AI Engineer

Job Title:

Experience Required:

Location:

Position Overview:

We are seeking an experienced AI Engineer Traineer with over a decade of expertise in designing, developing, and deploying artificial intelligence and machine learning solutions. The role involves architecting end-to-end AI systems, applying advanced models to real-world problems, and ensuring scalability, accuracy, and compliance with industry standards. The candidate will be responsible for driving AI initiatives across enterprise applications, collaborating with cross-functional teams, and integrating AI into digital transformation programs.

Key Responsibilities:

• Designed and implemented advanced machine learning, deep learning, and natural language processing (NLP) models for business-critical applications.
• Built and optimized scalable AI pipelines, from data ingestion and preprocessing to model training, deployment, and monitoring.
• Deployed AI models using MLOps frameworks with CI/CD, versioning, and automated retraining strategies.
• Applied computer vision, reinforcement learning, and generative AI for domain-specific use cases.
• Optimized model performance, accuracy, and interpretability through feature engineering and hyperparameter tuning.
• Integrated AI solutions with cloud environments (AWS SageMaker, Azure ML, Google Vertex AI).
• Established AI governance, bias detection, and compliance frameworks to ensure ethical and transparent use of AI.
• Collaborated with data scientists, software engineers, and business stakeholders to translate requirements into scalable AI solutions.
• Published documentation, conducted technical reviews, and supported knowledge transfer across teams.
• Drove innovation by evaluating emerging AI technologies and applying them to enterprise needs.

Top Skills & Competencies:

• Programming: Python, R, Java, C++
• Machine Learning & Deep Learning: TensorFlow, PyTorch, Keras, Scikit-learn
• Natural Language Processing: Transformers, Hugging Face, spaCy, NLTK
• Generative AI: LLMs, diffusion models, prompt engineering
• Computer Vision: OpenCV, YOLO, Detectron2
• Data Engineering: Spark, Hadoop, Kafka, SQL/NoSQL databases
• MLOps & Deployment: MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines
• Cloud Platforms: AWS SageMaker, Azure ML, Google Vertex AI
• Governance & Compliance: Model monitoring, bias detection, explainability, AI ethics frameworks
• Strong analytical, problem-solving, and collaboration skills