CI
CloudPSO Inc
Senior AI ENGINEER/DEVELOPER (Remote)
Islamabad, PKIn sedeIndeterminatoTempo pieno
Pubblicato il 5 set 2026
Questa offerta è pubblicata in EN
This is a remote position.
Job timings: Mon - Fri US EST Time zone
Job Location: Pakistan (Remote)
Experience: 5+ years
PRODUCT CONTEXT
CloudPSO's first standardized AI Agent product enables enterprises to deploy intelligent voice assistants for customer support, sales, and internal operations. Its core capabilities include:
- Speech-to-Text (STT): Real-time voice transcription.
- Natural Language Understanding (NLU): Intent recognition, context awareness, and conversation control.
- Text-to-Speech (TTS): Natural, human-like voice responses.
- Enterprise Platform: Cloud-native deployment with scalability, low latency, security, observability, and enterprise-grade reliability.
ROLE OVERVIEW
The AI Engineer will be responsible for designing, training, deploying, and optimizing AI/ML models that power the Voice Agent platform. This role spans the full AI lifecycle—from research and experimentation to production deployment and monitoring. The ideal candidate has deep expertise in speech and NLP technologies, strong engineering practices, and the ability to collaborate across backend, frontend, and infrastructure teams. Frontend development skills are mandatory, as this role includes building prototypes, dashboards, and internal demos.
KEY RESPONSIBILITIES
- Model Development: Design, train, and fine-tune models and pipelines for STT, NLU, and TTS use cases.
- MLOps: Build and maintain MLOps pipelines for model deployment, monitoring, and retraining.
- API Development: Develop APIs and services that expose AI capabilities to backend and frontend systems.
- Performance Optimization: Collaborate with backend engineers to optimize inference performance and end-to-end latency.
- Frontend Prototyping: Create frontend prototypes, dashboards, and demonstrations using a modern frontend framework.
- Research & Experimentation: Conduct research and controlled experiments to improve model accuracy, quality, and performance.
- Vendor Evaluation: Evaluate external models and providers against product requirements and measurable benchmarks.
- Documentation: Document model architectures, experiments, evaluation results, and deployment processes.
- Code Quality: Participate in code reviews and maintain high engineering and reproducibility standards.
Requirements
PREFERRED SKILLS
- Experience with real-time streaming using WebSocket or WebRTC.
- Knowledge of model quantization, pruning, and inference optimization.
- Familiarity with SIP, WebRTC, or PSTN integration.
- Open-source contributions or research publications in AI, speech, or voice domains.
- Experience: 7–9 years of AI/ML development experience.
- Programming: Strong Python expertise with experience in PyTorch, TensorFlow, Hugging Face, or equivalent frameworks.
- Speech & NLP: Hands-on experience with speech/audio processing and natural language processing techniques.
- Model Deployment: Hands-on deployment experience using ONNX, TensorRT, Triton, or equivalent tooling.
- Frontend (Mandatory): Experience with React, Vue.js, or Angular.
- Cloud AI Platforms: Experience with AWS SageMaker, GCP Vertex AI, Azure ML, or an equivalent cloud AI platform.
- Containerization: Knowledge of Docker and Kubernetes.
- Version Control & CI/CD: Experience with Git and continuous integration and delivery pipelines.
- Analytical Skills: Strong analytical and problem-solving skills.
Benefits
- Medical insurance
- Company gadgets
- Paid time off
- Stock options (ESOP)
- Competitive salary and benefits package.
- Opportunities for professional development and growth.
- Collaborative and innovative work environment.
- Chance to work on cutting-edge cloud projects.
- Supportive and inclusive company culture
Informazioni ruolo
Tipo di lavoro
Tempo pieno
Skill richieste
Python programming with PyTorch/TensorFlow/Hugging FaceSpeech and audio processingNatural Language Understanding (NLU) / NLP techniquesSpeech-to-Text (STT) and Text-to-Speech (TTS) model development and fine-tuningModel deployment tooling (ONNX, TensorRT, Triton)MLOps: building pipelines for deployment, monitoring, and retraining modelsCloud AI platforms (AWS SageMaker, GCP Vertex AI, Azure ML)Containerization and orchestration (Docker, Kubernetes)Frontend development with modern frameworks (React, Vue.js, or Angular)Real-time streaming technologies (WebSocket, WebRTC)Model optimization techniques (quantization, pruning, inference optimization)API development for exposing AI services to backend/frontend systemsVersion control and CI/CD (Git, continuous integration and delivery pipelines)Research, experimentation, and vendor evaluation (benchmarks, publications, open-source contributions)
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