AI Model Development Specialist

3 days ago

Lahore, Punjab, Pakistan beBeeDataScientist Full time 2,500,000 - 3,500,000
Job Description

We are seeking a highly skilled professional to design, develop, and deploy AI-driven solutions that drive innovation and business impact. The ideal candidate will have expertise in machine learning, deep learning, and AI-powered applications, with a strong foundation in data science methodologies, model deployment, and MLOps.

The successful candidate will be responsible for developing and optimizing machine learning models for predictive analytics, NLP, computer vision, or recommendation systems. They will also implement Retrieval-Augmented Generation (RAG), vector search, and generative AI models, fine-tune large language models (LLMs) using LoRA, QLoRA, Hugging Face, OpenAI, and LangChain, and build and deploy AI-powered applications using FastAPI, Flask, TensorFlow, PyTorch, and OpenAI APIs.

Additionally, the candidate will develop data pipelines, feature engineering, and model training workflows for production use, ensure scalability and reliability of ML models with MLOps best practices, leveraging Docker, MLflow, and CI/CD pipelines, optimize AI models for performance, cost-efficiency, and real-time processing, work with cross-functional teams to integrate AI solutions into business applications, monitor AI models in production, analyze performance metrics, and implement improvements.

The ideal candidate will have a Bachelor's or Master's degree in Computer Science, AI, Data Science, or related fields, 3+ years of experience in machine learning, deep learning, and AI model development, expertise in Python, R, SQL, and frameworks like TensorFlow, PyTorch, Keras, strong knowledge of NLP, LLMs, generative AI, RAG, FAISS, and vector databases, experience with MLOps, model deployment (AWS SageMaker, GCP Vertex AI), and cloud services, hands-on experience in Graph Neural Networks, Transformers, AutoML, and reinforcement learning is a plus, and proficiency in working with big data technologies (Spark, Hadoop, Dask, Apache Kafka, Airflow) is desirable.

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