Manager, Machine Learning Operations

Job not on LinkedIn

🕒 October 6

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Kohls Construction

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏗️ Construction

🌾 Agriculture

Construction • Agriculture

Kohls Construction is a company whose name indicates it operates in the construction sector. The company's LinkedIn industry is listed as Farming, suggesting its work may be focused on agricultural or farm-related construction, site development, or infrastructure services for agricultural clients. Public information is limited from the supplied data, so this description is conservative and based on the company name plus the LinkedIn industry tag.

📋 Description

• Manage a team of Machine Learning Operations Engineers • Lead implementation of the full machine learning lifecycle • Build and scale ETL pipelines • Deploy Data Scientist-developed models into customer-facing applications • Enable organizational throughput through cloud infrastructure and tooling • Own the roadmap for Machine Learning Engineering and Data Science tools • Develop reusable frameworks and standardized solutions for model implementation • Research, prototype and instruct the team on machine learning infrastructure • Move decisions forward and eliminate blockers • Provide technical thought leadership on cloud-based tools and ML lifecycle infrastructure • Establish best practices and foster continuous learning and development • Train and coach engineers through pair programming and code review • Contribute to development, monitoring, alerting and automated testing frameworks • Ensure reliability, performance and integrity of data pipelines, models and infrastructure • Document and communicate implementations and best practices across Kohl’s data organization • Stay current with Google Cloud Platform services and evolving MLE and ML Ops best practices • Perform additional assigned tasks

🎯 Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field • 5+ years of experience as a Machine Learning Engineer with a proven track record of successful, independent, project delivery • 2+ years of managerial or leadership experience in Data Science or Analytics organizations • Expertise in ML Ops practices, including Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving, and automated testing frameworks • Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments • In-depth knowledge of cloud platforms, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc • Extensive expertise with CI/CD and IaC best practices • Extensive knowledge of distributed computing and big data technologies such as Spark, Kubeflow, Airflow and SQL • Extensive expertise in Python and machine learning libraries such as TensorFlow, PyTorch and scikit-learn • Experience working in Agile environments with an emphasis on iterative development and continuous delivery • Ability to comply with dress code requirements • Basic math and reading skills, legible handwriting, and basic computer operation • Ability to maintain prompt and regular attendance and meet scheduling requirements • Ability to learn and comply with company policies, procedures, standards and guidelines • Ability to give and receive direction from leadership and company personnel • Ability to work as part of a team and interact effectively and appropriately with others • Ability to maintain composure and work in a fast-paced environment while accomplishing multiple tasks within established timeframes • Ability to satisfactorily complete company training programs • Ability to use a personal computer for communication and report preparation • Ability to plan, prioritize and monitor activities across business units • Ability to complete or oversee assigned projects in a timely manner

🏖️ Benefits

• Remote work arrangement • Full-time employment • Company training programs • Reasonable accommodations for individuals with disabilities

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