4h 15m ago
Senior AI Engineer
pythonsqlpytorchtensorflowhugging_face+3
📡Worldwide Remote
Senior AI Engineer
Artificial Intelligence
4h 15m agoWorldwide Remote
Contract
IC
Source not independently verified - confirm the company domain before applying.
#vacancy #job #remote #AI #MachineLearning #GenerativeAI
Senior AI / Machine Learning Engineer (Generative AI & LLMs)
Format: Full-time / Contract / Remote
Location: Remote
Role Focus: Build and deploy production-grade AI/ML and Generative AI systems, with a focus on LLMs, RAG, personalization, MLOps, and cloud infrastructure.
Responsibilities:
- Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants.
- Develop recommendation, ranking, classification, and predictive ML models.
- Own end-to-end ML pipelines from data processing and training to deployment and monitoring.
- Build MLOps / GenAIOps workflows, CI/CD, GPU inference, and cloud-native AI infrastructure.
- Work with Product and Engineering to measure business impact through KPIs and experiments.
- Improve AI system scalability, reliability, cost, governance, and performance.
Requirements:
- 4–5+ years in AI, ML, or Data Science.
- Strong Python, SQL, and production ML experience.
- Hands-on experience with LLMs, Transformers, embeddings, RAG, and prompt engineering.
- Experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.
- Strong knowledge of Docker, Kubernetes, MLflow/W&B, CI/CD, AWS, and Terraform.
- Experience with Kafka, ETL pipelines, vector databases, and search systems.
- Ability to independently take AI projects from idea to production.
Nice to Have:
- Experience with A/B testing, responsible AI, recommendation systems, regulated environments, or team leadership.
- Candidate should be able to work on US time schedule
- Good English conversation skill is much much preferred
Senior AI / Machine Learning Engineer (Generative AI & LLMs)
Format: Full-time / Contract / Remote
Location: Remote
Role Focus: Build and deploy production-grade AI/ML and Generative AI systems, with a focus on LLMs, RAG, personalization, MLOps, and cloud infrastructure.
Responsibilities:
- Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants.
- Develop recommendation, ranking, classification, and predictive ML models.
- Own end-to-end ML pipelines from data processing and training to deployment and monitoring.
- Build MLOps / GenAIOps workflows, CI/CD, GPU inference, and cloud-native AI infrastructure.
- Work with Product and Engineering to measure business impact through KPIs and experiments.
- Improve AI system scalability, reliability, cost, governance, and performance.
Requirements:
- 4–5+ years in AI, ML, or Data Science.
- Strong Python, SQL, and production ML experience.
- Hands-on experience with LLMs, Transformers, embeddings, RAG, and prompt engineering.
- Experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.
- Strong knowledge of Docker, Kubernetes, MLflow/W&B, CI/CD, AWS, and Terraform.
- Experience with Kafka, ETL pipelines, vector databases, and search systems.
- Ability to independently take AI projects from idea to production.
Nice to Have:
- Experience with A/B testing, responsible AI, recommendation systems, regulated environments, or team leadership.
- Candidate should be able to work on US time schedule
- Good English conversation skill is much much preferred
Required Skills
pythonsqlpytorchtensorflowhugging_facelangchaindockerkubernetes
Required Languages
🇬🇧 English