● 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.