development through deployment.
Qualifications: - B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Computational Biology, Data Science, Statistics, Mathematics, or a related quantitative discipline.
- Must be authorized to work in the United States without current or future employer sponsorship.
- 1-5 years of relevant professional experience, including postdoctoral research where applicable.
- Strong foundation in data structures, algorithms, software engineering, and computational problem solving.
- Expert-level Python programming skills.
- Extensive experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow.
- Strong debugging and software development skills, with the ability to independently diagnose and resolve complex technical issues.
- Experience with large-scale or distributed model training, such as DDP, Ray, FSDP, or DeepSpeed.
- Experience with model deployment technologies such as Triton or ONNX.
- Experience working with cloud and/or GPU computing infrastructure.
- Hands-on experience with geometric deep learning, molecular cofolding models, neural force fields, or related scientific ML approaches is highly preferred.
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