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About This Role
About Us
Always open. Our code, our culture, our opportunities. Leading open innovation without limits. We are SUSE.
SUSE is a global leader in innovative, reliable, and secure enterprise open source solutions, including SUSE® Linux Suite , SUSE® Rancher Suite , SUSE® Edge Suite , and SUSE® AI Suite . More than 60% of the Fortune 500 rely on SUSE to power their mission\-critical workloads, enabling them to innovate everywhere – from the data center to the cloud, to the edge and beyond.
SUSE puts the “open” back in open source, collaborating with partners and communities to give customers the agility to tackle innovation challenges today and the freedom to evolve their strategy and solutions tomorrow. For more information, visit www.suse.com .
AI Partner Marketing
Job Description
Always open. Our code, our culture, our opportunities. Leading open innovation without limits. We are SUSE. SUSE is a global leader in innovative, reliable, and secure enterprise open source solutions, including SUSE® Linux Suite, SUSE® Rancher Suite, SUSE® Edge Suite, and SUSE® AI Suite. More than 60% of the Fortune 500 rely on SUSE to power their mission\-critical workloads, enabling them to innovate everywhere – from the data center to the cloud, to the edge and beyond. SUSE puts the “open” back in open source, collaborating with partners and communities to give customers the agility to tackle innovation challenges today and the freedom to evolve their strategy and solutions tomorrow. For more information, visit www.suse.com .
The Role:
Reporting to the Director of Communities and Ecosystem (Robert Sirchia), you are the primary commercial architect for SUSE’s most strategic AI relationships (NVIDIA, Intel, AMD). This is a Level 05 Leadership role designed to close the gap between engineering enablement and revenue execution. You will lead the creation of the SUSE AI Factory narrative, developing technical GTM solutions that move at the speed of the AI market. You aren't just marketing a partnership; you are architecting the Sovereign AI Foundation that our partners build upon.
Focus Areas:
- Technical Alliance Architecture: Bridging the gap between Partner Engineering and Growth Marketing to ensure "Day 0" support for stacks like NVIDIA Jetpack 6 or Intel Gaudi 3 is commercially ready.
- Vertical AI Blueprints: Identifying and productizing top use cases (Healthcare Imaging, AI\-RAN, and Industrial Robotics) into validated "Blueprints" for OEM and GSI partners.
- Developer On\-Ramp: Architecting the GTM strategy for our AI Developer Bundles (AppCO/SLES Desktop/NVIDIA SDK) to win mindshare at the workstation level.
Accountabilities (Aligned to SUSE Level 05\):
- Partner GTM Strategy (Strategic Thinking \- Advanced): Define and execute the "Better Together" narrative. You must anticipate 18\-month hardware roadmaps and align SUSE’s software release cycles to maximize market impact.
- Content \& Narrative Authority (Executing \- Expert): Author high\-fidelity technical content—Reference Architectures (ERAs) and POV papers—that establishes SUSE as the definitive "Horizontal Open" partner.
- Sales \& Partner Enablement (Influencing w/ Empathy \- Advanced): Develop specialized training for global teams. You must build consensus across matrixed organizations to move sales from "selling Linux" to "selling AI Infrastructure ROI."
- Global Event Strategy (Analytical Reasoning \- Proficient): Lead SUSE’s technical presence at key AI shows (NVIDIA GTC, Embedded World), using data\-driven insights to transform booths into high\-conversion "Experience Centers."
- Team Leadership (Leading \& Developing \- Proficient): Assemble and lead a specialized team (or cross\-functional task force). You are responsible for coaching and building a pipeline of "Technical Marketers" who understand the AI substrate.
Preferred Experience and Skills:
- 12\+ Years in Tech Marketing/Alliances: Proven experience at a high\-growth AI or Semiconductor company (NVIDIA, AWS, Intel).
- Deep Technical Fluency: Ability to discuss CUDA cores, Kubernetes orchestration, and Model Context Protocols (MCP) with the same ease as P\&L targets.
- Global Perspective: Experience managing complex partner motions across North America, EMEA, and APJ.
- Storytelling \& Executive Presence: A superior ability to simplify complex technical "plumbing" into a compelling value proposition for C\-level executives.
Core Competencies (SUSE Level 05 Requirements):
- Learnability (Advanced): Proactively maintains "Day 0" knowledge of emerging AI standards (like NemoClaw or Project Sidecar) to keep SUSE's marketing ahead of the curve.
- Adaptable Resilience (Advanced): Thrives in "AI\-speed" environments where partner roadmaps shift rapidly; maintains strategic focus for the team during pivots.
- Self\-Awareness (Advanced): Models SUSE values while navigating high\-pressure partner negotiations; seeks feedback to refine executive influence.
Measures (2026 Standards):
- Pipeline Velocity (AI Specific): Growth in qualified pipeline for AI\-related workloads (Jetson, NVAIE).
- Partner\-Sourced Revenue: Percentage of AI revenue influenced or sourced through strategic technical alliances.
- Technical Brand Authority: Share of Voice within the NVIDIA/Intel/AMD developer communities.
- Blueprint Adoption: Number of OEM and GSI partners successfully deploying SUSE "AI Factory" validated blueprints.
What We Offer
\*\*We empower you to be bold, driving your career to create the future you want. We celebrate and reward your achievements. SUSE is a dynamic environment that is evolving rapidly, thus requiring agility, strong entrepreneurship and an open mind. This is a compelling opportunity for the right person to join us as we continue to scale and prosper. \*\*
If this role is filled in the United States of America, the starting base salary is expected to be between $270 and $280k . In addition to this base salary, we offer a corporate bonus plan, paid quarterly and an attractive benefits package. US benefits include a comprehensive medical plan, life and disability insurance, 401k, Employee Assistance Programme and generous paid time off and leave policies.
If you’re a big thinker, obsessed with execution and thrive in a dynamic environment in which you can tangibly create a lasting legacy, ! We give you the freedom to be yourself. You will work in a global community of unique individuals – like you – with different backgrounds, talents, skills and perspectives. A truly open community where everyone is welcome, has a voice and is encouraged to reach their full potential regardless of age, gender, race, nationality, disability, sexual orientation, religion, or any other characteristics. Sounds like the right fit for you? . A recruiter will contact you if your skills match our current or any future positions. In the meantime, stay updated on the latest SUSE news and job vacancies by joining our Talent Community.
This position is subject to a background check(s), including criminal, credit, and/or employment references. The candidate is required to complete the background check(s) once an offer has been accepted. This will be conducted by SUSE’s external provider, where legally permitted.
For US Only \- US Pay Transparency Disclaimer
If this role is filled in the United States of America, the starting base salary will be within the applicable pay range displayed below. In addition to base salary, this position may be eligible for a commission plan and a competitive benefits package. US benefits include comprehensive medical coverage, life and disability insurance, a 401(k) plan, an Employee Assistance Program, and generous paid time off and leave policies.
Final compensation will be determined based on factors such as experience, skills, geographic location, internal equity, and budget. This pay transparency information applies to US\-based roles only.
Base Pay Range Min \& Max
Job
Marketing
What We Offer
We empower you to be bold, driving your career to create the future you want. We celebrate and reward your achievements.
SUSE is a dynamic environment that is evolving rapidly, thus requiring agility, strong entrepreneurship and an open mind.
This is a compelling opportunity for the right person to join us as we continue to scale and prosper.
If you’re a big thinker, obsessed by execution and thrive in a dynamic environment in which you can tangibly create a lasting legacy, !
We give you the freedom to be yourself. You will work in a global community of unique individuals – like you – with different backgrounds, talents, skills and perspectives. A truly open community where everyone is welcome, has a voice and is encouraged to reach their full potential regardless of age, gender, race, nationality, disability, sexual orientation, religion, or any other characteristics.
Sounds like the right fit for you? . A recruiter will contact you if your skills match our current or any future positions. In the meantime, stay updated on the latest SUSE news and job vacancies by joining our Talent Community .
SUSE Values
- Choice
- Innovation
- Trust
- Community
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At SUSE Software Solutions Germany GmbH, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
SUSE Software Solutions Germany GmbH AI Hiring
SUSE Software Solutions Germany GmbH has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in CA, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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