AI/ML Engineer

**Job Title:** Senior AI/ML Engineer

**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.