SENIOR DATA SCIENTIST - NLP
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Key skills for this role
Role Overview
Design, build, and deploy production-grade machine learning and multimodal AI solutions across text, image, audio, and video data.
Transform unstructured and semi-structured data into scalable AI services for search, recommendations, automation, analytics, and content intelligence.
Own model development, pipeline implementation, optimization, deployment, MLOps practices, and mentorship of junior team members.
Key Skills for This Role
Full Job Posting
Role Summary
Design, build, and deploy production-grade machine learning and multimodal AI solutions across text, image, audio, and video data.
Transform unstructured and semi-structured data into scalable AI services for search, recommendations, automation, analytics, and content intelligence.
Own model development, pipeline implementation, optimization, deployment, MLOps practices, and mentorship of junior team members.
Model and Pipeline Development
- Build and deploy multimodal models for NLP, computer vision, OCR, document understanding, and speech applications.
- Develop pipelines for text processing, entity extraction, classification, image tagging, moderation, visual understanding, speech-to-text, and speaker analysis.
- Implement Retrieval-Augmented Generation pipelines with text and multimodal indexing.
Optimization and Deployment
- Optimize inference for latency, throughput, and cost efficiency across batch and near-real-time workloads.
- Build CI/CD pipelines using GitHub Actions, Azure DevOps, or Jenkins.
- Deploy models as cloud-native microservices using Docker, Kubernetes, AKS, and FastAPI.
- Use Azure Machine Learning for experiment tracking, model registry, training pipelines, and deployment.
- Implement monitoring and observability with metrics, logging, alerts, and drift detection tools such as Prometheus and Grafana.
Application Integration and Collaboration
- Integrate AI capabilities into search, recommendation, knowledge, document, and content platforms.
- Design inference and retrieval APIs for downstream consumption.
- Collaborate with product, backend, data, and platform teams on scalable and secure AI integrations.
- Review code, mentor junior engineers, and contribute to reusable components, documentation, and engineering standards.
Required Skills and Qualifications
- Strong proficiency in Python with PyTorch and/or TensorFlow.
- Hands-on experience with NLP, computer vision, or speech models.
- Working knowledge of LangChain, LlamaIndex, or equivalent orchestration frameworks.
- Experience with vector search and semantic retrieval using FAISS, Pinecone, Weaviate, Azure AI Search, or equivalent.
- Solid understanding of Docker, Kubernetes, and CI/CD pipelines.
- 3–5+ years of hands-on experience in ML engineering or applied AI roles.
- Bachelor's degree in Computer Science, AI, Engineering, or a related field.
Preferred Skills
- Experience with Azure AI and ML services, including Azure OpenAI and Azure Data Lake, is preferred.
- Familiarity with real-time inference, streaming data, or distributed ML systems is preferred.
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