Phenomics Health
We are seeking an experienced AI Engineer based in southeastern Michigan to join our team as we develop and deploy cutting‑edge artificial intelligence solutions that can make a meaningful impact in healthcare and life sciences. This is a hands‑on role where you’ll wear multiple hats – researcher, engineer, problem‑solver, and collaborator.
Key Responsibilities
Design and implement production‑ready AI agents that interact with scientific data, tools, and APIs to support discovery and decision‑making.
Develop and maintain AI pipelines for biological data analysis, including genomics, metabolomics, and clinical datasets.
Build and fine‑tune foundation models (language, multimodal, generative) for biological and clinical data.
Prototype quickly, test often, and iterate toward scalable solutions.
Push forward best practices for model evaluation, interpretability, and deployment in a regulated industry.
Build scalable machine learning infrastructure that can handle large‑scale biological datasets.
Implement MLOps practices including model versioning, monitoring, and automated retraining.
Keep pace with the latest in generative AI, multimodal learning, and agent frameworks.
Ensure AI systems meet regulatory compliance requirements relevant to biotech and healthcare.
Cross‑Functional Collaboration
Collaborate with product management and scientific team to identify high‑impact opportunities for AI integration.
Work closely with bioinformaticians, data scientists, and domain experts to translate scientific requirements into technical solutions.
Ensure AI implementations align with FDA and other regulatory frameworks.
Required Qualifications Technical Expertise
3‑5 years of experience in machine learning engineering with production deployment experience.
Strong programming skills in Python and relevant ML frameworks and tools (TensorFlow, PyTorch, Hugging Face, LangChain, or equivalent).
Experience creating AI agents and multi‑agent systems.
Hands‑on experience building or fine‑tuning large models (transformers, diffusion, multimodal).
Proficiency in data engineering tools and techniques for handling large‑scale datasets.
Practical experience deploying models as services or agents in production.
2+ years of experience applying AI/ML in biotech, pharmaceutical, or healthcare domains.
Familiarity with biological data types and analysis pipelines (genomics, transcriptomics, clinical data).
Understanding of regulatory requirements for AI in healthcare/biotech (FDA guidelines, etc.).
Experience with bioinformatics tools and databases is highly preferred.
Communication
Strong problem‑solving abilities with experience in research‑oriented environments.
Excellent communication skills with ability to present to both technical and business audiences.
Experience working in startup or fast‑paced environments.
Preferred Qualifications
Bachelor’s or master’s degree in computer science, Machine Learning, or related technical field.
Experience with biological sequence modeling or scientific foundation models.
Knowledge of agent‑based modeling or multi‑agent systems.
Familiarity with computational biology tools and databases.
Experience with model compression, quantization, or efficient deployment techniques.
Publications or projects demonstrating AI applications in scientific domains.
Location: Based in Plymouth, Michigan, with hybrid work flexibility.
About Us We are an Artificial Intelligence‑Powered Patient‑Focused Precision Medicine company translating patient‑specific and population‑based big medical data into novel pharmacological clinical treatment decision support products and services.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
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Key Responsibilities
Design and implement production‑ready AI agents that interact with scientific data, tools, and APIs to support discovery and decision‑making.
Develop and maintain AI pipelines for biological data analysis, including genomics, metabolomics, and clinical datasets.
Build and fine‑tune foundation models (language, multimodal, generative) for biological and clinical data.
Prototype quickly, test often, and iterate toward scalable solutions.
Push forward best practices for model evaluation, interpretability, and deployment in a regulated industry.
Build scalable machine learning infrastructure that can handle large‑scale biological datasets.
Implement MLOps practices including model versioning, monitoring, and automated retraining.
Keep pace with the latest in generative AI, multimodal learning, and agent frameworks.
Ensure AI systems meet regulatory compliance requirements relevant to biotech and healthcare.
Cross‑Functional Collaboration
Collaborate with product management and scientific team to identify high‑impact opportunities for AI integration.
Work closely with bioinformaticians, data scientists, and domain experts to translate scientific requirements into technical solutions.
Ensure AI implementations align with FDA and other regulatory frameworks.
Required Qualifications Technical Expertise
3‑5 years of experience in machine learning engineering with production deployment experience.
Strong programming skills in Python and relevant ML frameworks and tools (TensorFlow, PyTorch, Hugging Face, LangChain, or equivalent).
Experience creating AI agents and multi‑agent systems.
Hands‑on experience building or fine‑tuning large models (transformers, diffusion, multimodal).
Proficiency in data engineering tools and techniques for handling large‑scale datasets.
Practical experience deploying models as services or agents in production.
2+ years of experience applying AI/ML in biotech, pharmaceutical, or healthcare domains.
Familiarity with biological data types and analysis pipelines (genomics, transcriptomics, clinical data).
Understanding of regulatory requirements for AI in healthcare/biotech (FDA guidelines, etc.).
Experience with bioinformatics tools and databases is highly preferred.
Communication
Strong problem‑solving abilities with experience in research‑oriented environments.
Excellent communication skills with ability to present to both technical and business audiences.
Experience working in startup or fast‑paced environments.
Preferred Qualifications
Bachelor’s or master’s degree in computer science, Machine Learning, or related technical field.
Experience with biological sequence modeling or scientific foundation models.
Knowledge of agent‑based modeling or multi‑agent systems.
Familiarity with computational biology tools and databases.
Experience with model compression, quantization, or efficient deployment techniques.
Publications or projects demonstrating AI applications in scientific domains.
Location: Based in Plymouth, Michigan, with hybrid work flexibility.
About Us We are an Artificial Intelligence‑Powered Patient‑Focused Precision Medicine company translating patient‑specific and population‑based big medical data into novel pharmacological clinical treatment decision support products and services.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
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