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Machine Learning Operations jobs in United States

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Skill:Machine Learning Operations

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1–2 jobs· newest first

Senior Data Engineer
Keebo · Remote, US
$170K–$200KRemote · Full-time · Senior
Director, Applied AI Engineering
ICW Group · San Diego, US
$161K–$288KManager

+10K new in the last hour

K

Senior Data Engineer

Keebo · Posted Nov 10, 2026

Remote, United States
Remote
Full-time · Senior
$170K–$200K per year
5+ years

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Design and scale data pipelines and machine learning infrastructure for an AI-first platform, using AI tools to multiply output and working with product/ML engineers.

Compensation

The base salary is $170,000 to $200,000 for US-based candidates, plus equity.

Responsibilities

Design and build reliable data pipelines that process large volumes of customer warehouse data
Build and run the machine learning operations infrastructure that takes models from training to production: feature pipelines, training jobs, deployment, and monitoring
Own data quality and data modeling to ensure accurate and trustworthy data
Use AI coding tools effectively by writing clear specs and context, running agents on parallel workstreams, and reviewing their output critically
Build shared AI workflows, guardrails, and review standards

Requirements

Nice to have: Snowflake
Nice to have: Databricks
Nice to have: Time-series forecasting
Nice to have: Regression
Nice to have: Anomaly detection

Skills

Data engineering Software engineering SQL Python Dagster Airflow Temporal Machine learning operations Data modeling Cloud platforms Containers Automated deploy pipelines Snowflake Databricks AI coding agents

Benefits

Equity
Medical
dental
vision benefits
401(k) retirement program

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Director, Applied AI Engineering

ICW Group · Posted Nov 5, 2026

San Diego, California, United States
Manager
$161K–$288K per year
10+ years

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Senior leader responsible for delivery and operation of generative and agentic AI solutions across the enterprise.

Compensation

The current range for this position is $160,745.90 - $287,738.43

Responsibilities

Lead design, development, and production delivery of generative and agentic AI solutions
Own AI Platforms and establish engineering standards
Collaborate with data services, cloud, product management, and governance
Direct delivery model and team structure
Partner with risk and governance for approvals

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or related field
Nice to have: Master's degree in a technical or quantitative discipline
Nice to have: Cloud certifications (AWS Certified Machine Learning Engineer, AWS Certified Solutions Architect, Microsoft Certified Azure AI Engineer)
Nice to have: Agile certifications (CSM, SAFe, PMI-ACP)

Skills

Generative AI Agentic AI Foundation model selection Model lifecycle management

Evaluation methods

Bedrock AgentCore

Machine learning operations

Project management

Benefits

Medical, dental, and vision plans
401K retirement plans with company match
Bonus potential
Paid Time Off
Paid holidays

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