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AI/ML Engineer
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- Posted 5 days ago
- Be among the first 10 applicants
Job Description
Key Responsibilities
- Lead the architecture, development, and deployment of production-grade ML solutions for geospatial applications.
- Design scalable ML systems and integrate AI components into end-to-end platforms with software engineering teams.
- Drive MLOps best practices, including deployment, monitoring, model performance, reliability, and continuous improvement.
- Translate business objectives into technical requirements and delivery plans in collaboration with product, sales, and business development teams.
- Mentor engineers, guide technical decisions, and support pre- and post-sales activities.
Requirements
- Degree in Computer Science, Electrical Engineering, or a related discipline.
- Strong knowledge of machine learning/deep learning, including model development, evaluation, and optimisation.
- Proficient in Python with hands-on experience in PyTorch, scikit-learn, OpenCV, or similar frameworks.
- Experience deploying ML services, developing APIs (Flask/FastAPI/Node.js), and using Docker.
- Experience with LLMs, RAG, retrieval optimisation, and graph databases is an advantage.
(EA Reg No: 20C0312)
Please email a copy of your detailed resume to [Confidential Information] for immediate processing.
Only shortlisted candidates will be notified.
More Info
Job Type:
Industry:
Employment Type:
Key Skills
scikit-learn
LLMs
RAG retrieval
About Company
Skills:
Pyspark, Api Development, Azure Synapse Analytics, Azure Machine Learning, Financial Services, Ai, AI Governance, AutoGen, Cloud Native Architecture, AI Evaluation, Ethical Conduct and Professional Integrity, Fine Tuning, Conversational AI, Azure AI, Liaising with cross functional teams, Azure AI Search
Skills:
Machine Learning
Skills:
Machine Learning, Databricks, Azure, Kubernetes, Python, Sql, GenAI, AI Foundry, AI Search
Skills:
Prometheus, Grafana, Sql, Numpy, Pandas, MLops, Agile, Microsoft Azure, Databricks, Scrum, Azure Machine Learning, Python, CrewAI, Generative AI, Scikit-learn, RAG AI agents, Kanban, LlamaIndex
Skills:
Computer Vision, Deep Learning, Tensorflow, Numpy, Opencv, Rest Apis, Machine Learning, Pandas, MLops, Pytorch, Python, Docker, SAM-like models, CLIP-like models, Mask R-CNN, scikit-learn, CNNs, YOLO, Vision Transformers, Transformers