AI / ML Engineer

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.