Senior ML Data Lab Solution Architect
Do you love building software and thinking big about how data and AI can change the world? Are you a data and analytics specialist? Do you have deep expertise in developing platforms optimized for analytics and machine learning solutions at scale? Would you like a career that gives you opportunities to help customers and partners use cloud computing services to build new ML solutions, faster, and at lower cost?
At AWS, we're hiring highly technical ML platform solution architects and engineers to collaborate with our customers on building solutions in database, data management, and analytics/machine learning. AWS Data Labs are a global and online based facility where customers come to build data and analytics platforms. You will focus on real time and batch-based data processing, business intelligence, analytics, and machine learning platforms. These solutions are built alongside the customer and quickly put into production use in a matter of weeks. You'll work closely with AWS Field Teams including Solution Architects, Technical Account Managers, and AWS Service Developers to partner with customers to solve hard problems with data. Every day, you'll be working with AWS Services and Data Labs Customers to determine the optimal implementation, build it, prove it works, extract documents and CloudFormation templates to speed project delivery. If you are builder, and love data, then this could be your ideal job!
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded architect and enable them to take on more complex tasks in the future. BASIC QUALIFICATIONS
• BS level technical degree required; Computer Science or Mathematics background preferred.
• 10+ years of Machine Learning and/or Analytics Systems development and deployment experience, IT systems and engineering experience, security and compliance experience, etc.
• Experience of software development and/or IT and implementation/consulting experience.
• Experience implementation and tuning in the Big Data Ecosystem, (such as EMR, Hadoop, Spark, R, Presto, Hive), ML Platforms (SageMaker, Kubeflow, Azure Machine Learning, SAS, Domino), and MLOps (model development, orchestration and deployment, monitoring, optimization).
• Track record of implementing AWS services in a variety of business environments such as large enterprises and start-ups. PREFERRED QUALIFICATIONS
• Knowledge of foundation infrastructure requirements such as Networking, Storage, and Hardware Optimization.
• Ability to understand complex business requirements and render them as prototype systems with quick turnaround time.
• Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external organizations and virtual teams.
• Hands on experience leading large-scale big data and analytics projects.
• Demonstrated industry leadership in the fields of Big Data processing, Data Sciences and Machine Learning.
• Deep understanding of data, application, server, and network security
• Experience with Statistics, Machine Learning and Predictive Modeling.
• Hands on experience as a database, data warehouse, big data/analytics developer or administrator, or work as a data scientist.
• Hands on experience architecting, deploying and maintaining production machine learning systems.
• Experience working within the software development or Internet industries is highly desired.
• Technical degrees in computer science, software engineering, or mathematics
• Working knowledge of modern software development practices and technologies such as agile methodologies and DevOps/MLOps.
• AWS Certification, eg. AWS Solutions Architect, Big Data, Developer, Machine Learning, DevOps, SysOps
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit US Disability Accommodations.