Description :

Job Summary

We are seeking an innovative and results-driven Artificial Intelligence Engineer to design, develop, deploy, and optimize AI/ML models and intelligent systems.

The role involves working with large datasets, building machine learning and deep learning models, integrating AI solutions into production systems, and collaborating with cross-functional teams to solve complex business problems.

Key Responsibilities :

- Design, develop, train, evaluate, and deploy machine learning and deep learning models

- Apply supervised, unsupervised, and reinforcement learning techniques

- Build and optimize models for classification, regression, clustering, recommendation, and prediction

- Collect, clean, preprocess, and analyze structured and unstructured data

- Perform feature engineering and data augmentation to improve model performance

- Work with large-scale datasets and distributed data processing systems

- Deploy AI/ML models into production environments

- Build and maintain scalable inference pipelines

- Implement monitoring, versioning, and retraining strategies for deployed models

- Collaborate with DevOps teams on CI/CD for ML (MLOps)

- Develop deep learning models using CNNs, RNNs, Transformers, and LLM-based architectures

- Work on NLP, Computer Vision, Speech Recognition, or Recommendation Systems

- Fine-tune pre-trained models and foundation models

- Integrate AI models with applications using REST APIs or microservices

- Optimize model performance for latency, scalability, and cost

- Work closely with software engineers to embed AI into products

- Stay up to date with the latest AI/ML research, tools, and frameworks

- Evaluate new algorithms and technologies and recommend adoption

- Conduct experiments and document findings and best practices

Required Skills & Qualifications :

Technical Skills :

- Strong proficiency in Python (mandatory); knowledge of Java/Scala is a plus

- Hands-on experience with machine learning frameworks: TensorFlow, PyTorch, Scikit-learn

- Experience with data processing libraries: Pandas, NumPy, Spark

- Strong understanding of statistics, probability, linear algebra, and optimization

- Experience with NLP (BERT, GPT, embeddings) and/or Computer Vision (OpenCV, CNNs)

- Knowledge of LLMs, prompt engineering, RAG pipelines, and vector databases (FAISS, Pinecone, Milvus)