Senior ML Research Engineer — Predictive Modeling

About the Role

Biocient is a biotechnology company developing novel therapies for neurodegenerative diseases.

Biocient is seeking a Senior ML Research Engineer to build predictive models that help answer open biological and drug-development questions across our programs.

This is a hands-on role with broad ownership. You will build predictive models from the ground up and work directly with scientists to turn biological questions into quantitative predictions and actionable experimental decisions.The role sits at the intersection of machine learning, experimental biology, and drug development. You’ll work closely with our scientific team, using internal preclinical data, external datasets, and the scientific literature to build and validate models that inform program strategy.

Key Responsibilities

· Build and maintain the predictive roadmap for our programs.

· Build predictive models from the ground up. Design, train, validate, and iterate models using complex, multi-modal biological datasets. Apply modern ML approaches—including foundation-model methods where appropriate—while recognizing when simpler statistical or machine-learning approaches provide more reliable answers.

· Help design experiments around predictive questions. Work with the scientific team to translate biological questions into experimental designs, including cohort sizing, biomarker selection, sampling timepoints, and additional measurements needed to improve predictive power. Define analytical endpoints and Go/No-Go criteria before results are generated.

· Connect predictions to experimental results. Work with the team to establish a rigorous prediction → experiment → result → model-improvement loop, with appropriate validation, uncertainty assessment, and reproducibility.

· Map opportunities for platform expansion. Integrate internal data with external datasets and scientific literature to evaluate where the mechanism of our lead program may apply beyond other diseases.

· Support translational and regulatory development.

· Evaluate and operate external AI platforms. Frame scientific questions for external AI and drug-discovery platforms, critically evaluate their outputs, integrate useful findings with internal analyses, and maintain appropriate data-security standards when working with external systems.

Qualifications

Required:

· PhD, or equivalent industry research experience, in Machine Learning, Computer Science, Computational Science, Computational Biology, Bioinformatics, or a closely related quantitative discipline.

· 4+ years of relevant industry experience developing complex ML systems and building predictive models end to end

· Hands-on experience applying ML in biomedical research, biotechnology, pharmaceuticals, drug discovery, or life sciences.

· Strong expertise in modern machine-learning methods, including transformer architectures, self-supervised learning, and model pretraining/fine-tuning.

· Strong Python and PyTorch skills, including experience with scalable or distributed model training.

· Demonstrated ability to build modeling systems from the ground up rather than relying exclusively on off-the-shelf platforms.

· Experience extracting reliable signal from small, noisy, and/or multi-modal datasets, including appropriate validation and uncertainty assessment.

· Strong understanding of reproducible ML development, including version control, testing, documentation, model evaluation, and experiment tracking.

Strongly Preferred

· Experience working with preclinical or translational drug-development data.

· Familiarity with the IND process, preclinical-to-clinical translation, and FDA expectations.

· Experience integrating multiple data modalities, such as imaging, behavioral, tabular, omics, or longitudinal experimental data.

· Experience working directly with experimental scientists or wet-lab teams to design studies and interpret model outputs.

· Experience with foundation models or generative approaches applied to scientific or biomedical problems.

· Experience with AI-enabled drug-discovery platforms.

· Computational chemistry or cheminformatics experience.

· Drug-delivery, formulation, dose-response, PK/PD, or translational modeling experience.

Ideal Candidate

· A builder, not an advisor.

· ML-first with real biomedical grounding.

· Scientifically pragmatic.

· Comfortable with small-data biology.

· Works across disciplines.

Thrives with ownership and autonomy

This role is based in the Biocient office located in South Los Angeles, CA (Torrance). The successful candidate must be prepared to relocate if necessary to work out of the Los Angeles, CA office.

Compensation, Benefits & Perks

We offer a competitive total compensation package based on experience, qualifications, and the scope of the role.

Our benefits package is designed to support the health, well-being, and professional development of our team, including:

· Medical, dental, and vision coverage

· HSA

· 401(k) with a company contribution

· Generous paid time off

· 12 weeks of parental leave for eligible employees

· Training and professional development stipend

· Complimentary snacks, food, and beverages in the office

Benefit eligibility and offerings may vary by position and are subject to the terms of the applicable plans and company policy.

Candidates must be currently authorized to work in the United States, as visa or green card sponsorship is not available for this position.