Senior AI Engineer - Machine Learning

Job Description

Build, Refine and Use ML Engineering platforms and components. Scaling machine learning algorithms to work on massive data sets and strict SLAs. Build and orchestrate model pipelines including feature engineering, inferencing and continuous model training. Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop. Collaborate with client facing teams to understand business context at a high level and contribute in technical requirement gathering. Implement basic features aligning with technical requirements. Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors. Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews. Write unit tests as we'll as higher level tests to handle expected edge cases and errors gracefully, as we'll as happy paths. Uses bug tracking, code review, version control and other tools to organize and deliver work. Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues and dependencies. Consistently contribute in researching & evaluating latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts and creating prototype solutions. What you'll Bring A masters or bachelors degree in Computer Science or related field from a top university. 4+ years hands-on experience in ML development. Good understanding of the fundamentals of machine learning Strong programming expertise in Python, PySpark/Scala. Expertise in crafting ML Models for high performance and scalability. Experience in implementing feature engineering, inferencing pipelines, and real time model predictions. Experience in ML Ops to measure and track model performance, experience working with MLFlow Experience with Spark or other distributed computing frameworks. Experience in ML platforms like Sage maker, Kubeflow. Experience with pipeline orchestration tools such Airflow. Experience in deploying models to cloud services like AWS, Azure, GCP, Azure ML. Expertise in SQL, SQL DBs. Knowledgeable of core CS concepts such as common data structures and algorithms. Collaborate we'll with teams with different backgrounds / expertise / functions