About the Job
The Data Sceintest will lead efforts to leverage AI/ML to improve the operation and service of analytical instruments and laboratory equipment by partnering with our Product Owners and SAFe development teams to transform user stories into deployed reality. You’ll be working with a range of technologies and designing solutions to our customers’ biggest challenges. We’re looking for top architects, system and software engineers capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Your ideas and solutions will affect hundreds of product lines and thousands of customers.
• Understand the customer’s business need and guide them to a solution using AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .
• Assist our business partners by being able to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
• Use Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help our customers build DL models.
• Use SparkML and Amazon Machine Learning (AML) to build ML models.
• Work with our Big Data teams to analyze, extract, normalize, and label relevant data.
• Work with our SAFEe DevOps teams to operationalize models after they are built.
• Assist our TechOps with identifying model drift and retraining models.
• Research and implement novel ML and DL approaches, including using FPGA.
• Graduate degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.)
• 5+ years of industry experience in predictive modeling and analysis
• Good skills with programming languages, such as Java or C/C++
• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately identify cause and effect relationships
• Consulting experience and track record of helping customers with their AI needs
• Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences
• Experience using Python and/or R
• Knowledge of SparkML
• Able to write production level code, which is well-written and explainable
• Experience using ML libraries, such as scikit-learn, caret, mlr, mllib
• Experience working with GPUs to develop models
• Experience handling terabyte size datasets
• Track record of diving into data to discover hidden patterns
• Familiarity with using data visualization tools
• Knowledge and experience of writing and tuning SQL
• Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
• Experience giving data presentations
• Strong written and verbal communication skills
• Experience with AWS technologies like Redshift, S3, EC2, Data Pipeline, & EMR
• Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our customer’s organization
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment