ZS Associates - Chicago, IL

posted 2 months ago

Full-time - Mid Level
Remote - Chicago, IL
Professional, Scientific, and Technical Services

About the position

As a Machine Learning Engineering Specialist in the AI Innovation Lab at ZS, you will be part of a dynamic team focused on leveraging advanced machine learning and engineering capabilities to create continuous business value for clients. This role is integral to ZS's Scaled AI practice, where you will collaborate closely with data scientists to develop state-of-the-art AI models and deploy advanced machine learning pipelines. Your work will encompass the entire machine learning lifecycle, from design and implementation to testing and deployment, ensuring that the solutions you create are robust, scalable, and aligned with best practices in the industry. In this position, you will be responsible for designing and implementing technical features that leverage the best practices for the technology stack in use. You will collaborate with client-facing teams to gather and analyze technical requirements, ensuring that the solutions developed meet the needs of our clients. Your role will also involve writing production-ready code that is easily testable and maintainable, while adhering to architecture and design guidelines. You will participate in code reviews, write unit tests, and engage in agile ceremonies to communicate progress and address any issues that arise. Additionally, you will have the opportunity to mentor and groom technical talent within the team, contributing to the overall growth and development of your colleagues. Your expertise in deploying and productionizing machine learning models at scale will be crucial, as will your ability to adapt to new technologies and innovate solutions that drive impact. ZS values a collaborative culture, and you will be encouraged to share your findings and insights with the team, fostering an environment of continuous learning and improvement.

Responsibilities

  • Design and implement technical features leveraging best practices for the technology stack being used
  • Collaborate with client-facing teams to understand solution context and contribute to technical requirement gathering and analysis
  • Work with technical architects on the team to validate design and implementation approach
  • Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors
  • Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, and periodic design/code reviews
  • Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths
  • Use 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 the latest technologies through rapid learning, conducting proofs-of-concept and creating prototype solutions
  • Support the project architect in designing modules/components of the overall project/product architecture
  • Break down large features into estimable tasks, lead estimation, and can defend them with clients
  • Implement complex features with limited guidance from the engineering lead
  • Systematically debug code issues/bugs using stack traces, logs, monitoring tools, and other resources
  • Perform code/script reviews of senior engineers in the team
  • Mentor and groom technical talent within the team

Requirements

  • At least 5+ relevant hands-on experience in deploying and productionizing ML models at scale
  • Expertise in designing, configuring, and using ML Engineering platforms like Sagemaker, MLFlow, Kubeflow, or other platforms
  • Experience with big data technologies such as Hive, Spark, Hadoop, and queuing systems like Apache Kafka/Rabbit MQ/AWS Kinesis
  • Ability to quickly adapt to new technology and be innovative in creating solutions
  • Ability to independently run POCs on new technologies and document findings to share
  • Strong in at least one of the programming languages - PySpark, Python, Java, Scala, etc., and programming basics - Data Structures
  • Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, ingestion patterns (batch, real-time)
  • Experience in designing and implementation of solutions on distributed computing and cloud services platforms (AWS, Azure, Google Cloud Platform)
  • Hands-on experience building CI/CD pipelines and awareness of practices for application monitoring

Nice-to-haves

  • AWS/Azure Solutions Architect certification with an understanding of broader AWS/Azure stack
  • Understanding of DevOps CI/CD, data security, experience in designing on cloud platforms
  • Willingness to travel to other global offices as needed to work with the client or other internal project teams

Benefits

  • Comprehensive total rewards package including health and well-being
  • Financial planning support
  • Annual leave
  • Personal growth and professional development opportunities
  • Robust skills development programs
  • Multiple career progression options
  • Internal mobility paths
  • Flexible working arrangements combining work from home and on-site presence
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service