
AI/ML Engineer
2 days ago
**Job Type:** Full-Time
**Experience Level:** 3-9 Years
**Job Overview:**
We are seeking a highly skilled AI/ML Engineer to join our dynamic team. The ideal candidate will have strong proficiency in Python, extensive experience with AWS services, and a solid understanding of MLOps principles. This role involves developing, deploying, and maintaining advanced machine learning models that drive business growth and innovation.
**Responsibilities:**
1. **Model Development & Deployment:**
- Develop cutting-edge AI/ML models using Python libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
- Design and implement scalable ML pipelines using AWS services including SageMaker, Lambda, EC2, and RDS.
- Continuously improve model performance through iterative experimentation and hyperparameter tuning.
2. **Data Engineering:**
- Work closely with data scientists and engineers to ingest, preprocess, and store large datasets efficiently.
- Implement robust data pipelines using AWS Glue, EMR, and Kinesis for real-time data processing.
- Ensure data quality and manage metadata effectively using tools like AWS Data Catalog and Glue DataBrew.
3. **MLOps Practices:**
- Automate model deployment processes using CI/CD tools like AWS CodePipeline and AWS CodeBuild.
- Implement monitoring and logging mechanisms to track model performance and detect anomalies.
- Conduct A/B testing and experiment management to optimize model outcomes.
- Ensure compliance with regulatory standards and best practices in MLOps.
4. **Collaboration & Communication:**
- Collaborate with cross-functional teams including product managers, data scientists, and business stakeholders to understand project requirements.
- Communicate technical findings and recommendations clearly and concisely to non-technical stakeholders.
- Participate in regular code reviews and contribute to the continuous improvement of development processes.
5. **Research & Innovation:**
- Stay updated with the latest advancements in AI/ML and explore innovative solutions to address business challenges.
- Contribute to open-source projects and share knowledge within the broader community.
**Requirements:**
1. **Technical Skills:**
- Proficiency in Python, including familiarity with libraries such as NumPy, Pandas, TensorFlow, PyTorch, and Scikit-Learn.
- Expertise in designing and implementing machine learning pipelines using AWS services (SageMaker, Lambda, EC2, RDS).
- Strong understanding of data engineering principles and experience with AWS Glue, EMR, and Kinesis.
- Familiarity with containerization technologies like Docker and Kubernetes for managing ML workloads.
- Knowledge of cloud-native storage and database solutions.
2. **MLOps Experience:**
- Hands-on experience with automating ML workflows using CI/CD tools like AWS CodePipeline and CodeBuild.
- Experience with model monitoring and logging frameworks like Amazon CloudWatch and X-Ray.
- Understanding of A/B testing and experiment management techniques.
- Compliance with relevant regulations and best practices in MLOps.
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