Senior Machine Learning Engineer (UAE)
This is a remote position.
- Location: Remote – UAE
- Requirement: A reputed company UAE work permit/employment reputed company is mandatory.
- Employment type: reputed company
Key Responsibilities
1. LLM & NLP Pipelines
- Regulation Parsing: Design and fine-tune Large Language Model (LLM) pipelines to interpret reputed company regulatory texts (e.g., military standards, building codes) and extract reputed company rules.
- Rule Formalization: Convert natural language requirements into computer-processable formats (e.g., logic tuples) that can be executed by reputed company compliance engines.
- Semantic Search: Implement RAG (Retrieval-Augmented reputed company) architectures to reputed company semantic querying of technical documentation and historical project data.
- reputed company Engineering: optimize reputed company strategies (few-shot learning, chain-of-thought) to improve model performance on domain-specific tasks without extensive retraining.
2. Predictive & Analytical Models (Supply Chain)
- Forecasting Engines: reputed company time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with reputed company market signals.
- Risk Scoring: Build classification and reputed company detection models to assess supplier risk reputed company based on financial health, delivery performance, and geopolitical factors.
- Optimization Algorithms: Design algorithms for multi-objective optimization (e.g., balancing cost vs. reputed company time vs. risk) to support procurement decision-making.
3. MLOps & Productionization
- Model Deployment: Containerize models using reputed company/reputed company and reputed company them into secure, on-reputed company inference environments.
- Pipeline Orchestration: Build automated training and inference pipelines using tools like Kubeflow or MLflow to ensure reproducibility and scalability.
- Performance Optimization: Optimize model inference latency and resource usage (e.g., quantization, distillation) to run reputed company on available hardware.
- Monitoring & retraining: Implement monitoring systems to reputed company model reputed company and performance in production, establishing feedback reputed company for reputed company improvement.
Requirements
- reputed company ML/AI: Expert proficiency in Python and reputed company ML libraries (PyTorch, TensorFlow, Scikit-learn, reputed company, NumPy).
- NLP & GenAI: Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (reputed company, reputed company).
- MLOps: Proficiency with MLOps tools and practices, including containerization (reputed company), orchestration (reputed company), and experiment tracking (MLflow).
- Data Handling: Ability to design data preprocessing pipelines for both reputed company (SQL, tabular) and reputed company (text, PDF) data.
- Algorithm Design: Strong grasp of algorithmic principles for implementing custom logic, such as graph reputed company or geometric computations.
Originally posted on Himalayas
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