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AI Omics Scientist III (Remote - US) at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for an . AI Omics Scientist III. in the . United States. .. This role offers an exciting opportunity to lead the design and deployment of advanced AI and machine learning models in the field of genomics and multi-omics research. You will play a pivotal part in developing predictive and generative models that accelerate discoveries in diagnostics, therapeutic development, and precision medicine. Working remotely with cross-functional teams of scientists, engineers, and clinicians, you will design scalable, production-ready AI pipelines, ensuring reproducibility, interpretability, and clinical relevance. This position combines high-level technical expertise with scientific creativity and leadership.. . Accountabilities:. Lead the design and implementation of machine learning models for multi-omics data analysis and clinical AI applications.. Integrate genomic, transcriptomic, proteomic, and clinical datasets to create scalable and interpretable AI solutions.. Develop and optimize deep learning architectures, including CNNs, RNNs, transformers, and LLMs, for predictive and generative modeling.. Deploy production-ready models using MLOps frameworks, containerized environments, and cloud-native platforms.. Mentor junior scientists, guide project direction, and ensure scientific rigor in all AI-driven research activities.. Collaborate with data engineering and clinical teams to translate computational models into actionable insights.. Publish research findings, contribute to open-source projects, and maintain high standards of transparency and reproducibility.. . PhD in Computational Biology, Bioinformatics, Artificial Intelligence, or a related field with 4+ years of experience, or MS with 6+ years of experience.. Strong expertise in . omics technologies. (RNA-seq, WGS, single-cell, proteomics) and biomedical informatics.. Deep understanding of . machine learning. , . statistical modeling. , and . biological data interpretation. .. Proficiency in . Python. and modern ML frameworks such as PyTorch, TensorFlow, JAX, or HuggingFace.. Experience with . GPU-based training. , distributed learning systems, and . cloud computing platforms. (AWS, GCP).. Skilled in . MLOps tools. (MLflow, DVC), . Docker/Kubernetes. , and . data pipeline orchestration. (Nextflow, Snakemake).. Experience with . foundational AI models. (BERT, BioBERT, GPT, AlphaFold, or domain-adapted LLMs).. Familiarity with . HIPAA-compliant and regulated environments. .. Excellent communication skills and proven ability to work across scientific and engineering disciplines.. Track record of . peer-reviewed publications. , conference presentations, or open-source contributions.. . Company Location: United States.