Sr ML & AI Engineer
Tasks
- Apply deep learning for vision language tasks
- Architect AI first systems
- Build MLOps pipelines and evaluation
- Build retrieval-augmented systems
- Collaborate to deliver scalable explainable AI solutions
- Design embedding models and vector retrieval
- Develop agentic AI multi agent solutions
- Develop and deploy generative AI applications
- Develop multimodal vision language models
- Implement confidence gating and escalation logic
- Implement prompt engineering and model fine-tuning
- Mentor engineers and data scientists
- Optimize production Python code
Perks/Benefits
- N/A
Skills/Tech-stack
Active Learning | Agent systems | Agentic AI | Artificial Intelligence | Autogen | BERT | CNN | Classification | Clustering | CrewAI | Deep learning | Diffusion Models | Embeddings | Fine Tuning | Forecasting | GANs | GRU | Generative AI | Graph Neural Networks | Human-in-the-loop | LSTM | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Fine-tuning | Multi-Agent | Multi-Agent Systems | Multimodal Learning | Neural Networks | Prompt engineering | PyTorch | Python | Regression | Retrieval-Augmented Generation | SVM | Scikit-learn | Similarity Search | Spark | TensorFlow | The Loop | Transformers | Vector Databases | Vector similarity | Vector similarity search | Vision Language Models | Vision-language | XGBoost
Education
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