AI Engineer

We are looking for an AI Engineer to design, build and deploy machine learning models and data pipelines. You will work across the full ML lifecycle — from data preparation and model training to deployment and monitoring.

Key Responsibilities

• Develop and optimize models across LLMs, NLP, computer vision or related AI domains
• Design and architect data mining and synthetic labeling pipelines
• Preprocess data, perform feature engineering, and work with 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 toolkit to train models in containerized environments
• Collaborate with backend and product teams to integrate AI capabilities into production systems
• Maintain version-controlled, well-documented codebases

Requirements

• 4+ years of experience in machine learning or AI engineering
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
• Solid understanding of ML fundamentals: supervised/unsupervised learning, deep learning, optimization, and evaluation metrics
• Experience with MLOps tools (MLflow, Kubeflow, or SageMaker)
• Familiarity with cloud platforms for model training and serving (AWS Lambda or similar)
• Experience with Docker for containerized model training
• Version control with Git and collaborative development practices
• Proficiency in English language

Good to Have

• Experience with vector databases (Qdrant, Weaviate, 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