
Deep Learning Specialist
1 week ago
About the Role:
This role involves working as an AI/ML Engineer at Datum Labs, where you will be responsible for designing, training, and deploying cutting-edge AI models. The primary focus will be on deep learning, generative AI, and neural representation learning, with contributions to real-world applications in AI-driven data intelligence.
Your Key Responsibilities:
- Develop, deploy, and optimize AI models, including LLMs, diffusion models, and neural networks.
- Collaborate with data engineers to build and enhance data pipelines & ETL workflows.
- Optimize deep learning models for improved performance, scalability, and efficiency.
- Implement and manage vector databases (Weaviate, Pinecone) for AI applications.
- Work closely with cross-functional teams to align AI initiatives with business objectives.
- Ensure model explainability, fairness, and bias mitigation for responsible AI practices.
- Provide valuable insights and actionable recommendations through customer discussions.
- Deploy models in production with intuitive, user-friendly interfaces.
- Implement MLOps practices for model monitoring, retraining, and lifecycle management.
Key Requirements:
- Strong expertise in Python and relevant libraries (PyTorch, TensorFlow, Pandas, NumPy).
- Hands-on experience with LLMs, Generative AI, Hugging Face Transformers, Diffusers.
- Knowledge of prompt engineering, model optimization, and fine-tuning techniques.
- Experience with data analysis, unstructured datasets, and model visualization tools.
- Familiarity with APIs for model integration (e.g., FastAPI, Flask).
- Solid understanding of SQL for structured data analysis.
- Experience with cloud-based ML tools (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).
- Proficiency in version control systems like Git.
- Excellent problem-solving skills with attention to detail.
- Effective communication and presentation skills for technical and non-technical stakeholders.
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