AI Engineer

Responsibilities

What you’ll do in this role:

• ◦ Design, develop and maintain scalable and resilient AI/ML products, recommendations system and personalization, chatbot, search and forecasting. You are responsible for end-to-end machine learning product life cycle, i.e. EDA, experimentation, model development, productionization, evaluation, automation with CI/CD pipeline, and A/B testing.
• ◦ Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our machine learning products that serve millions of Lumin users and businesses.
• ◦ Work with large and complex data sets to solve challenging problems using analytical, statistical, and machine learning algorithms.
• ◦ Identify and measure the success of machine learning product efforts through goal setting and monitoring of key metrics to understand trends.
• ◦ Gain an understanding of potential opportunities and methods to enhance the solutions, and use your insights and recommendations to test and drive initiatives forward.
• ◦ Develop and conduct best practices in the AI team.
• ◦ Partner with product, engineering, analytics, business, and cross-functional teams to inform, influence, support, and execute AI initiatives.
• ◦ Responsible for maintaining the health of the uptime SLA of the service.
• ◦ Provide support in coaching and mentoring the more junior team members.

Your skills and experience

Good candidates for AI Engineer position should have the following qualifications:

• ◦ A Bachelor or Master in a quantitative field (Computer Science, Engineering, etc).
• ◦ Experience of 3-9 years in AI, Machine Learning, or Data Science roles.
• ◦ Strong technical hands-on experience in Python.
• ◦ Solid knowledge of Machine Learning fundamental i.e. knowledge of models variant and use cases, end-to-end ML lifecycle process, model development, model selection, hyperparameter optimization, feature engineering, evaluation, etc.
• ◦ Extensive practical knowledge of Machine Learning algorithms libraries such as Tensorflow, Pytorch, Keras, Scikit-Learn and Pandas.
• ◦ Hands-on experience in three or more of the following AI topics: NLP, recommendation systems, predictive analytics, computer vision, search.
• ◦ Proficient experience in git and building CI/CD pipelines.
• ◦ Experience in operating Docker images within a microservices architecture.
• ◦ Proficiency in working with either GCP or AWS cloud platforms is required.
• ◦ Experience in MLOps platform e.g. MLflow, or Kubeflow.
• ◦ Having experience working with SQL is a plus.
• ◦ Nice-to-have: practical experience working with GenAI/LLM.
• ◦ Have a growth mindset, self-driven, high motivation & curiosity to learn.
• ◦ Strong analytical skills and proven experience working with complex & large data.
• ◦ Having a track record of delivering and taking action based on insights derived from JD – Senior AI Engineer 3 data is a plus.
• ◦ Demonstrated ability to successfully deliver end-to-end ML projects, including identifying impactful use cases, estimating effort, conducting EDA, developing solutions and models, evaluating performance, deploying models, and monitoring their performance.
• ◦ Proven track record of operating independently, stakeholder management, demonstrating creativity, and delivering results.
• ◦ A self-driven individual and a team player with excellent communication skills.