ai engineer

The company provides research services involving the design, development, and deployment of machine learning models and data pipelines across the full ML lifecycle.

• 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 and well-documented codebases.

• 4+ Years of experience in machine learning or AI engineering;
• Strong proficiency in Python and ML frameworks, including 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, including AWS Lambda or similar;
• Experience with Docker for containerized model training;
• Version control with Git and collaborative development practices;
• Proficiency in English;
• 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.

• No conditions specified