Design, train, deploy, monitor, and optimize AI/ML models powering a cloud-based voice agent platform. Responsibilities include STT, NLU, and TTS development; MLOps pipelines; AI API services; inference and latency optimization; frontend prototypes and dashboards; research, experimentation, vendor evaluation, documentation, and code quality. The role requires collaboration with backend, frontend, and infrastructure teams.
This is a remote position.
Job timings: Mon - Fri US EST Time zone
Job Location: Pakistan (Remote)
Experience: 5+ years
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.
We are looking for an experienced AI Engineer / Developer to join our product development team and drive the AI capabilities of this platform.
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.
REQUIRED QUALIFICATIONS
- 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
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, develop, and deploy AI-powered healthcare solutions using Java and Spring Boot microservices. Implement HL7 FHIR and Da Vinci interoperability standards across prior authorization, claims, eligibility, and provider domains. Build Kafka-based event-driven services, integrate relational databases, automate CI/CD, deploy with Docker and Kubernetes on AWS or Azure, and establish monitoring using Splunk, ELK, Prometheus, and Grafana.
Top Skills:
Apache KafkaAWSAzureAzure DevopsDa Vinci Implementation GuidesDockerElkGitGitGithub ActionsGrafanaHibernateHl7 FhirJava 17/21JenkinsJwtKubernetesMySQLOauth 2.0OraclePostgresPrometheusRest ApisSplunkSpring BootSpring Data Jpa
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, deploy, and improve enterprise AI solutions including LLM workflows, RAG pipelines, agents, classifiers, and copilots. Develop prompt strategies, tool-calling patterns, guardrails, evaluation frameworks, and responsible AI controls. Partner with data, security, privacy, compliance, architecture, and QA teams to ensure solutions are safe and governed. Monitor production quality, accuracy, hallucination risk, latency, cost, observability, and model drift while documenting limitations and operational requirements.
Top Skills:
Agent FrameworksData PipelinesEmbeddingsEvaluation ToolingLlmsModel ApisModel MonitoringModel ObservabilityOrchestration FrameworksPrompt EngineeringPythonRagVector Search
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, build, and deploy enterprise-scale generative AI and LLM-powered applications and agentic workflows. Implement RAG pipelines, document ingestion, embeddings, semantic and hybrid search, and integrate vector databases with PostgreSQL. Build responsive frontends (React/Next.js) and backend services (Python/Node.js), define end-to-end architecture, lead technical decisions and reviews, mentor engineers, and ensure safe, scalable AI solutions in collaboration with product and business partners.
Top Skills:
Agentic WorkflowsAi Orchestration FrameworksCrewaiEmbeddingsGenerative AiGraphragHybrid SearchLangchainLanggraphLlmsMicroservicesNext.JsNode.jsPostgresPythonReactRest ApisRetrieval-Augmented Generation (Rag)Semantic SearchVector Databases
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
