AI Engineer
First seen by Alion on Sep 24, 2026.
Job Description :
Key Responsibilities :
- Design and develop machine learning models, deep learning architectures, and AI solutions to address business challenges.
- Build end-to-end ML pipelines including data ingestion, feature engineering, model training, evaluation, and deployment.
- Develop and integrate RESTful APIs and microservices to serve AI/ML models in production with high availability.
- Implement generative AI solutions leveraging LLMs, RAG, prompt engineering, and fine-tuning.
- Collaborate with cross-functional teams to translate research prototypes into scalable applications.
- Optimize model performance through hyperparameter tuning, A/B testing, and continuous monitoring.
- Architect scalable AI infrastructure using cloud-native services (Azure AI, AWS SageMaker, or GCP Vertex AI) and containerization (Docker, Kubernetes).
- Maintain MLOps practices including version control, automated retraining, and CI/CD workflows.
- Ensure responsible AI practices including fairness, explainability, and bias detection.
Qualifications :
- Bachelor's degree in Computer Science, AI, Data Science, or related field (Required).
- Master's degree or Ph.D. (Preferred).
- Hands-on experience building and deploying ML models in production.
- Experience with end-to-end ML pipelines and MLOps in cloud environments.
Tech Stack :
- Python, TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain.
- Azure ML, AWS SageMaker, GCP Vertex AI.
- Pandas, NumPy, Spark, SQL.
- MLflow, Kubeflow, Docker, Kubernetes.
- GPT, Claude, LLaMA, Vector Databases (Pinecone, Weaviate, FAISS).
Skills
Python, Machine Learning, Tensorflow, PyTorch, Generative AI, Artificial Intelligence, LLM, RAG, MLOps