Tiger Analytics

Machine Learning Architect

Tiger Analytics • $150K — $180K *
US-AnywhereRemote in New Jersey, US
Enterprise Technology
8 - 10 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field.
  • 10+ years of hands-on experience with advanced analytics solutions in a corporate setting, including 4 years programming in Python.
  • 7+ years of experience in productionizing, monitoring, and maintaining models.
  • Strong programming skills in Python and familiarity with ML libraries like scikit-learn, TensorFlow, and PyTorch.
  • Deep understanding of MLOps tools such as MLflow, Kubeflow, and SageMaker.

Responsibilities

  • Design system architecture for ML and AI solutions across various business domains.
  • Lead discussions on ML system design and make key design choices for model serving and data pipelines.
  • Architect cloud-native platforms for model training, validation, deployment, and monitoring (AWS/GCP/Azure).
  • Build reusable components and reference architectures for the ML lifecycle.
  • Define best practices in model versioning and CI/CD for ML, including testing and rollback strategies.
  • Deploy and maintain ML pipelines in production environments.
  • Collaborate as part of an Agile team to enhance big data and ML applications.

Benefits

  • Excellent opportunity for career development in a fast-growing entrepreneurial environment.
  • High degree of individual responsibility in the role.
Full Job Description
You will be responsible for:
  • Highly experienced Machine Learning Architect with a proven track record of designing and delivering end-to-end ML solutions across diverse business domains. The ideal candidate will have over 10 years of experience in data science, machine learning, and MLOps, and a deep understanding of scalable system design, model lifecycle management, and production-grade deployment pipelines.
  • This is a strategic and hands-on role, involving collaboration with data scientists, engineers, product teams, and business stakeholders to architect solutions that are robust, scalable, and aligned with business goals
  • You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

What you'll do in the role-
  • Design and define system architecture for ML and AI-driven solutions across multiple business verticals.
  • Lead ML system design discussions and make high-level design choices for model serving, data pipelines, and MLOps frameworks.
  • Architect scalable and secure cloud-native platforms for ML model training, validation, deployment, and monitoring (AWS/GCP/Azure).
  • Build reusable components and reference architectures for various stages of the ML lifecycle.
  • Define and enforce best practices in model versioning, CI/CD for ML, testing, and rollback strategies
  • Deploy and manage machine learning & data pipelines in production environments.
  • Work on containerization and orchestration solutions for model deployment.
  • Participate in fast iteration cycles, adapting to evolving project requirements.
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Collaborate with Data scientists, software engineers, data engineers, and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting and automated model deployment.
  • Ability to work with a global team, playing a key role in communicating problem context to the remote teams
  • Excellent communication and teamwork skills

Basic Qualification-
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
  • Typically requires 10+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate environment with at least 4 years of experience programming with Python.
  • At least 7 years of experience productionizing, monitoring, and maintaining models
  • Strong programming skills in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Deep experience with MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, or Vertex AI.
  • Hands-on experience designing ML systems using cloud platforms like AWS, Azure, or GCP.
  • Strong understanding of data engineering, APIs, CI/CD pipelines, and model observability.
  • Excellent communication and stakeholder management skills.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

About Tiger Analytics

Tiger Analytics is a consulting firm that provides data analytics consulting services to businesses. The company specializes in data science, machine learning, and artificial intelligence. Tiger Analytics helps businesses to leverage data to make better decisions, improve operations, and drive growth. The company has worked with clients in a variety of industries, including healthcare, retail, finance, and technology.
Learn more about Tiger Analytics
Size
500 employees
Industry
Information Technology
Net Income
$1 million
Founded
2011
5 Year Trend
+50%
Revenue
$10 million
* Ladders Estimates

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