AIML Engineer
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Job Summary
Job Title: AI/ML Engineer
iSmart Recruit seeks an experienced AI/ML Engineer to design develop and deploy machine learning solutions that power intelligent recruiting and talent-matching features. You will collaborate with product data and engineering teams to turn data into production-grade models optimize model performance and ensure scalable maintainable ML systems.
Responsibilities
- Design and implement ML and deep learning models for candidate matching recommendation and ranking.
- Build end-to-end ML pipelines from data ingestion and feature engineering to model training evaluation and deployment.
- Collaborate with data engineers to prepare and maintain high-quality datasets.
- Deploy monitor and maintain models in production using MLOps best practices.
- Optimize model performance and latency for real-time and batch use cases.
- Implement testing versioning and CI/CD for ML workflows.
- Work cross-functionally to translate product requirements into technical solutions and technical trade-offs into business outcomes.
Qualifications
- Bachelor's or Master's degree in Computer Science Engineering Statistics or a related field (or equivalent experience).
- Proven experience developing and deploying ML/AI solutions in production environments.
- Strong programming skills in Python and experience with ML frameworks such as TensorFlow or PyTorch.
- Experience with cloud platforms (AWS GCP or Azure) and containerization with Docker and Kubernetes.
- Familiarity with data storage technologies model monitoring and MLOps practices.
- Excellent problem-solving communication and collaboration skills.
Skills
- Python
- Machine Learning
- Deep Learning
- Natural Language Processing
- Computer Vision
- TensorFlow
- PyTorch
- scikit-learn
- Keras
- Pandas
- NumPy
- Feature Engineering
- Hyperparameter Tuning
- Model Evaluation
- Model Deployment
- MLOps
- Model Monitoring
- SQL
- PostgreSQL
- MongoDB
- NoSQL
- Apache Spark
- Docker
- Kubernetes
- AWS
- GCP
- Azure
- Git
- CI/CD
- RESTful API
- Data Visualization
- Data Science
- Data Engineering
- Distributed Computing
- Explainable AI
- Time Series Analysis
- Reinforcement Learning
- Optimization Algorithms
- Big Data
Required Skills:
Python Machine Learning Deep Learning Data Science TensorFlow PyTorch scikit-learn Keras Natural Language Processing Computer Vision SQL NoSQL PostgreSQL MongoDB Pandas NumPy Apache Spark Docker Kubernetes AWS GCP Azure MLOps Model Deployment Model Monitoring Feature Engineering Hyperparameter Tuning Model Evaluation CI/CD Git RESTful API Data Visualization Data Engineering Distributed Computing Explainable AI Time Series Analysis Reinforcement Learning Optimization Algorithms Big Data
