Senior AI/ML Engineer (MLOps)

Published date Posted on Indeed on Aug 06, 2022 (8 d ago)

Overview

Concentrix Catalyst is the experience design and engineering team of Concentrix, a leading global solutions company that reimagines everything CX through strategy, talent, technology. We combine human-centered design, powerful data and strong tech to accelerate CX transormation at scale.

The Catalyst Team is seeking a Senior AI/ML Engineer to join our team as a full-time employee.

The AI Engineering Community has Member with ML Engineering and DevOps skills who are responsible for taking Data Science models and scaling them out to production while ensuring that business SLAs, including security requirements are adhered to. They are an important part of the AI Engineering Community ensuring the continuous feedback loop that is vital for enhancing validity and accuracy of AI workloads that:
  • Have a mix of technical skills in software engineering, AI hardware, DevOps toolchains, and ML model management, as well as process skills in areas such as agile, reliability engineering, and liaising with Data Scientists and Data Engineers
  • Facilitate cooperation between ML Engineers and Data Scientists, Data Engineers, Security, Developers, and IT Operations by enforcing shared objectives and enabling collaboration tools across their organizations.
  • Tasked the ML Engineer role with aiding Data Science Teams in formulating best practices for data science platform selection, ML model testing, serving, deployment and monitoring, and availability of ML infrastructure.

Open to remote locations, excluding Colorado.

Responsibilities

Programming and computer science along with software engineering and DevOps skills and experiences:

  • Distributed systems - know-how of AI hardware (GPUs, SSDs, InfiniBand, etc.), experience in managing and troubleshooting distributed systems, such as such as Apache Hadoop, Apache Spark and Apache Kafka, and familiarity with public cloud IaaS/PaaS
  • Familiar with common techniques and general ML programming to ensure quality of algorithms before pushing them to production
  • Work with Data Engineers to identify and optimize the interdependencies between data stores, applications, development and execution of models
  • Apart from making the appropriate data accessible and available for data scientists, they play an instrumental role in providing optimized infrastructure to build and train the models
The AI Engineering is for focused on the design, development, execution, deployment and support of platforms and infrastructures to facilitate the job of Data Scientists and AI tools. Specific responsibilities include:
  • Convert Machine Learning models into Application Program Interfaces (APIs) so that other applications consume and reuse
  • Build data ingestion and data transformation infrastructure to stream appropriate data into analytic, ML and AI applications
  • Automate infrastructure that Data Science Teams use
  • Understand the uses and connectivity of various analytic and AI applications and how they can be integrated into a complex architecture
  • Set-up and manage analytic, ML and AI development and product infrastructure.
  • Optimize various tasks in the ML pipeline
  • Collaborate with Data Scientists and streamline the process of delivering ML models into Production by using software engineering best practices for testing, security, tuning and optimization
  • Optimizing ML models for performance, scalability and reliability with a focus on continuous improvement
  • Interface with Data Engineers to ensure there is an automated data pipeline and adequate data integrity for building and ensuring continuous operation of ML models
  • Work with Security, Privacy and Compliance specialists to have the full ML pipeline secured and documented in compliance with existing regulations (e.g., HIPAA, GDPR, SOX, etc.)
  • Mentor junior product developers
  • Development and Functional Testing of committed to stories, tasks, and defects within a sprint cycle with high quality every time
  • Development and maintenance of automated tests and CI/CD scripts that provides high coverage of all the key positive and negative use cases that customers need to ensure no regression occurs from release to release
  • Constantly scan the landscape for new tools that can be used for improving the DataOps and MLOps processes

Qualifications

  • 5+ years of experience as a software developer for web-based large-scale enterprise products
  • Expert level coding in Python and Node.js
  • Experience with Machine Learning Frameworks
  • Experience in Modular technologies such as Microservices and Docker Containers
  • Proven ability to develop resilient code (best practice error handling) that performs and scales for large enterprise needs
  • Deep expertise in developing REST-based API's (json/yaml) leveraging both NoSql and Sql databases
  • Knowledge of CI/CD processes, DevOps toolchains, template and/or container based deployment models
  • Experience with multiple Cloud services - vmWare, IBM Cloud, AWS, MS Azure, Google Cloud
  • Experience with Big Data architectures including Spark/Hadoop, HDFS, analytical processing.
  • Experienced with Jira / Confluence, GitHub, Travis
  • Bachelor's degree in Computer Science or equivalent; Master’s degree preferred
  • Technical Skills: Python, Javascript, Angular or React, Node.js, Flask, SQL Databases, No-SQL Databases, Machine Learning Frameworks, Kubernetes, Kubeflow, Docker, TravisCI, Git, VmWare, AWS, Azure, Google Cloud and IBM.

~ In order to provide equal employment and advancement opportunities to all individuals, employment decisions at Concentrix Catalyst are based exclusively on merit. Concentrix Catalyst does not discriminate in employment opportunities or practices on the basis of race, color, religion, sex, including gender identity and identity expression, national origin, age, or any other characteristic protected by law.

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