1 день назад
Senior Software Engineer, AI and ML Platforms
132 400 - 217 600$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Software Engineer, AI and ML Platforms (AI/ML, cloud-native SaaS): Building scalable backend microservices and AI-powered services for scientific software products with an accent on LLM assistants, REST and event-driven APIs, and RAG pipelines. Focus on designing production-grade distributed systems, implementing MLOps for model reliability, and integrating AI capabilities into regulated scientific environments.
Location: Hybrid position based out of the San Jose, California site, United States
Salary: $132,400–$217,600 annually
Company
develops software and instrumentation solutions that help scientists generate accurate, reproducible biological data for life sciences and clinical diagnostics.
What you will do
- Lead the design and development of cloud-native, microservices-based backend systems for software products.
- Build and deploy AI-powered services, including LLM assistants, recommendations, and automation workflows.
- Develop scalable REST and event-driven APIs integrating AI services with instrument software and customer-facing applications.
- Architect RAG pipelines over scientific, operational, and customer data.
- Establish MLOps practices for model versioning, evaluation, monitoring, retraining, and reliable production operation.
- Drive architecture, reliability, observability, security, performance, documentation, code quality, and mentoring across engineering and scientific teams.
Requirements
- B.S. with 7+ years of relevant experience, M.S. with 5+ years, or an equivalent combination of education and experience.
- Strong proficiency in Python, Java, or a similar backend language, with hands-on microservices experience.
- Experience designing and operating cloud-native SaaS platforms and RESTful APIs using FastAPI, Flask, Spring Boot, or similar frameworks.
- Experience integrating AI/ML or LLM services into real-world applications and implementing information-retrieval or ML algorithms.
- Understanding of distributed systems, asynchronous processing, service-to-service communication, Docker, and CI/CD pipelines.
- Strong computer-science fundamentals, including data structures, algorithmic complexity, and system design.
Nice to have
- Experience with AWS or Azure, Kubernetes, and multi-service deployment strategies.
- Experience managing the ML lifecycle, including feature engineering, training, validation, deployment, and maintenance.
- Experience with vector databases such as pgvector, FAISS, or Pinecone and RAG frameworks such as LangChain or LlamaIndex.
- Exposure to scientific software, laboratory instrumentation, regulated GxP environments, or multi-tenant SaaS licensing.
Culture & Benefits
- Medical, dental, vision, life, disability, pet, legal, and identity protection insurance benefits begin on day one.
- Benefits include 401(k), ESPP, HSA, FSA, dependent care FSA, paid holidays, paid time off, and paid parental leave.
- Mentorship, training and development, tuition reimbursement, and promotional opportunities support career growth.
- Employee resource groups, volunteer paid time off, employee events, and charity drives support an inclusive workplace.
- fosters empowerment and innovation and is an E-Verify employer in the United States.
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