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Lead Machine Learning Engineer - News

Disney
Glendale, USA
Full-time
Lead · 7+ years experience
Onsite
Discovered 3 weeks ago
awsdatabricksdatadogkafkakinesisspark

Full Job Posting

Responsibilities and Duties of the Role:

  • Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence
  • Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries
  • Drive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, RAGs
  • Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
  • Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution
  • Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response
  • Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement
  • Contribute to technical documentation and promote knowledge sharing across teams

Required Education, Experience/Skills/Training:

  • Minimum and Preferred. Inclusive of Licenses/Certs (include functional experience as well as behavioral attributes and/or leadership capabilities)
  • Basic Qualifications
  • Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
  • 7+ years of software engineering experience
  • 5+ years of hands-on experience developing and deploying machine learning systems in production
  • Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
  • Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low-latency online serving
  • Experience designing and developing backend microservices for large-scale distributed systems using REST
  • Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
  • Familiarity with developing and deploying Spark and ML pipelines
  • Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
  • Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals
  • Experience with observability tools for metrics, logging, and monitoring such as Datadog
  • Experience working in Agile/Scrum development environments
  • Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment
  • Job Posting Segment:
  • Job Posting Primary Business:
  • Primary Job Posting Category:
  • Employment Type:
  • Primary City, State, Region, Postal Code:
  • Alternate City, State, Region, Postal Code:
  • Date Posted:

Qualifications

  • Minimum and Preferred. Inclusive of Licenses/Certs (include functional experience as well as behavioral attributes and/or leadership capabilities)
  • Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
  • 7+ years of software engineering experience
  • 5+ years of hands-on experience developing and deploying machine learning systems in production
  • Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
  • Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low-latency online serving
  • Experience designing and developing backend microservices for large-scale distributed systems using REST
  • Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
  • Familiarity with developing and deploying Spark and ML pipelines
  • Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
  • Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals
  • Experience with observability tools for metrics, logging, and monitoring such as Datadog
  • Experience working in Agile/Scrum development environments
  • Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment
  • Date Posted

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