MID-LEVEL AI ENGINEER
MID-LEVEL AI ENGINEER
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Design train evaluate and fine-tune AI/ML models for production use.
Implement state-of-the-art algorithms in areas such as NLP computer vision recommender systems or time-series forecasting.
Optimize models for performance scalability and cost efficiency in cloud and edge environments.
Data Engineering & Processing
Collaborate with data engineers to collect clean and preprocess large datasets.
Develop automated data pipelines for training and inference workflows.
System Integration & Automation
Integrate AI models into web mobile and enterprise applications using APIs and microservices.
Collaborate with software engineers to ensure seamless integration and deployment in production systems.
Develop and manage workflow automations using tools such as n8n Zapier or similar platforms to streamline data flows trigger AI processes and integrate multiple services.
Research & Innovation
Stay up to date with the latest AI research and assess applicability to business use cases.
Prototype new concepts and evaluate feasibility through proof-of-concepts and pilot projects.
Collaboration & Documentation
Work closely with cross-functional teams to translate business requirements into technical solutions.
Document model architecture training processes and deployment guidelines for maintainability and knowledge transfer.
Requirements
Bachelor s degree in Computer Science Data Science Artificial Intelligence or related field (Master s preferred).
3 5 years of experience in AI/ML development.
Proficiency in Python and AI/ML frameworks such as TensorFlow PyTorch Scikit-learn or Hugging Face Transformers.
Solid understanding of machine learning fundamentals data structures and algorithms.
Experience deploying models to production environments (AWS Azure GCP or on-premise).
Familiarity with version control (Git) and containerization (Docker Kubernetes).
Preferred:
Experience with large language models (LLMs) and prompt engineering.
Knowledge of MLOps tools and practices (MLflow Kubeflow Airflow).
Experience with automation and integration platforms like n8n or Zapier.
Exposure to data visualization libraries (Matplotlib Plotly) and analytics platforms.
Understanding of ethical AI principles bias mitigation and model interpretability.
Soft Skills
Strong problem-solving and analytical thinking.
Excellent communication and teamwork abilities.
Ability to work independently and manage multiple priorities in a fast-paced environment.
Employment Type
Full Time
