Research Scientist, AI / ML Biologics

Real Staffing Group; Boston (MA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Retirement savings plans

Life and disability insurance

Paid leave

Job summary

Real Staffing Group is seeking a Research Scientist specializing in AI/ML for biologics. This fully remote contract role operates on Eastern Standard business hours and focuses on ASO and antibody discovery using advanced ML/AI methods.

You will build reproducible computational frameworks, curate datasets, and collaborate with experimental teams to validate predictions. Strong coding and teamwork are essential for success in this role.

Qualifications

• PhD with at least three years of industry experience in ML/AI for biologics.
• Strong background in oligonucleotide chemistry, antibody design, and modeling interactions.
• Expertise in probabilistic and deep learning models and modern DL frameworks.
• Proficient in Python, R, SQL; familiar with large-scale computing and cloud infra.

Responsibilities

• Develop sequence-aware predictive models to prioritize oligonucleotide therapeutics.
• Design and implement AI/ML methods for de novo antibody discovery and protein design.
• Fine-tune protein language models and develop generative design workflows.
• Deploy ML methods for multi-objective optimization of biologics and agents.

Skills

Python

R

SQL

PyTorch

TensorFlow

scikit-learn

JAX

Recurrent Neural Networks

Generative AI

Natural Language Processing

Education

PhD in computational biology or related field

Job description

An exciting opportunity is available for a Research Scientist specializing in AI and Machine Learning for biologics. This fully remote contract role requires working Eastern Standard business hours and offers the chance to contribute to cutting-edge advancements in antisense oligonucleotide (ASO) therapeutics and antibody discovery. The position focuses on integrating advanced ML and AI techniques to accelerate discovery and optimization across multiple biologic modalities.

The successful candidate will develop sequence-aware predictive models to prioritize oligonucleotide therapeutics based on exon-skipping response, extending these approaches across diverse ASO modalities. Responsibilities include designing and implementing AI/ML methods for de novo antibody discovery, fine-tuning protein language models, and developing generative protein design workflows. The role also involves deploying machine learning methods to support multi-objective optimization of antibodies, antigens, ADCs, and other biologic modalities.

Additional duties include building reproducible computational frameworks for biologics, curating and harmonizing datasets, defining robust sequence and structure features, and establishing benchmarks to assess model performance. The scientist will collaborate closely with experimental teams to validate predictions and adopt both proprietary and open-source tools to enhance modeling workflows. Maintaining a well-documented codebase and providing user guidance for cross-functional teams is essential.

Candidates should hold a PhD in Computational Chemistry, Computational Biology, Machine Learning, Biomedical or Chemical Engineering, with at least three years of relevant industry experience. A strong background in oligonucleotide chemistry, antibody design, and computational modeling of antibody-antigen interactions is required. Expertise in probabilistic and deep learning models, programming in Python, R, and SQL, and experience with modern deep learning frameworks are essential. Familiarity with large-scale computing, cloud infrastructure, and collaborative tools is expected. Strong communication skills and a commitment to teamwork and continuous learning are vital for success in this role.

Must-Have Skills: Python, R, SQL, PyTorch, Tensorflow, skikit-learn, JAX, Recurrent Neural Networks

Nice-to-Have Skills: AWS, database technologies, GitHub, GitLab, Docker, oligonucleotide chemistry, antibody design, structure prediction, design, large-scale computing, cloud infrastructures, data development, collaboration, continuous learning, Graph Neural Networks, Transformers, Natural Language Processing, Generative AI, computational modeling, machine learning

EOE Statement: Specialist Staffing Group is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

In addition to base pay, employees may be eligible for benefits such as health insurance, health savings accounts, retirement savings plans, life and disability insurance, and paid leave where required by applicable law. Eligibility may vary based on factors such as location and hire date and is subject to change.

To find out more about Real, please visit www.realstaffing.com