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Qubika Tech Stack
AI transformation and MLOps services for enterprise data teams
Qubika is a 501–1,000-person services firm helping enterprises build AI-native operations. The stack reveals a deep ML engineering maturity: PyTorch, TensorFlow, scikit-learn, LangChain, Hugging Face, plus production infrastructure (Kubernetes, Airflow, dbt, Databricks). Active projects span MLOps architecture, LLM reasoning applications, and chip-simulation diagnostics—indicating heavy lifting on data pipelines and AI agent frameworks. Hiring is accelerating with 17 roles posted in 30 days, skewed toward senior engineers and data practitioners, matching internal pain around scaling ML teams and building repeatable MLOps infrastructure.
Tech Stack 92 technologies
Core StackPython Ruby Go Kubernetes GitHub Actions Datadog Sentry AWS Terraform Helm Ansible PyTorch TensorFlow scikit-learn Docker LangChain Hugging Face Apache Spark Apache Airflow dbt Databricks Bash Karpenter KEDA Vault Spacelift Azure GCP OpenAI API SQL+58 more
ReplacingRedshift
What Qubika Is Building
◆Challenges
- Improving win rates
- Increasing pull-through revenue
- Institutionalizing vertical ip
- Building mlops infrastructure
- Scaling ml teams
- Migrating datasets from redshift to databricks
- Validating migrated data consistency
- Data infrastructure improvement
- Advanced analytics support
- Improving employee lifecycle processes
▲Active Projects
- Develop repeatable accelerators and domain workflows
- Build standardized discovery frameworks
- Mlops infrastructure and architecture
- Internal ai solutions and reusable components
- Diagnostics software for hardware ips in chip qualification and production
- Pre-silicon simulation and chip bring-up
- Chip screening processes on production line
- Migration of datasets from redshift to databricks
- Data validation using datafold and monte carlo
- Llm-based reasoning applications
Hiring Activity
25 roles · 15 in 30d
Department
Seniority
Company intelligence
