Mid-Level AI Engineer

About the role

Raincode is looking for a Mid-Level AI Engineer to join its staff augmentation and delivery services. You will work on client projects, either on‑site or remotely, designing and deploying AI/ML solutions that solve real business challenges, especially for customers in the Scandinavian market.

Key responsibilities

• Collaborate with client stakeholders to gather requirements, define success metrics, and align AI solutions with business objectives.
• Design, develop, and fine‑tune machine learning models (NLP, computer vision, recommendation systems, etc.) using TensorFlow, PyTorch or scikit‑learn.
• Build and maintain data pipelines for structured and unstructured data, including ETL, cleaning, and feature engineering.
• Implement inference services and micro‑services for model deployment using Docker, Kubernetes or serverless architectures.
• Integrate third‑party AI tools and APIs (OpenAI, AWS SageMaker, Azure Cognitive Services, Hugging Face) into web and mobile applications.
• Monitor production models, evaluate performance, and perform retraining or fine‑tuning to meet SLA requirements.
• Document AI architectures, APIs, workflows and best practices for both client and internal use.
• Mentor junior engineers and ensure professional communication with client stakeholders.

Required profile

• Bachelor’s degree in Computer Science, Data Science, AI, Software Engineering or equivalent practical experience.
• 3–5 years of professional experience in AI/ML engineering.
• Strong proficiency in Python and related data‑science libraries.
• Experience with NLP techniques and/or computer‑vision frameworks.
• Familiarity with cloud ML services (AWS, GCP, Azure) and container/orchestration tools.
• Ability to translate business requirements into measurable AI solutions and communicate effectively with clients.

Required skills

• Python
• NumPy, Pandas, scikit‑learn
• TensorFlow, PyTorch
• NLP (transformers, embeddings, LLM integrations)
• Computer‑vision frameworks
• Cloud ML services (AWS, GCP, Azure)
• Docker, Kubernetes
• OpenAI API, AWS SageMaker, Azure Cognitive Services, Hugging Face
• Git, CI/CD pipelines, unit testing