Project Description :
We are seeking a highly skilled Senior AI Engineer to design, build, and deploy scalable artificial intelligence and machine learning solutions. This role requires strong expertise in developing predictive models, implementing AI-powered applications, and integrating them into enterprise systems. The ideal candidate combines deep technical proficiency with practical experience in cloud platforms and production-grade AI systems.
Make sure to apply with all the requested information, as laid out in the job overview below.
Responsibilities :
AI/ML Model Development
Design, develop, and optimize machine learning and deep learning models
Build NLP, computer vision, or predictive analytics solutions
Train, test, and evaluate models for accuracy, scalability, and performance
Fine-tune pre-trained models (e.g., LLMs, transformers) for business use cases
Data Engineering & Processing (Optional)
Collect, clean, and preprocess structured and unstructured datasets
Work with large-scale data pipelines and streaming data systems
Implement feature engineering and data transformation workflows
Deployment & MLOps
Deploy models into production using APIs, containers, or microservices
Work with DevOps to build CI/CD pipelines for ML workflows (MLOps)
Monitor model performance, drift, and reliability in production
Optimize latency, throughput, and cost efficiency
Cloud & System Integration
Integrate AI solutions into cloud platforms (AWS)
Work with services like SageMaker, Azure ML, Vertex AI, or OpenAI APIs
Collaborate with DevOps, backend, and frontend teams for implementation
Research & Innovation
Stay up to date with emerging AI technologies and frameworks
Evaluate and implement GenAI, LLMs, and prompt engineering techniques
Prototype and experiment with new AI-driven solutions
Mandatory Skills Description :
Technical Skills
Programming: Python (preferred), Java, or Scala
ML Frameworks: TensorFlow, PyTorch, Scikit-learn
AI/GenAI: prompt engineering (preferred), xsgimln Claude CLI / Code(preferred), LLMs(preferred) Hugging Face, OpenAI APIs
Data Tools (Optional): Pandas, NumPy, Spark
APIs & Microservices development
Version control (Git)
Cloud & DevOps
Experience with AWS
Containers: Docker, ECS/EKS
CI/CD pipelines (GitHub Actions Or Jenkins Or GitLab CI)
Data & Systems
Databases: SQL, NoSQL
Familiarity with data pipelines and ETL processes (Optional)
Understanding of distributed systems