We are seeking an Applied Artificial Intelligence (AI) Engineer to design, develop, and deploy AI-driven solutions that transform digital processes and enhance decision-making capabilities. The ideal candidate combines strong AI/ML engineering expertise with practical application experience in real-world digital transformation scenarios.
Design, develop, and implement AI/ML models and algorithms for business applications.
Apply AI techniques such as machine learning, deep learning, natural language processing (NLP), computer vision, and generative AI to solve practical problems.
Collaborate with cross-functional teams (data scientists, software engineers, and product managers) to integrate AI capabilities into digital platforms and enterprise systems.
Develop and optimize data pipelines, model training workflows, and deployment strategies using MLOps best practices.
Evaluate emerging AI technologies and frameworks for potential adoption in digital transformation projects.
Conduct performance analysis, fine-tuning, and model interpretability testing.
Document design and implementation details to ensure maintainability and compliance.
Work closely with cloud and DevOps teams to operationalize AI models at scale.
Languages: Python, Java, or C++
Frameworks/Libraries: TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face Transformers
MLOps Tools: MLflow, Kubeflow, AWS Sagemaker, Azure ML, or GCP Vertex AI
Data Handling: SQL, NoSQL, Spark, Pandas, NumPy
Cloud Platforms: AWS / Azure / Google Cloud (AI & Data Services)
Version Control: Git, GitHub/GitLab
Optional (nice-to-have): LangChain, LlamaIndex, RAG pipelines, Generative AI (LLMs, Diffusion Models)
Strong analytical and problem-solving abilities
Ability to translate business requirements into technical AI solutions
Excellent communication and collaboration skills
Passion for continuous learning and emerging AI technologies