Address
Form of workTOP Skills:
Python – CI/CD – programming
AWS Cloud engineering
MUST HAVE: AWS (Sagemaker, Lambdas S3 Buckets) / ETL / Python / Machine Learning Ops experience.
Sr. AWS Cloud Engineer w/ Machine Learning Ops
As a Cloud Engineer, build and maintain large scale ML Infrastructure and ML pipelines. Contribute to building advanced analytics, Machine Learning platform and tools to enable both prediction and optimization of models. Extend existing ML Platform and frameworks for scaling model training & deployment. Partner closely with various business & engineering teams to drive the adoption, integration of model outputs. This role is a critical element to using the power of Data Science in delivering our clients promise of creating the best customer experiences in financial services.
- Has Bachelor’s or Master’s Degree in a technology related field (e.g. Engineering, Computer Science, etc.).
- Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.).
- Experience in building cloud native applications using AWS services like S3, RDS, CFT, SNS, SQS, Step functions, Event Bridge, cloud watch etc.,
- Experience with building data pipelines in getting the data required to build, deploy and evaluate ML models, using tools like Apache Spark, AWS Glue or other distributed data processing frameworks.
- Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies.
- Strong knowledge of developing highly scalable distributed systems using Open-source technologies.
- 5+ years of proven experience in implementing Big data solutions in data analytics space.
- Experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker.
- Extensive experience working with Machine Learning models with respect to deployment, inference, tuning, and measurement required.
- Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).
- Solid experience in Agile methodologies (Kanban and SCRUM).
- Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models.
- Partner with Data Scientists and to help use the foundational platform upon which models can be built and trained.
- Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers).
- Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics.
- Exploring new technology trends and leveraging them to simplify our data and ML ecosystem.
- Driving Innovation and implementing solutions with future thinking.
- Guiding teams to improve development agility and productivity.
- Resolving technical roadblocks and mitigating potential risks.
- Delivering system automation by setting up continuous integration/continuous delivery pipelines.
We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.
The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
