Machine Learning Architect
Tiger Analytics, United States

Experience
1 Year
Salary
0 - 0
Job Type
Job Shift
Job Category
Traveling
No
Career Level
Telecommute
Qualification
Professional
Total Vacancies
1 Job
Posted on
May 15, 2021
Last Date
Jun 15, 2021
Location(s)

Job Description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are one of the highest rated employers on Glassdoor.

If you are passionate about working on unstructured business problems that can be solved using data, we would like to talk to you.

We are looking for a Machine Learning Architect for our team. As part of this job, you will be responsible for:

Mentorship and solution support to client facing Data and ML Engineers across key accounts

  • Review data and machine learning engineer work and proactively establish adoption of best practices and frameworks that improve productivity and client satisfaction
  • Work with the DevOps, MLE team to onboard and productionize Data Science models at scale.
  • Building reusable production data pipelines for implemented machine learning models
  • Writing production quality code and libraries that can be packaged as containers, installed and deployed
  • Coordinate between onsite and offshore leadership for regular updates

    Engage key client stakeholders to

    • Review and provide best solutions on the existing or new architecture requirements.
    • Recommend strategies to improve resiliency, security, and optimize costs.
    • Analyse, architect, design, and actively develop analytics frameworks, data lakes, and other cloud-based machine learning solutions.
    • Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions.
    • Creating Scalable Machine Learning systems that are highly performant

    Requirements

    • Demonstrates up-to-date knowledge in software engineering practices and provides solutions for the development, implementation and scaling, execution, validation, monitoring, and improvement of data science solutions
    • Collaborate with data engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments.
    • Manage the infrastructure and data pipelines needed to bring ML solution to production.
    • Demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created and maintain scalable machine learning solutions in production
    • Abstracts complexity of production for machine learning using containers
    • Troubleshoots production machine learning model issues, including recommendations for retrain, revalidate, and improvements
    • Experience with Big Data Projects using multiple types of structured and unstructured data
    • Ability to work with a global team, playing a key role in communicating problem context to the remote teams
    • Excellent communication and teamwork skills
    • Bachelor's degree or higher in computer science or related

    Additional Skills Required

    • Technologies used would include Python (multiple versions), Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
    • Test driven development (prefer py.test / nose), experience with Cloud environments.
    • Proficiency in statistical tools, relational databases amp; expertise in programming languages like Python/SQL is desired.
    • Knowledge of all aspects of ML dev lifecycle automation- Model Development, Training, Feature engineering, Model Deployment, Model Monitoring and Governance
    • 1-3 yrs experience with Devops tools such as uDeploy, Flux, Argo-CD or JenkinsX
    • 1-3 yrs experience on ML frameworks like Scikitlearn, Tensorflow, Keras etc
    • 1-3 yrs experience on MLflow, Airflow, Kubernetes
    • 1-2 yrs experience on on any of the cloud native MLaaS offerings like AWS SageMaker, AzureML or Google AI platform

    Benefits

    Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

    Job Specification

    Job Rewards and Benefits

    Tiger Analytics

    Information Technology and Services - Dallas, United States
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