Key Responsibilities · Build, train, and optimize ML/GenAI models (RAG, embeddings, LLM integrations) · Develop production-grade services using Python + FastAPI · Deploy ML workloads on GCP (Cloud Run, BigQuery, GCS, Pub/Sub) · Design scalable APIs and lead API integrations · Contribute to Cloud Migration and ML platform modernization · Implement CI/CD for ML pipelines and microservices · Apply OOPS principles for clean, modular design · Work collaboratively with Product, Data Engineering, and Infra teams Must-Have Skills · Strong hands-on Python · GenAI / LLM development · GCP – ML pipelines and deployment services · FastAPI · CI/CD (Jenkins / GitHub Actions) · API Development & API Management · Solid OOPS fundamentals Nice-to-Have · Docker / Kubernetes · Vector DBs (Pinecone / FAISS / Chroma) · Terraform / IaC

About Quickhyre AI

QuickHyre AI is an online job portal and HRMS software platform for hiring and workforce management, trusted by over 10 million active users. It connects freshers and experienced professionals across all career levels with verified job opportunities, while enabling companies to hire, onboard, and manage employees through a single system. Candidates use QuickHyre AI to search and apply for jobs across entry-level, mid-level, and senior roles, including internships and contract positions across tech and non-tech domains. Employers use QuickHyre AI as a hiring platform, applicant tracking system (ATS), and HRMS to post jobs, screen candidates, manage applications, onboard hires, and maintain employee records. Built for startups, growing companies, and enterprises, QuickHyre AI reduces irrelevant applications, improves hiring efficiency, and simplifies HR operations. By combining job discovery, online recruitment, and HR management software, QuickHyre AI supports end-to-end talent acquisition and workforce administration at scale.