Job Title: AI Engineer
Experience Required: 10+ Years
Location: Remote
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