Sr Machine Learning Engineer

undefined ago • 5 Years + • Research Development

Job Summary

Job Description

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.
Must have:
  • Develop and optimize machine learning models for various applications.
  • Preprocess and analyze large datasets to extract meaningful insights.
  • Deploy ML solutions into production environments using appropriate tools and frameworks.
  • Collaborate with cross-functional teams to integrate ML models into products and services.
  • Monitor and evaluate the performance of deployed models.
  • Minimum of 5 years of relevant work experience.
  • Bachelor's degree or equivalent experience.
  • Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
  • Several years of experience in designing, implementing, and deploying machine learning models.
Good to have:
  • Strong understanding of supervised and unsupervised learning, deep learning algorithms, model evaluation, and algorithm tuning.
  • Proven experience working with tabular and textual data, including advanced preprocessing techniques.
  • Proficiency in Python and Java, with hands-on experience building RESTful APIs and integrating AI/ML models into live services.
  • Solid grasp of containerization (Docker, Kubernetes), and MLOps frameworks (MLflow, TFX, or Kubeflow), streaming data systems (Kafka, Flink) and real-time ML inference.
  • Demonstrated experience in system architecture, solution design, and building scalable AI/ML systems.
  • Familiarity with agentic and multi-agent frameworks.
Perks:
  • Flexible work environment
  • Employee shares options
  • Health and life insurance
  • Valuable benefits and resources to help you care for the whole you
  • Hybrid work model (3 days in office, 2 days home/office)

Job Details

Job Summary:

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Job Description:

Essential Responsibilities:

  • Develop and optimize machine learning models for various applications.
  • Preprocess and analyze large datasets to extract meaningful insights.
  • Deploy ML solutions into production environments using appropriate tools and frameworks.
  • Collaborate with cross-functional teams to integrate ML models into products and services.
  • Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

  • Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
  • Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
  • Several years of experience in designing, implementing, and deploying machine learning models.

Preferred Qualification:

  • Strong understanding of supervised and unsupervised learning, deep learning algorithms, model evaluation, and algorithm tuning.
  • Proven experience working with tabular and textual data, including advanced preprocessing techniques.
  • Proficiency in Python (preferred) and Java, with hands-on experience building RESTful APIs and integrating AI/ML models into live services.
  • Solid grasp of containerization (Docker, Kubernetes), and MLOps frameworks (e.g., MLflow, TFX, or Kubeflow), streaming data systems (e.g., Kafka, Flink) and real-time ML inference.
  • Demonstrated experience in system architecture, solution design, and building scalable AI/ML systems.
  • Familiarity with agentic and multi agent frameworks is a plus

Subsidiary:

PayPal

Travel Percent:

0

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