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About This Role
DESCRIPTION
We are looking for a talented Digital Marketing Campaign Leader to join our team specializing in Communications for Cummins Inc. in Indianapolis, IN.
In this role, you will make an impact in the following ways:
- Lead the development and execution of integrated marketing communication plans that align stakeholders and drive cohesive brand messaging.
- Deliver effective multi\-channel campaigns by optimizing digital, social, email, and traditional marketing strategies for maximum reach and engagement.
- Produce compelling, audience\-focused content that strengthens the brand and clearly communicates value propositions.
- Leverage industry insights and competitive intelligence to shape proactive marketing strategies and uncover new growth opportunities.
- Strengthen cross\-functional alignment by partnering closely with sales, product, and creative teams to ensure seamless execution of initiatives.
- Build and guide a high\-performing marketing team through mentorship, clear direction, and ongoing development.
- Cultivate strong relationships with leaders, stakeholders, and suppliers to support collaboration and accelerate project success.
- Safeguard and elevate Cummins’ brand identity across all marketing materials and customer touchpoints.
RESPONSIBILITIES
To be successful in this role you will need the following:
- Strong brand management expertise to ensure consistent application of brand standards, protect reputation, and build competitive advantage through recognizable, trusted positioning.
- Advanced digital media capabilities , leveraging automation tools, social platforms, and content management systems to influence audience behavior and drive measurable engagement.
- Proficiency in data analytics , including interpreting qualitative and quantitative data, applying statistical and visualization techniques, and translating insights into actionable recommendations.
- Ability to articulate compelling value propositions that translate customer needs into clear, differentiated messaging that highlights product and service strengths.
- Deep channel awareness to understand market dynamics, pathways to customers, and industry structure, enabling smarter strategy and execution.
- Strong marketing plan management skills, using the 4 Ps to build effective marketing strategies and guiding cross\-functional teams to execute plans and assess business performance.
QUALIFICATIONS
Education/Experience
Education, Licenses, Certifications:
College, university, or equivalent degree in marketing or a related subject required.
Experience:
- Product marketing experience preferred.
- Talent Management experience and experience managing distributed teams highly preferred.
- Digital marketing experience preferred.
- Global perspective and experience preferred.
- B2B experience preferred.
- Strong project management skills and the ability to meet deadlines.
- Creative thinker with a strong attention to detail.
- Strong analytical skills and proficiency in using marketing analytics tools.
- Ability to work collaboratively in a team environment.
- Strategic thinker with the ability to develop and implement successful marketing campaigns.
Additional Responsibilities:
The top priority of this role is to set the strategy and process for the Digital Marketing Campaign Management team that enables close collaboration with Marketing Communications teams to drive integrated, multi\-channel digital marketing campaigns, analyze performance data, and contribute to Cummins growth and success. The role must establish an organizational structure that successfully designs and implements digital marketing communications strategies that align with Cummins business goals while driving awareness, engagement and conversion. The organization will view this role as the voice of industry expertise and best practices, who not only establishes industry leading digital marketing campaign frameworks and playbooks but also ensures that campaigns are scalable, repeatable and measurable. Finally, this role must enable collaboration across businesses and stakeholders, must set prioritization to the work and effectively partner to deliver efficient, professional, and best\-in\-class marketing practices.
Key Responsibilities:
- Lead the Digital Marketing Campaign Management Team
- Builds team dynamics that value innovation of ideas and approach and fosters coordination and alignment with stakeholders.
- Leads the Digital Marketing Campaign Management Team, providing guidance, mentorship, and support to ensure team and individual success.
- Sets team goals and personal development expectations, gathers stakeholder feedback and engages the team in ongoing performance improvement with a focus on deepening the team’s digital marketing skillset.
- Own and optimize the campaign management process
- Leads and manages digital marketing initiatives, develops and executes digital marketing strategies, oversees the planning, execution, and optimization of digital marketing campaigns, including web, paid advertising, and email marketing.
- Oversees the creation of engaging and relevant messaging and content, ensuring it aligns with brand identity, resonates with target audiences, optimizes against target campaign goals, and aligns with stakeholders.
- Establish marketing campaign frameworks and playbooks to ensure campaigns are scalable, repeatable, and measurable
- Manages critical supplier relationships that facilitate the work globally to deliver the best results at the lowest costs.at the lowest costs.
- Implement market\-leading best practices
- Stays updated on industry trends, competitor activities, and customer preferences to inform marketing strategies and identify new opportunities.
- Collaborates with cross\-functional teams, including sales, product development, and creative, to ensure alignment and successful execution of marketing initiatives.
- Serves a key role in influencing the creation and execution of integrated marketing communication plans and assets, working across stakeholders and subject matter experts.
- Leverage data reporting to optimize performance and measure impact
- Monitors and analyzes campaign performance metrics, providing insights and recommendations for improvement. Regularly reports on marketing KPIs.
- Develops reporting requirements and best practices that enables end to end reporting for teams to measure marketing value in the lead and sales process.
- Develops and manages budget, financial controls, and risk ensuring operations are executed efficiently and within established budgets.
- Understands and champions digital marketing tools, trends, and channels.
Experience:
- 10 years of experience leading digital or integrated marketing campaigns for a global or complex matrix organization
- 5 years of experience managing and leading hybrid teams
- Experience with marketing automation and CRM platforms such as Salesforce Marketing Cloud or equivalent digital marketing experience required
- Ability to work collaboratively in a team environment.
- Experience managing agency relationships
- Strategic thinker with the ability to develop and implement successful marketing campaigns across complex business organizations.
- Strong project management skills and the ability to meet deadlines.
- Creative thinker with a strong attention to detail.
- Strong analytical skills and proficiency in using marketing analytics tools (Datorama, PowerBI).
- B2B experience preferred.
- Global experience preferred.
Job Communications
Organization Cummins Inc.
Role Category On\-site with Flexibility
Job Type Exempt \- Experienced
Min Salary $120000
Max Salary $180000
ReqID 2426176
Relocation Package Yes
100% On\-Site No
Cummins and E\-Verify
At Cummins, we are an equal opportunity and affirmative action employer dedicated to diversity in the workplace. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, gender, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity and/or expression, or other status protected by law. Cummins validates the right to work using E\-Verify and will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee’s Form I\-9 to confirm work authorization. Visit http://EEOC.gov to know your rights on workplace discrimination.
Salary Context
This $120K-$180K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Cummins, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($150K) sits 10% below the category median. Disclosed range: $120K to $180K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Cummins AI Hiring
Cummins has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Whitakers, NC, US, Indianapolis, IN, US. Compensation range: $140K - $180K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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