AI Engineer

Responsibilities

1. AI Model Development

   • Research, design, and build machine learning (ML) and deep learning (DL) models.
   • Select appropriate algorithms for classification, regression, clustering, NLP, or computer vision tasks.
   • Train, validate, and fine-tune models for high accuracy and efficiency.

2. Data Preparation & Management

   • Collect, clean, and preprocess structured and unstructured data.
   • Perform feature engineering and data augmentation.
   • Work with databases, big data frameworks, and cloud storage.

3. Deployment & Integration

   • Deploy AI/ML models into production using APIs, cloud platforms, or edge devices.
   • Build scalable AI pipelines using MLOps practices (CI/CD, automation, monitoring).
   • Collaborate with software engineers to integrate AI into products and services.

4. Performance Optimization

   • Monitor model performance in real‑world scenarios.
   • Perform hyperparameter tuning, optimization, and retraining as needed.
   • Ensure robustness, efficiency, and low latency of deployed models.

5. Research & Innovation

   • Stay updated with new AI architectures (transformers, generative AI, reinforcement learning).
   • Experiment with state‑of‑the‑art algorithms and techniques.
   • Contribute to proofs of concept (PoCs) and innovative AI‑driven applications.

6. Collaboration & Communication

   • Work with cross‑functional teams (data engineers, domain experts, product managers).
   • Translate business requirements into AI solutions.
   • Present technical findings and results to stakeholders in a clear way.

7. Ethics, Security & Compliance

   • Ensure AI solutions are fair, unbiased, and explainable.
   • Follow data privacy and security standards (GDPR, HIPAA, etc.).
   • Build responsible and ethical AI systems.

Qualifications

• Bachelor’s/Master’s degree in Computer Science, AI, Data Science, or related field.
• 2–3 years of experience in AI/ML model development and deployment.
• Strong programming skills in Python (NumPy, Pandas, Scikit-learn).
• Expertise with ML/DL frameworks (TensorFlow, PyTorch, Keras, Hugging Face).
• Hands‑on experience with cloud AI platforms (AWS SageMaker, Azure ML, Google Vertex AI).
• Solid knowledge of SQL/NoSQL databases, data engineering, and APIs.
• Strong grasp of mathematics, probability, statistics, and optimization.

Preferred Skills (Nice to Have)

• Experience with MLOps tools (Docker, Kubernetes, MLflow, Airflow).
• Familiarity with edge AI and deploying models on embedded systems.
• Experience in NLP, LLM fine‑tuning, computer vision, or reinforcement learning.
• Proven record of leading AI projects from research to production.

Job Details

• Job Type: Full-time
• Pay: From ₹20,000.00 per month
• Ability to commute/relocate: Nagercoil, Tamil Nadu – Reliably commute or planning to relocate before starting work (Preferred)
• Work Location: In person