Senior Software Engineer, AI and ML Platforms
Bio-Techne Corporation3 months ago
San Jose, CA, USASenior
Base Salary
$132k - $218k/yr
Responsibilities
- Lead the design and development of cloud-native, microservices-based backend systems.
- Build and deploy AI-powered services including LLM assistants, recommendations, and automation workflows.
- Develop scalable APIs integrating AI services with instrument software and customer-facing applications.
- Architect and implement RAG pipelines over scientific, operational, and customer data.
- Establish MLOps practices for model versioning, evaluation, monitoring, retraining, and reliable production operation.
- Collaborate with IT, data, infrastructure, product, scientific, and UX teams on AI platform standards and capabilities.
- Ensure reliability, observability, security, and performance of distributed production services.
- Drive standards for code quality, service ownership, and system architecture.
- Mentor junior engineers and contribute to design reviews, code reviews, technical decisions, and documentation.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field with 7+ years of relevant experience, or a master’s degree in Computer Science, AI/ML, or a related discipline with 5+ years of relevant experience, or an equivalent combination of relevant education and experience.
- Strong proficiency in Python, Java, or similar backend languages with hands-on microservices experience.
- Experience designing and operating cloud-native SaaS platforms and production-grade distributed systems.
- Experience building APIs with frameworks such as FastAPI, Flask, or Spring Boot.
- Hands-on experience integrating AI/ML or LLM-based services into real-world applications.
- Understanding of distributed systems, asynchronous processing, and service-to-service communication.
- Experience with Docker and CI/CD pipelines.
- Ability to implement ML or information-retrieval algorithms, including custom retrieval, ranking, re-ranking, embedding, chunking, evaluation, or inference optimization approaches.
- Track record of designing and building novel systems or components rather than primarily integrating off-the-shelf tools.
- Strong computer-science fundamentals including data structures and algorithmic complexity.
- Strong written and verbal communication skills across engineering and scientific teams.
- Preferred: experience with AWS or Azure, Kubernetes, ML lifecycle management, vector databases, RAG frameworks, scientific software, laboratory instrumentation, regulated environments, and multi-tenant SaaS systems.
Benefits
- Medical, dental, vision, life, short-term disability, long-term disability, pet, legal, and ID shield insurance benefits beginning on day one.
- 401(k) plans, employee stock purchase plan, HSA, FSA, and Dependent Care FSA.
- Mentorship, promotional opportunities, training and development, tuition reimbursement, and internship programs.
- Employee resource groups, volunteer paid time off, employee events, and charity drives.
- Accrued leave policy with paid holidays, paid time off, and paid parental leave.
- Hybrid work arrangement based at the San Jose, California site.
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