ai engineer in information services

The company provides information services.

• Design, build, and deploy RAG, NLP, and computer vision models;
• Develop and optimize models across LLMs, NLP, computer vision, and related AI domains;
• Design and architect data mining and synthetic labeling pipelines;
• Preprocess data and perform feature engineering on large-scale datasets;
• Train and evaluate models using PyTorch or TensorFlow;
• Deploy and monitor models using MLOps tools and cloud infrastructure;
• Use Docker and container toolkits to train models in containerized environments;
• Collaborate with backend and product teams to integrate AI capabilities into production systems;
• Maintain version-controlled and well-documented codebases.

• Experience working with Computer Vision;
• Experience in machine learning or AI engineering;
• Strong proficiency in Python and ML frameworks such as PyTorch and TensorFlow;
• Solid understanding of supervised and unsupervised learning, deep learning, optimization, and evaluation metrics;
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker;
• Familiarity with cloud platforms for model training and serving, such as AWS Lambda or similar;
• Experience with Docker for containerized model training;
• Version control with Git and collaborative development practices;
• Bachelor's degree in Computer Science, AI, Data Science, or a related field;
• Nice to have: Experience with vector databases such as Qdrant, Weaviate, or Pinecone, knowledge of model quantization, distillation, or fine-tuning techniques, familiarity with Kubernetes for model serving at scale, experience building synthetic data or annotation pipelines.

• Part-time employment.