Build AI Agents with the domain context for specialised tasks
Integrate the agents with the applications
Build, train, and deploy gen AI
Perform feature engineering, model validation, and experiments
Implement agents in production environments (APIs, microservices, cloud architecture)
Document your work, follow best MLOps practices, and help shape AI development standards at Appsilon
Work closely with Data Engineers, Developers, and Analysts to integrate Gen AIML solutions into full-scale applications

Demonstrated hands-on experience with generative AI technologies, including LLM architectures and frameworks
Strong programming skills in Python or R and experience with ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.)
Proven experience training, evaluating, and deploying ML models in real-world scenarios
Solid understanding of data preprocessing, feature engineering, and model lifecycle
Ability to integrate ML solutions with applications (APIs, cloud endpoints, microservices)
Excellent communication skills and a collaborative approach to teamwork
Nice to have: Experience with cloud deployment (AWS, Azure, GCP) and containerization (Docker / Kubernetes)
Knowledge of MLOps tools (MLflow, Vertex AI, SageMaker, DVC, Airflow)
Experience working with large-scale or scientific datasets (biostatistics, genomics, pharma)
Understanding of data engineering / ETL concepts
Awareness of AI ethics, bias, and responsible AI principles

100% remote work
flexible schedule
global team culture
competitive B2B compensation with transparent ranges
budget and dedicated time for professional development (courses, certs, conferences)
modern equipment and tools for efficient development
supportive environment with room for innovation, experimentation, and ownership

AI Engineer

Key skills