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As a Senior Software Engineer, Advanced Analytics, your main responsibilities will be:• Designing and implementing portable, modular, instrumented and highly performant data contextualization pipelines from landed and cleansed, batch and streamed unstructured data, using Apache Spark, Deltalake and/or Databricks• Designing and implementing portable, modular, instrumented and highly performant model deployment pipelines for many types of machine learning including supervised and unsupervised learning as well as CNNs, RNNs or other deep learning algorithms• Working with data engineering to define pipelines that serve curated datasets to business intelligence, reporting and HMI systems• Working closely with domain expert data scientists, process and controls engineers, both within and outside the company to understand and automate transformation, normalization and other contextualization operations based on the types of analytics being performed on the inbound datasets, as well as model performance management requirements and design suitable inferencing instrumentation systems and practices that meet them• Delivering and presenting proofs of concept implementations that explain the key technologies you have selected for your design and the recommended patterns of practice for ongoing development and lifecycle management. The target audience for these efforts span the company and include project stakeholders, data scientists, process experts, other domain architects and relevant technical communities of practice interested in leveraging your code for their own projects• Working with your fellow developers using agile development practices, and continually improving development methods with the goal of automating the build, integration, deployment and monitoring of production inferencing and dataset delivery systems• Working with the relevant communities of practice on roadmaps, and serving as a trusted committer for your code for inner sourcing efforts with other development teams in the company
Education & Experience• Advanced degrees in computer science and data science strongly preferred, though an equivalent level engineering, data science or mathematics degree, a technical undergraduate degree and relevant experience will also be considered• 3+ years of experience working with data scientists in a large-scale data engineering or production machine learning inferencing capacity, working with various types of supervised and unsupervised learning algorithms for classification, recommendation, anomaly detection, clustering and segmentation, as well as CNNs, RNNs or other deep learning algorithms• 3+ years of full-stack experience developing large scale distributed systems and multi-tier applications• 6 years of programming proficiency in, at least, one modern JVM language (e.g. Scala) and at least one other high-level programming language such as Python• 2+ years of production DevOps experience• 2+ years of programming on the Apache Spark platform, leveraging both low level RDD and MLlib APIs and the higher-level APIs (SparkContext, DataFrames, DataSets, GraphFrames, SparkSQL, SparkML). Demonstrated deep understanding of Spark core architecture including physical plans, DAGs, UDFs, job management and resource management• Familiarity with MLflow and a demonstrated ability to implement in Databricks on AWS• Demonstrated experience working with inner sourcing initiatives, serving both as a trusted committer and contributor• Strong technical collaboration and communication skills• Unwavering commitment to coding best practice and a strong proponent of code review• Cultural bias towards continual learning, sharing best practice, encouraging and elevating less experienced colleagues as they learn Additional Technical Qualifications• Proficiency with functional programming methods and their appropriate use in distributed systems• Experience with AWS foundational compute services, including S3 and EC2, ECS and EKS, IAM and CloudWatch• Experience working with Kubernetes and Docker• Experience with continuous integration and continuous deployment methodologies• Experience with data management fundamentals and data storage principles Other Qualifications• Strong relationship building skills• Proven success working in highly matrix environment.• Excellent analytical and decision-making abilities.• Must demonstrate a proven willingness to go the extra mile, to take on the things that need to be done and maintain a positive attitude that can adapt to change.• Strong leadership and excellent verbal and written communications skills, with the ability to develop and sell ideas.- ID: #43733475
- State: North Carolina Charlotte 28201 Charlotte USA
- City: Charlotte
- Salary: Depends on Experience
- Job type: Permanent
- Showed: 2022-07-01
- Deadline: 2022-08-29
- Category: Et cetera