Remotely
dockerkubernetesnlpmlopsllmopsgenaillmsrag
Job Description
📋 Description
- Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through
- Build and optimize ML models and apps across deep learning, NLP, forecasting, classification
- Develop production-grade GenAI apps using LLMs, RAG pipelines, embeddings, retrieval optimization
- Design and implement AI evaluation frameworks to assess model quality, reliability, relevance, and
- Build scalable AI services and integrations using REST and gRPC APIs and event-driven architectures.
- Establish and maintain MLOps and LLMOps across deployment, automation, versioning, monitoring, and
🎯 Requirements
- 8+ years of professional software engineering or technical engineering experience.
- Strong hands-on experience in Machine Learning and AI/ML Engineering.
- Advanced Python development skills with practical experience in deep learning and ML techniques.
- Experience with NLP, forecasting, classification, regression, and anomaly detection.
- Proven experience building GenAI apps using LLMs and Retrieval-Augmented Generation (RAG)
- Strong understanding of embeddings, retrieval tuning, reranking, prompt engineering, and AI/LLM
🎁 Benefits
- Competitive annual salary of $100,000–$120,000.
- Full-time opportunity with a remote working model.
- Opportunity to work on cutting-edge AI, ML, and GenAI solutions.
- Hands-on exposure to LLMs, RAG, MLOps, LLMOps, Kubernetes, and cloud-native practices.
- Opportunity to contribute to AI solutions from concept to production deployment.
- Work on technically challenging projects with focus on scalability, security, governance, and
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