Microsoft Azure

cloud, cloud provider, microsoft, infrastructure

Open jobs

4875

Companies looking for Azure

4386

Microsoft, when the world moved to the cloud, didn't want to be left holding the on-premise bag. Thus emerged Azure, a platform promising to deliver everything-as-a-service with the comforting familiarity of Windows Server underneath. It aimed to be the enterprise’s easy transition, a way to lift-and-shift workloads without retraining entire departments. The reality, of course, is a bit messier. Azure is powerful, undeniably, but navigating its vast ecosystem can feel like exploring a Byzantine bureaucracy.

It’s essentially Amazon Web Services, but with a distinctly Microsoft flavor – meaning more integration with existing Microsoft products, and a pricing structure that requires a PhD in economics to decipher. While AWS still dominates, Azure has carved out a strong niche with enterprises already deeply invested in the Microsoft stack. Today, it's a mature platform, powering everything from simple websites to complex AI applications, and constantly battling AWS and Google Cloud for cloud supremacy – a battle fought largely in PowerPoint presentations and quarterly earnings reports.

Used together with Azure

Additional Resources

Compare to other cloud platforms

Jobs (this month)

4875

Companies with Jobs

4386

Jobs in

All cities

Amsterdam

San Francisco

London

Paris

New York

Berlin

Copenhagen

Singapore

Tokyo

Sydney

Madrid

Rio De Janeiro

using Microsoft Azure for

All job types

Analytics Engineers

Data Engineers

Analysts

Data Scientists

Machine Learning Engineers

Others

but please no

Agile/Scrum

JIRA

Activity Schema

Adobe Analytics

Agile/Scrum

Artificial Intelligence/Machine Learning

Airbyte

Apache Airflow

Alation

Alteryx

Amplitude

Analytics

Analytics Engineering

Ansible

Apache Flink

Application Programming Interface (API)

AppDynamics

Redpanda

Webhooks

Argo CD

Apache Arrow

Astronomer

Amazon Athena

Apache Avro

Amazon Web Services (AWS)

Amazon Aurora

AWS CloudFormation

Amazon CloudWatch

Amazon EC2

Amazon EMR

AWS Glue

Amazon Kinesis

AWS Lambda

Amazon RDS

Microsoft Azure

Azure Data Factory

Azure DevOps

Bash

Apache Beam

Business Intelligence (BI)

Big Data

BigEye

Google BigQuery

Blendo

Blockchain

C

C#/.NET

Apache Cassandra

Cyber Security

Certified Cloud Security Professional (CCSP)

Certified Information Systems Security Professional (CISSP)

FinOps

Customer Data Platform (CDP)

Chef

Chroma

Continuous Integration/Continuous Delivery (CI/CD)

Circle CI

ClickHouse

Cloud Computing

Cloud Storage

Cloudflare

Azure Cosmos DB

Collibra

IBM Cognos

Computer Science

Confluence

C++

Customer Relationship Management (CRM)

Comma-Separated Values (CSV)

Cypress

Dagster

Dashboard

Data Analytics

Data Contracts

Data Engineering

Data Governance

Data Lake

Data Lakehouse

Data Management

Data Modelling

Data Quality

Data Science

Data Vault

Data Visualization

Databricks

Datacoral

Datadog

Google Cloud Dataflow

Datafold

Google Dataform

Dataiku

DataOps

Google Cloud Dataproc

Data Analysis Expressions (DAX)

dbt (data build tool)

Delta Lake

DevOps

Docker

Dremio

DuckDB

Data Warehouse

DynamoDB

Dynatrace

Elasticsearch/ELK Stack

Enterprise Resource Planning (ERP)

ETL/ELT

Ethereum

Binance

Non-Fungible Tokens (NFT)

Geographic Information System (GIS)

Decentralized Finance (DeFi)

Smart Contracts

Chainalysis

Web3

Microsoft Excel

Feather

Fivetran

Funnel

Google Cloud Platform (GCP)

GDPR/CCPA

Generative AI

Git

GitHub

GitLab

Go

Google Analytics

Google Cloud Composer

Google Cloud Data Fusion

Google Cloud Functions

Google Cloud Run

Google Sheets

Grafana

Google Tag Manager (GTM)

Apache Hadoop

Apache HBase

Hierarchical Data Format

Hadoop Distributed File System (HDFS)

Heap Analytics

Hevo Data

Apache Hive

HyperText Markup Language (HTML)

Hubspot

Hyper-V

IBM

Apache Iceberg

Informatica

Data Collection

Internet of Things (IoT)

Java

JavaScript

Jenkins

Jira

JavaScript Object Notation (JSON)

JSON Schema

Apache Kafka

Keras

Kibana

(Kimball) Dimensional Modeling

Kissmetrics

Key Performance Indicator (KPI)

Kubernetes

Linux

Large Language Models (LLM)

Logstash

Looker

Looker Studio

Luigi

Management

MariaDB

Marketing

Marketing Mix Modeling (MMM)

Master Data Management

Masthead Data

Matillion

MATLAB

Matomo

Matplotlib

Modern Data Stack

Meltano

Mendix

Metabase

Microsoft

Microsoft Fabric

Mixpanel

MLOps

Mode Analytics

MongoDB

Monte Carlo

MySQL

IBM Netezza

Neo4j

New Relic

Natural Language Processing (NLP)

NoSQL

NumPy

Opsgenie

Oracle

Optimized Row Columnar (ORC)

PagerDuty

Pandas

Apache Parquet

Pendo

Doctor of Philosophy (PhD)

Pinecone

Piwik PRO

Plausible Analytics

Playwright

Plotly

Polars

PostgreSQL

Microsoft Power BI

Microsoft PowerPoint

PowerShell

Prefect

Presto

Process Mining

Prometheus

Protocol Buffers

Pub/Sub

Pulumi

Puppet

Puppeteer

Pydantic

PySpark

Python

PyTorch

Qlik

Amazon QuickSight

R (Language)

Retrieval Augmented Generation (RAG)

Relational Database Management System (RDBMS)

React

Redash

Redis

Amazon Redshift

Recurrent Neural Networks

Rust

Amazon S3

Software as a Service (SaaS)

Amazon SageMaker

SAP

SAS

Scala

Scikit-learn

SciPy

Seaborn

Twilio Segment

Selenium

Singer

Sisense

Snowflake

Snowplow

Apache Spark

Splunk

SPSS

Structured Query Language (SQL)

SQLMesh

SQLFluff

SQLFmt

Microsoft SQL Server

SQL Server Analysis Services (SSAS)

SQL Server Integration Services (SSIS)

SQL Server Reporting Services

Stitch

Data Streaming

Supermetrics

Apache Superset

Azure Synapse Analytics

TIBCO Spotfire

Tableau

Talend

TensorFlow

Teradata

Bicep

Infrastructure as Code (IaC)

Azure Resource Manager (ARM)

Terraform

Terragrunt

Third Normal Form (3NF)

TOML

Trifacta

Apache Trino

Apache Druid

TypeScript

Unix

Visual Basic for Applications (VBA)

Vector DB

Vertica

VirtualBox

Virtual Machine

VMware

Microsoft Word

Extensible Markup Language (XML)

Xplenty

Yet Another Markup Language (YAML)

Motherduck

PostHog

Kestra

Omni Analytics

Thoughtspot

Lightdash

Hudi

Open Table Format (OTF)

Lance

machine learning engineer Senior Machine Learning Engineer - (Vendor Data) @ delivery-hero-se DE \| 2025-12-28 Delivery Hero’s Senior Machine Learning Engineer for Vendor Data promises end‑to‑end ML at scale across 70+ markets, designing and operating production systems that balance performance with cost.... read more »	AI/ML, Data Science, Cloud Computing, Data Management, MLOps, DataOps, TensorFlow, PyTorch, AWS, GCP, Azure, Docker, Kubernetes, CI/CD, Airflow, Grafana	Senior Machine Learning Engineer - (Vendor Data) delivery-hero-se (DE) FULL TIME \| JOB LISTED Delivery Hero’s Senior Machine Learning Engineer for Vendor Data promises end‑to‑end ML at scale across 70+ markets, designing and operating production systems that balance performance with cost. You’ll own the ML lifecycle, guardrails for reproducibility and responsible AI, and push for modern tooling across a cross‑functional vendor tribe. The tech roster is solid: TensorFlow, PyTorch, AWS/GCP/Azure, Docker, Kubernetes, Metaflow, MLflow, Airflow, Grafana. Expect cloud‑native, containerized services and CI/CD pipelines that try to keep pace with business growth and multi‑restaurant latency budgets. Berlin hybrid work, generous education and wellbeing perks sweeten the deal. What stands out is real, practical scale and a clear path to impact on thousands of vendors; what hurts is the inevitable tension between speed, governance, and cost in a profit‑driven marketplace. A gristly but authentic ML engineering role. Generated content Technology used AI/ML Data Science Cloud Computing Data Management MLOps DataOps TensorFlow PyTorch AWS GCP Azure Docker Kubernetes CI/CD Airflow Grafana Listed At 2025-12-28 2025-10-02 (original listing) Permalink View original posting
machine learning engineer Machine Learning Engineer @ jpmorganchase US \| 2025-12-28 JPMorgan Chase markets a machine-learning heavy role in its Digital Intelligence unit, a high-profile perch for building relevance and ranking models at scale. The job leans on large datasets, ML... read more »	AI/ML, Agile/Scrum, MLOps, Management, Computer Science, NLP, GenAI, LLM, Cloud Computing, AWS, GCP, Azure	Machine Learning Engineer jpmorganchase (US) FULL TIME \| JOB LISTED JPMorgan Chase markets a machine-learning heavy role in its Digital Intelligence unit, a high-profile perch for building relevance and ranking models at scale. The job leans on large datasets, ML Ops, and production-grade code, with a clear appetite for graph learning, recommender systems, NLP, RL, and Gen AI—plus cloud fluency across AWS, GCP, or Azure. The challenges are real: turning academic models into robust, auditable systems that survive production, managing risk from ML predictions, and aligning with senior stakeholders in a heavily regulated financial environment. The qualifications skew toward advanced degrees and hands-on cloud experience; the market will notice the bar is stylistically high, and the compensation talk is opaque until later. What stands out: direct exposure to scalable, impact-driven ML in finance, but the role risks bureaucracy and hype-dilution in equal measure. Generated content Technology used AI/ML Agile/Scrum MLOps Management Computer Science NLP GenAI LLM Cloud Computing AWS GCP Azure Listed At 2025-12-28 2025-09-11 (original listing) Permalink View original posting
promoted BigQuery Cost Optimization Guide by Masthead Data The BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of...	Learn More
machine learning engineer Lead Machine Learning Engineer @ thoughtworks SG \| 2025-12-27 This role is ambitious in its vision but lacks specificity in defining responsibilities and expectations. The job emphasizes leadership in ML engineering but fails to clearly outline the technical... read more »	AI/ML, Python, TensorFlow, PyTorch, MLOps, CI/CD, Data Science, Cloud Computing, IaC, Azure, AWS, GCP, Databricks, Management, Computer Science	Lead Machine Learning Engineer thoughtworks (SG) FULL TIME \| JOB LISTED This role is ambitious in its vision but lacks specificity in defining responsibilities and expectations. The job emphasizes leadership in ML engineering but fails to clearly outline the technical skills, tools, or deliverables expected. While the position highlights strategic thinking and collaboration, it does not specify the technologies or frameworks required, nor does it detail the measurable outcomes or performance metrics. The description is filled with vague language and generic claims, making it difficult to assess the actual skills and responsibilities. It aligns with the broader trend of overpromising and underdelivering in the ML engineering field, offering little clarity on what makes a successful candidate or what the role truly entails. Generated content Technology used AI/ML Python TensorFlow PyTorch MLOps CI/CD Data Science Cloud Computing IaC Azure AWS GCP Databricks Management Computer Science Listed At 2025-12-27 2025-04-14 (original listing) Permalink View original posting
machine learning engineer Machine Learning Engineer @ scribd US \| 2025-12-26 \| USD 126000 - 196000 / year Scribd's Machine Learning Engineer II sits on the Orion platform, building and tuning real-time ML systems that power recommendations and AskAI. Expect end-to-end ownership—from ingestion and... read more »	Spark, AI/ML, GenAI, Python, Go, Scala, Airflow, Databricks, AWS, Amazon SageMaker, LLM, API, Cloud Computing, AWS Lambda, CloudWatch, Datadog, Terraform, Azure, GCP, Computer Science	Machine Learning Engineer scribd (US) FULL TIME \| JOB LISTED Scribd's Machine Learning Engineer II sits on the Orion platform, building and tuning real-time ML systems that power recommendations and AskAI. Expect end-to-end ownership—from ingestion and feature engineering to training, deployment and monitoring—with a heavy inclination toward production-ready infra: feature stores, model registries, and embedding-based retrieval serving layers. The tech stack leans Python or Golang (Scala/Ruby optional), Airflow, Databricks, Spark, and AWS (ECS/EKS/Lambda). Embedding-based retrieval via Weaviate and exposure to SageMaker plus multiple LLM providers signal a production-first AI agenda, not playground experiments. Requirements demand 3+ years, cloud-ops experience, and comfort with scale and performance trade-offs. What stands out is platform-first scope and the GRIT culture; what nags is geographic salary fragmentation and a demanding near-real-time pace that prizes speed over daylight hours. Generated content Technology used Spark AI/ML GenAI Python Go Scala Airflow Databricks AWS Amazon SageMaker LLM API Cloud Computing AWS Lambda CloudWatch Datadog Terraform Azure GCP Computer Science Listed At 2025-12-26 2025-08-19 (original listing) Similar Jobs Loading... Permalink View original posting
machine learning engineer Machine Learning Engineer @ scribd US \| 2025-12-26 \| USD 103500 - 196000 / year Machine Learning Engineer II at Scribd, built to design, deploy, and optimize near real-time ML for millions across the Orion platform. Expect heavy exposure to an embedding-based retrieval stack... read more »	Spark, AI/ML, GenAI, Python, Go, Scala, Airflow, Databricks, AWS, Amazon SageMaker, LLM, API, Cloud Computing, AWS Lambda, CloudWatch, Datadog, Terraform, Azure, GCP, Computer Science	Machine Learning Engineer scribd (US) FULL TIME \| JOB LISTED Machine Learning Engineer II at Scribd, built to design, deploy, and optimize near real-time ML for millions across the Orion platform. Expect heavy exposure to an embedding-based retrieval stack (Weaviate), feature store and model registry, and direct product integrations from recommendations to AskAI. The tech radar is broad: Python or Go preferred; Spark, Databricks, Airflow for pipelines; AWS Sagemaker, multi-LLM providers; HTTP/gRPC interfaces; AWS infrastructure (Lambda, ECS, EKS, SQS) with observability via CloudWatch and Datadog; Terraform for infra. You will balance core platform improvements with product-grade features, run A/B tests, and ensure data accuracy. The gap is twofold: a) density of responsibilities across ML infra and product tie-ins; b) Scribd's in-person cadence and regional pay variance. It's a technically hands-on role in a well-financed but crowded ML marketplace. Generated content Technology used Spark AI/ML GenAI Python Go Scala Airflow Databricks AWS Amazon SageMaker LLM API Cloud Computing AWS Lambda CloudWatch Datadog Terraform Azure GCP Computer Science Listed At 2025-12-26 2025-08-19 (original listing) Permalink View original posting
machine learning engineer Manager, Machine Learning Engineering @ adobe US \| 2025-12-24 \| USD 168200 - 340100 / year Adobe's Firefly Foundry Manager for Applied Research asks you to shepherd a distributed team designing and curating large-scale training data for enterprise generative AI, turning research into... read more »	AI/ML, Cloud Computing, API, GenAI, Data Quality, Data Science, ETL/ELT, DWH, AWS, Azure, GCP, Spark, Databricks, Snowflake, MLOps, Data Management	Manager, Machine Learning Engineering adobe (US) FULL TIME \| JOB LISTED Adobe's Firefly Foundry Manager for Applied Research asks you to shepherd a distributed team designing and curating large-scale training data for enterprise generative AI, turning research into production-ready data pipelines while policing quality, bias, privacy, and brand safety. The role prizes deep domain fluency in ML data lifecycles, ETL/ELT at scale, and governance across cloud stacks (AWS, Azure, GCP) with Spark, Databricks, and Snowflake, plus expertise in annotation platforms and tools like DVC. It is heavy on cross-functional leadership and collaboration with researchers, ML engineers, and PMs, and it promises influence over model development via data availability. The salary is competitive, and the scope is enterprise-grade rather than consumer-gen AI hype. The pitfalls: a metrics-driven, potentially bureaucratic environment, high expectations for ethical AI, and risk of misalignment between research ambition and production reality. Generated content Technology used AI/ML Cloud Computing API GenAI Data Quality Data Science ETL/ELT DWH AWS Azure GCP Spark Databricks Snowflake MLOps Data Management Listed At 2025-12-24 2025-09-07 (original listing) Permalink View original posting

machine learning engineer Senior Machine Learning Engineer - (Vendor Data) @ delivery-hero-se DE \| 2025-12-28 Delivery Hero’s Senior Machine Learning Engineer for Vendor Data promises end‑to‑end ML at scale across 70+ markets, designing and operating production systems that balance performance with cost.... read more »	AI/ML, Data Science, Cloud Computing, Data Management, MLOps, DataOps, TensorFlow, PyTorch, AWS, GCP, Azure, Docker, Kubernetes, CI/CD, Airflow, Grafana	Senior Machine Learning Engineer - (Vendor Data) delivery-hero-se (DE) FULL TIME \| JOB LISTED Delivery Hero’s Senior Machine Learning Engineer for Vendor Data promises end‑to‑end ML at scale across 70+ markets, designing and operating production systems that balance performance with cost. You’ll own the ML lifecycle, guardrails for reproducibility and responsible AI, and push for modern tooling across a cross‑functional vendor tribe. The tech roster is solid: TensorFlow, PyTorch, AWS/GCP/Azure, Docker, Kubernetes, Metaflow, MLflow, Airflow, Grafana. Expect cloud‑native, containerized services and CI/CD pipelines that try to keep pace with business growth and multi‑restaurant latency budgets. Berlin hybrid work, generous education and wellbeing perks sweeten the deal. What stands out is real, practical scale and a clear path to impact on thousands of vendors; what hurts is the inevitable tension between speed, governance, and cost in a profit‑driven marketplace. A gristly but authentic ML engineering role. Generated content Technology used AI/ML Data Science Cloud Computing Data Management MLOps DataOps TensorFlow PyTorch AWS GCP Azure Docker Kubernetes CI/CD Airflow Grafana Listed At 2025-12-28 2025-10-02 (original listing) Permalink View original posting
machine learning engineer Machine Learning Engineer @ jpmorganchase US \| 2025-12-28 JPMorgan Chase markets a machine-learning heavy role in its Digital Intelligence unit, a high-profile perch for building relevance and ranking models at scale. The job leans on large datasets, ML... read more »	AI/ML, Agile/Scrum, MLOps, Management, Computer Science, NLP, GenAI, LLM, Cloud Computing, AWS, GCP, Azure	Machine Learning Engineer jpmorganchase (US) FULL TIME \| JOB LISTED JPMorgan Chase markets a machine-learning heavy role in its Digital Intelligence unit, a high-profile perch for building relevance and ranking models at scale. The job leans on large datasets, ML Ops, and production-grade code, with a clear appetite for graph learning, recommender systems, NLP, RL, and Gen AI—plus cloud fluency across AWS, GCP, or Azure. The challenges are real: turning academic models into robust, auditable systems that survive production, managing risk from ML predictions, and aligning with senior stakeholders in a heavily regulated financial environment. The qualifications skew toward advanced degrees and hands-on cloud experience; the market will notice the bar is stylistically high, and the compensation talk is opaque until later. What stands out: direct exposure to scalable, impact-driven ML in finance, but the role risks bureaucracy and hype-dilution in equal measure. Generated content Technology used AI/ML Agile/Scrum MLOps Management Computer Science NLP GenAI LLM Cloud Computing AWS GCP Azure Listed At 2025-12-28 2025-09-11 (original listing) Permalink View original posting
promoted BigQuery Cost Optimization Guide by Masthead Data The BigQuery Cost Optimization Guide is a valuable resource that offers a deep dive into understanding and managing the complexities of BigQuery costs. It provides practical guidelines and strategies to help you optimize both storage and compute expenses, ensuring you get the most value out of...	Learn More
machine learning engineer Lead Machine Learning Engineer @ thoughtworks SG \| 2025-12-27 This role is ambitious in its vision but lacks specificity in defining responsibilities and expectations. The job emphasizes leadership in ML engineering but fails to clearly outline the technical... read more »	AI/ML, Python, TensorFlow, PyTorch, MLOps, CI/CD, Data Science, Cloud Computing, IaC, Azure, AWS, GCP, Databricks, Management, Computer Science	Lead Machine Learning Engineer thoughtworks (SG) FULL TIME \| JOB LISTED This role is ambitious in its vision but lacks specificity in defining responsibilities and expectations. The job emphasizes leadership in ML engineering but fails to clearly outline the technical skills, tools, or deliverables expected. While the position highlights strategic thinking and collaboration, it does not specify the technologies or frameworks required, nor does it detail the measurable outcomes or performance metrics. The description is filled with vague language and generic claims, making it difficult to assess the actual skills and responsibilities. It aligns with the broader trend of overpromising and underdelivering in the ML engineering field, offering little clarity on what makes a successful candidate or what the role truly entails. Generated content Technology used AI/ML Python TensorFlow PyTorch MLOps CI/CD Data Science Cloud Computing IaC Azure AWS GCP Databricks Management Computer Science Listed At 2025-12-27 2025-04-14 (original listing) Permalink View original posting
machine learning engineer Machine Learning Engineer @ scribd US \| 2025-12-26 \| USD 126000 - 196000 / year Scribd's Machine Learning Engineer II sits on the Orion platform, building and tuning real-time ML systems that power recommendations and AskAI. Expect end-to-end ownership—from ingestion and... read more »	Spark, AI/ML, GenAI, Python, Go, Scala, Airflow, Databricks, AWS, Amazon SageMaker, LLM, API, Cloud Computing, AWS Lambda, CloudWatch, Datadog, Terraform, Azure, GCP, Computer Science	Machine Learning Engineer scribd (US) FULL TIME \| JOB LISTED Scribd's Machine Learning Engineer II sits on the Orion platform, building and tuning real-time ML systems that power recommendations and AskAI. Expect end-to-end ownership—from ingestion and feature engineering to training, deployment and monitoring—with a heavy inclination toward production-ready infra: feature stores, model registries, and embedding-based retrieval serving layers. The tech stack leans Python or Golang (Scala/Ruby optional), Airflow, Databricks, Spark, and AWS (ECS/EKS/Lambda). Embedding-based retrieval via Weaviate and exposure to SageMaker plus multiple LLM providers signal a production-first AI agenda, not playground experiments. Requirements demand 3+ years, cloud-ops experience, and comfort with scale and performance trade-offs. What stands out is platform-first scope and the GRIT culture; what nags is geographic salary fragmentation and a demanding near-real-time pace that prizes speed over daylight hours. Generated content Technology used Spark AI/ML GenAI Python Go Scala Airflow Databricks AWS Amazon SageMaker LLM API Cloud Computing AWS Lambda CloudWatch Datadog Terraform Azure GCP Computer Science Listed At 2025-12-26 2025-08-19 (original listing) Similar Jobs Loading... Permalink View original posting
machine learning engineer Machine Learning Engineer @ scribd US \| 2025-12-26 \| USD 103500 - 196000 / year Machine Learning Engineer II at Scribd, built to design, deploy, and optimize near real-time ML for millions across the Orion platform. Expect heavy exposure to an embedding-based retrieval stack... read more »	Spark, AI/ML, GenAI, Python, Go, Scala, Airflow, Databricks, AWS, Amazon SageMaker, LLM, API, Cloud Computing, AWS Lambda, CloudWatch, Datadog, Terraform, Azure, GCP, Computer Science	Machine Learning Engineer scribd (US) FULL TIME \| JOB LISTED Machine Learning Engineer II at Scribd, built to design, deploy, and optimize near real-time ML for millions across the Orion platform. Expect heavy exposure to an embedding-based retrieval stack (Weaviate), feature store and model registry, and direct product integrations from recommendations to AskAI. The tech radar is broad: Python or Go preferred; Spark, Databricks, Airflow for pipelines; AWS Sagemaker, multi-LLM providers; HTTP/gRPC interfaces; AWS infrastructure (Lambda, ECS, EKS, SQS) with observability via CloudWatch and Datadog; Terraform for infra. You will balance core platform improvements with product-grade features, run A/B tests, and ensure data accuracy. The gap is twofold: a) density of responsibilities across ML infra and product tie-ins; b) Scribd's in-person cadence and regional pay variance. It's a technically hands-on role in a well-financed but crowded ML marketplace. Generated content Technology used Spark AI/ML GenAI Python Go Scala Airflow Databricks AWS Amazon SageMaker LLM API Cloud Computing AWS Lambda CloudWatch Datadog Terraform Azure GCP Computer Science Listed At 2025-12-26 2025-08-19 (original listing) Permalink View original posting
machine learning engineer Manager, Machine Learning Engineering @ adobe US \| 2025-12-24 \| USD 168200 - 340100 / year Adobe's Firefly Foundry Manager for Applied Research asks you to shepherd a distributed team designing and curating large-scale training data for enterprise generative AI, turning research into... read more »	AI/ML, Cloud Computing, API, GenAI, Data Quality, Data Science, ETL/ELT, DWH, AWS, Azure, GCP, Spark, Databricks, Snowflake, MLOps, Data Management	Manager, Machine Learning Engineering adobe (US) FULL TIME \| JOB LISTED Adobe's Firefly Foundry Manager for Applied Research asks you to shepherd a distributed team designing and curating large-scale training data for enterprise generative AI, turning research into production-ready data pipelines while policing quality, bias, privacy, and brand safety. The role prizes deep domain fluency in ML data lifecycles, ETL/ELT at scale, and governance across cloud stacks (AWS, Azure, GCP) with Spark, Databricks, and Snowflake, plus expertise in annotation platforms and tools like DVC. It is heavy on cross-functional leadership and collaboration with researchers, ML engineers, and PMs, and it promises influence over model development via data availability. The salary is competitive, and the scope is enterprise-grade rather than consumer-gen AI hype. The pitfalls: a metrics-driven, potentially bureaucratic environment, high expectations for ethical AI, and risk of misalignment between research ambition and production reality. Generated content Technology used AI/ML Cloud Computing API GenAI Data Quality Data Science ETL/ELT DWH AWS Azure GCP Spark Databricks Snowflake MLOps Data Management Listed At 2025-12-24 2025-09-07 (original listing) Permalink View original posting

Open jobs

Companies looking for Azure

Used together with Azure

Additional Resources

Jobs (this month)

Companies with Jobs

Senior Machine Learning Engineer - (Vendor Data) @ delivery-hero-se

Machine Learning Engineer @ jpmorganchase

BigQuery Cost Optimization Guide by Masthead Data

Lead Machine Learning Engineer @ thoughtworks

Machine Learning Engineer @ scribd

Machine Learning Engineer @ scribd

Manager, Machine Learning Engineering @ adobe