Job Description
iENGINEERING is currently seeking an ideal candidate who will assume the responsibility of leveraging AI pipelines to manipulate data across diverse projects. This individual will play a key role in identifying and addressing any issues within the pipeline, while also maintaining performance analytics to guarantee optimal functionality.
Requirements What you’ll be doing:
- Utilize AI pipelines to manipulate and process data for different projects according to project requirements.
- Monitor and maintain the performance of AI pipelines, ensuring smooth operation and timely delivery of results.
- Develop and maintain documentation related to AI pipeline workflows, configurations, and troubleshooting procedures.
- Conduct performance analytics to evaluate the effectiveness of AI pipelines and identify areas for optimization.
- Conduct performance analytics and build dashboards for team performance focusing on manual effort vs automation effort.
- Provide technical guidance and support to team members regarding the use and maintenance of AI pipelines.
- Ensure adherence to data security and compliance standards in all AI pipeline activities.
- Emphasize strong communication and collaboration skills for effective cross-functional teamwork.
- Showcase project management skills, demonstrating the ability to manage multiple projects, prioritize tasks, and meet deadlines.
- Emphasize a commitment to continuous learning and staying updated on advancements in AI and data analytics.
What you’ll bring along:
- Bachelor’s degree or higher in Computer Science, Engineering, or related field.
- 1+ years of hands-on experience.
- Good understanding of programming languages commonly used in data manipulation and analysis, such as Python, R, or SQL.
- Strong analytical and problem-solving skills, with the ability to diagnose and resolve complex technical issues.
- Experience with data preprocessing, feature engineering, and model deployment processes.
- Detail-oriented mindset with a focus on delivering high-quality results.
- Experience in maintaining performance analytics and generating insights from data.
- Experience with geospatial data analytics and ESRI products.
- Understanding of Transportation Infrastructure Ecosystem and Asset Management.
- Troubleshoot issues within the AI pipelines, including data quality problems, algorithmic errors, and performance bottlenecks.
- Relevant certifications in AI, data analytics, or related fields are a plus.