Bio-Rad LaboratoriesRemote
Sr. Manager, Applied AI Engineering
United States of America
Full-time
2 weeks ago
$143,000 - $247,000 USD
H1B Sponsor Likely
Key skills
AIMachine LearningMLGenerative AILLMOpenAIPyTorchTensorFlowscikit-learnHugging FaceLangChainMLOpsAWSAzureGCPCI/CDMentoringCommunication
About this role
Bio-Rad Laboratories is focused on advancing the discovery process and transforming the fields of science and healthcare. The Senior Manager, Applied AI Engineering will lead the technical execution of AI and Machine Learning solutions across global business functions, collaborating with various teams to deliver impactful AI-powered experiences.
Responsibilities:
- Architect intelligent systems by designing and deploying scalable AI/ML solutions—including multi-agent frameworks, generative AI applications, and decision-optimization engines—that solve complex business challenges across global operations
- Drive innovation to production by leading proof-of-concepts through full deployment, managing the complete AI lifecycle from model development through MLOps, LLMOps, and continuous performance monitoring
- Build for reliability at scale by implementing feedback loops, drift detection, and hallucination monitoring systems that ensure AI solutions remain accurate, explainable, and trustworthy in production
- Develop future AI leaders by mentoring a team of AI and ML engineers, fostering a culture of innovation, technical excellence, and continuous learning
Requirements:
- 10+ years of progressive experience in software engineering, data science, or AI/ML roles, with 5+ years designing and deploying ML models in production environments—plus a proven track record leading technical teams and technology pilots
- Expert-level proficiency with ML frameworks (TensorFlow, PyTorch, scikit-learn) and generative AI frameworks (LangChain, LlamaIndex, Hugging Face), along with hands-on experience integrating LLM APIs from providers like OpenAI, Gemini and Anthropic
- Strong cloud platform experience (AWS, Azure, or GCP) with knowledge of containerization, CI/CD pipelines, and MLOps practices for deploying performant, cost-effective AI infrastructure
- A passion for turning emerging technologies into practical enterprise solutions, combined with strong communication skills to align technical initiatives with strategic business goals