Job Title: Artificial Intelligence (AI) Engineer / Specialist

Overview

We are seeking a skilled and motivated AI Engineer to design, develop, and deploy intelligent systems that solve complex business problems. The ideal candidate will have strong expertise in machine learning, deep learning, and data-driven decision-making, along with hands-on experience in building scalable AI solutions.

Key Responsibilities

1. Model Development & Deployment

• Design, develop, and optimize machine learning and deep learning models.
• Implement algorithms using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Deploy models into production environments using APIs, microservices, or cloud platforms.

2. Data Processing & Analysis

• Collect, clean, and preprocess large datasets (structured and unstructured).
• Perform exploratory data analysis (EDA) to extract meaningful insights.
• Work with data pipelines and big data tools.

3. AI Solution Design

• Translate business requirements into AI/ML solutions.
• Select appropriate models (e.g., NLP, computer vision, recommendation systems).
• Optimize model performance using tuning and validation techniques.

4. Research & Innovation

• Stay up to date with the latest advancements in AI and machine learning.
• Experiment with new algorithms, architectures, and tools.
• Contribute to innovation and continuous improvement.

5. Collaboration

• Work closely with data scientists, software engineers, and product teams.
• Communicate technical concepts to non-technical stakeholders.
• Participate in code reviews and technical discussions.

Key Requirements (Skills & Experience)

1. Technical Skills

• Strong programming skills in Python (preferred), or Java/R.
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Solid understanding of:
• Supervised and Unsupervised Learning
• Deep Learning and Neural Networks
• Natural Language Processing (NLP)
• Computer Vision (optional based on role)
• Experience with data manipulation libraries like Pandas and NumPy.
• Familiarity with building and consuming RESTful APIs.

2. Data & Analytical Skills

• Ability to work with large, complex datasets (structured and unstructured).
• Experience in data preprocessing, feature engineering, and exploratory data analysis (EDA).
• Strong understanding of statistics and probability concepts.
• Experience with SQL and/or NoSQL databases.

3. Tools & Technologies

• Version control systems such as Git.
• Experience with cloud platforms (AWS, Azure, or Google Cloud).
• Familiarity with MLOps tools such as Docker, Kubernetes, and MLflow.
• Exposure to big data technologies like Apache Spark (preferred).

4. Experience Requirements

• Entry-Level:
• 0–2 years of experience (including internships or academic projects in AI/ML).
• Mid-Level:
• 2–5 years of hands-on experience in developing and deploying ML models.
• Senior-Level:
• 5+ years of experience with end-to-end AI system design and production deployment.
• Proven track record of delivering scalable AI solutions.

5. Domain Knowledge (Preferred)

• Experience in applying AI in domains such as:
• Healthcare
• Finance
• E-commerce
• Robotics or Automation
• Knowledge of Generative AI concepts (LLMs, transformers) is a strong advantage.

6. Soft Skills

• Strong problem-solving and analytical thinking.
• Good communication skills to explain technical concepts.
• Ability to work collaboratively in cross-functional teams.
• Self-driven with a continuous learning mindset.

7. Educational Background

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
• Relevant certifications in AI/ML are a plus.