Machine Learning Engineer

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Artificial Intelligence, Computational Sciences & Engineering Staffing (US, UK & EU) at Skills Alliance

Develop novel cell embeddings that integrate multi-omics foundation models—transcriptomics, proteomics, epigenomics, and metabolomics—to capture comprehensive cellular signatures. Your work will enable precise predictions of drug effects, driving innovation in drug discovery.

Key Responsibilities:

1. Model Development:Design deep learning models integrating diverse omics data to create robust cell embeddings for digital twin technology.
2. Multi-Omics Integration:Develop and refine foundation models across omics platforms into a unified cell representation.
3. Collaboration:Work with experts in bioinformatics, drug discovery, and AI to validate models and integrate multi-modal data.
4. Client & Partner Engagement:Support product and service teams in translating AI models into real-world drug discovery applications.
5. Research Leadership:Stay at the forefront of AI and omics advancements, contributing to scientific publications and innovation.

Preferred Qualifications:

1. PhD/Postdoc in Computer Science (or related fields):Publications in top ML conferences (e.g., NeurIPS, ICLR, ICML, CVPR).
2. Strong ML/Applied Math Background:Expertise in advanced ML techniques.
3. Deep Learning Experience:Building and scaling AI models for omics or high dimensional biological data.
4. Collaborative Mindset:Track record of success in interdisciplinary teams and cross-functional projects.

Seniority level

Entry level

Employment type

Full-time

Job function

Research and Science

Industries

Biotechnology Research and Pharmaceutical Manufacturing

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