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职位Honeywell

Software Engineer II - AI/ML OPS Engineer

Honeywell

Software Engineer II - AI/ML OPS Engineer

Honeywell

Atlanta, GA, United States, US

·

On-site

·

Full-time

·

1mo ago

必备技能

Python

Docker

Kubernetes

GCP

Azure

Machine Learning

We are seeking a talented Software Engineer II- AI/ML OPS Engineer to contribute to our machine learning operations (ML Ops), large language model (LLM) and agentic AI integration, Databricks administration, data lake management, and cloud platform projects.

The ideal candidate will help design, implement, and optimize ML pipelines, support cloud infrastructure (GCP & Azure), participate in prompt engineering for generative and agentic AI, contribute to CI/CD practices, and assist with Databricks platform governance and data lake operations.

You will work closely with engineers, data scientists, and product managers to deliver innovative AI solutions.

You will report directly to our Sr.

Software Engineer Manager, and you’ll work out of our Atlanta, GA location on a Hybrid work schedule.

Hybrid Work Schedule Note: For the first 90 days, New Hires must be prepared to work 100% onsite M-F
YOU MUST HAVEBachelor’s degree in Computer Science, Engineering, or related field. 3 years of software engineering experience, with 2 years in ML Ops, agentic AI, Databricks, data lake, or cloud platforms.

Experience: with ML Ops tools (MLflow, Kubeflow, Vertex AI, Azure ML, etc.).

Exposure to LLMs (OpenAI, Google Gemini, Azure OpenAI, etc.), agentic AI systems, and prompt engineering.

Familiarity with Databricks platform administration, deployment, and troubleshooting.

Experience: with data lake solutions (Azure Data Lake, GCP Big Lake, etc.).

Proficiency in Python; experience with other languages is a plus.

Working knowledge of GCP and Azure cloud services.

Experience: with CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins, etc.).

Understanding of containerization (Docker, Kubernetes).

Experience: with data engineering, ETL, or big data technologies.

Good communication and problem-solving skills. WE VALUEExperience with working as DEVOPS/SRE or ML OPS Familiarity with MLOps for LLMs, agentic AI, or generative AI.

Contributions to open-source projects.

Certifications in GCP, Azure, Databricks, Data Lake, or ML Ops. US Person requirement:Due to compliance with U.S. export control laws and regulations, candidate must be a U.S.

Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.BENEFITS OF WORKING FOR HONEYWELLIn addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package.

This package includes employer-subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays.

For more information visit: click here (https://benefits.honeywell.com/)The
application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.

Job Posting date: March 2,2026.ABOUT HONEYWELLHoneywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world's most critical challenges around energy, safety, security, air travel, productivity, and global urbanization.

We are a leading software-industrial company committed to introducing state-of-the-art technology solutions to improve efficiency, productivity, sustainability, and safety in high-growth businesses in broad-based, attractive industrial end markets.

Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe.

Learn more about Honeywell: click here (https://www.honeywell.com/us/en)THE
BUSINESS UNITThe Corporate Strategic Business Group (CORP SBG) at Honeywell is a division focused on corporate-level functions and initiatives that support the overall operations and strategy of the company.

It is responsible for overseeing areas such as finance, legal, human resources, communications, and corporate governance, working closely with other business units and SBGs to ensure alignment and coordination across the organization.

The CORP SBG plays a crucial role in the overall strategic direction and management of Honeywell's corporate functions and operations, supporting the company's business objectives.
KEY RESPONSIBILITIESDesign and deploy API in Azure and GCP using multiple programming language Manage production system and data pipeline in prod environment On call support for any production issue for troubleshooting Work with data engineering, API development team to deploy release on time Automate things to improve developer experience Manage deployment in Azure and GCP cloud Partner with security team to remediate security issues in infrastructure.

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关于Honeywell

Honeywell

Honeywell

Public

Honeywell International Inc. is an American publicly traded, multinational conglomerate corporation headquartered in Charlotte, North Carolina. It primarily operates in four areas of business: aerospace, building automation, industrial automation, and energy and sustainability solutions (ESS).

10,001+

员工数

Charlotte

总部位置

$130B

企业估值

评价

2.3

2条评价

工作生活平衡

2.5

薪酬

3.5

企业文化

2.0

职业发展

2.0

管理层

1.5

15%

推荐给朋友

优点

Good compensation potential

Competitive pay scale

缺点

Poor communication from recruiters

Inadequate safety training

Poor management response to incidents

薪资范围

901个数据点

Mid/L4

Senior/L5

Mid/L4 · Data Analyst II

2份报告

$136,600

年薪总额

基本工资

$105,077

股票

-

奖金

-

$136,600

$136,600

面试经验

3次面试

难度

3.0

/ 5

时长

14-28周

录用率

33%

体验

正面 0%

中性 33%

负面 67%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Interview

4

Assessment/Testing

5

Final Interview

6

Offer

常见问题

Technical Knowledge

Behavioral/STAR

Past Experience

Problem Solving

Culture Fit