AI engineer 23

requirements

• 1. Educational Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Information Technology, or related field.
• 2. Technical Skills:
• Programming Languages: Proficiency in Python, Java, or C++.
• AI/ML Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar.
• Automation Tools: Familiarity with RPA tools like UiPath, Automation Anywhere, or Blue Prism.
• Data Handling: Strong in data preprocessing, feature engineering, and data visualization using Pandas, NumPy, Matplotlib, or similar.
• Cloud Platforms: Experience with AWS, GCP, or Azure services related to AI/ML and automation.
• APIs & Integration: Experience building and consuming REST APIs.
• DevOps/CI-CD: Familiarity with tools like Git, Jenkins, Docker, Kubernetes is a plus.
• 3. Soft Skills:
• Strong problem-solving and analytical skills.
• Ability to work independently and in a team.
• Clear communication skills (written and verbal).
• Ability to understand and translate business requirements into AI/automation solutions.
• 4. Experience:
• Prior experience (1–3 years) in AI, machine learning, data science, or automation projects preferred.
• Internship or academic project experience in AI/ML/RPA for fresher roles.
• 5. Certifications (Optional but Valuable):
• AI/ML certifications from Coursera, Google, AWS, Microsoft, etc.
• RPA Developer certifications (e.g., UiPath Certified RPA Associate).
• 6. Bonus Skills:
• Familiarity with NLP, computer vision, or reinforcement learning.
• Experience with workflow engines like Apache Airflow.
• Exposure to process mining and automation strategy.