Jobgether

Compensation

Full Description

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description 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. • 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. Qualifications • 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. Benefits • Competitive annual salary ranging from $140,000 to $175,000, plus a Short-Term Incentive Plan (10% of annual earnings). • Full remote work flexibility within the United States (PST preferred). • Comprehensive medical, dental, and vision insurance. • 401(k) plan with company match and flexible spending accounts (FSA). • Generous paid time off (PTO) and paid sick leave. • Continuous learning and professional development support. • Inclusive, collaborative culture that values scientific innovation and open exchange of ideas. • Equal opportunity employer supporting second-chance employment and fair hiring practices. Company Description Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. • Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. • It compares your profile to the job’s core requirements and past success factors to determine your match score. • Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. • When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest!