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About This Role
Whether you’re an experienced professional or just getting started, your contributions matter at Fortra. If you’re passionate about tackling meaningful challenges alongside talented team members committed to helping each other succeed, all while having lots of fun, we want to hear from you. We offer competitive benefits and salaries, personal and professional development opportunities, flexibility, and much more!
You will be responsible for supporting and strengthening our pipeline and business growth. Your impact will be on top\-of\-the\-funnel marketing and on lead generation campaigns. You will develop marketing plans and campaigns, including but not limited to: email, paid media, paid social, webinars, podcasts, influencer efforts, and anything else you anticipate will work. As a strategic member of the marketing organization, working closely with Sales and Product Marketing stakeholders, the Sr. Marketing Campaign Lead plays a strategic role on the design, orchestration, and delivery of the lead generation programs, as well as measuring and reporting results and success metrics.\&\#xa;\&\#xa;
WHAT YOU'LL DO
- Develop the demand generation strategy and manage the implementation of go\-to\-market plans necessary to meet the Sales revenue goals in its area of responsibility. Drives joint go\-to\-market plans and co\-marketing initiatives with Partners, aligning campaigns to partner goals and field objectives to accelerate pipeline and revenue growth
- Support Sales by generating new, well\-targeted leads and promoting our brand and products across our vertical markets. Contribute to the development, implementation and optimization of lead nurturing and ABM programs, measuring progress and conversions
- Expands partner sales and marketing capabilities through disciplined joint marketing activities, tailored content, toolkits, updates in the Partners Portal, and regular training to support aligned execution and message consistency
- Develop, execute, and manage comprehensive Marketing Plans for integrated multitouch marketing campaigns, including advertising, webinars, emails, landing pages, content syndication, social media, trade shows, seminars, articles and more…, in close collaboration with the Sales, BDRs, Product, Partners, Customer Advocacy and Marketing teams
- Partner with Product Marketing, Product Experts, Partners, and Sales Teams to produce all campaign\-related materials, such as industry briefs, guides, eBooks, whitepapers, customer stories, web updates, social media, use cases, and more. Develop and re\-purpose relevant marketing content and materials as needed
- Ensure materials are completed on time and campaigns are executed as scheduled, avoiding any delays that would negatively impact on the sales pipeline
- Make sure that all campaign materials, website, online contents, and emails have strong customer\-centric messaging, compelling narratives and effectively communicate the business value and benefits of technical solutions; Intimately understand MFT products and applications, and how each client aligns with them
- Coordinate the demand generation marketing campaigns with BDR and Sales to guarantee proper and swift follow\-through and eliminate the risks of losing potential opportunities. Brief BDR and Sales teams prior to campaigns launches, to ensure alignment and optimization of results
- Actively tracks the results of the deployed marketing activities and seek improvements to implement for future campaigns; Monitor leads and opportunities conversions, and pipeline velocity; ensures leads are rapidly followed up and called back
- Manage budget planning, execution, and ROI tracking, forecasting and reporting, ensuring funds are strategically allocated across marketing campaigns and high\-impact partner\-led demand generation activities
- Continuously learn, to become a market expert within the marketing team regarding the customers, personas, industries, events, professional associations, and local media related to the designated scope
- Stay ahead of global industry trends and best practices related to demand generation and multi\-channel marketing
- Perform all other duties and tasks as assigned by supervisor or manager
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QUALIFICATIONS
- Bachelor’s degree in business or technology. Master’s degree a plus
- 5\+ years previous experience in Field Marketing / Demand Generation for B2B technology products/solutions
- 3\+ years’ recent experience working in B2B Marketing for a mid\-sized to large global technology company is a very significant plus
- Marketing experience executing B2B marketing activities for product launches and/or lead generation
- Previous B2B customer\-facing experience as Sales or Presales is a plus
- Strong customer focus and business acumen; has a passion for business value
- Hands\-on, adaptable and agile
- Strong cross\-functional collaborator
- Relationship\-building and negotiation
- Driven and resilient
- Organized, analytical skills
- Good project management abilities, can prioritize multiple projects
- Familiar with CRM (D365, SFDC) and MarTech (6Sense, Hubspot, Pardot, Marketo…)
- Good knowledge in Microsoft Office Suite (Word, PowerPoint, Excel)
Compensation: 75,000 USD to 90,000 USD
At Fortra, we’re breaking the attack chain. Ready to join us?
At Fortra, our compensation philosophy prioritizes fair market value and internal equity, aligning with your experience and specialized skill set.
As a full\-time, exempt employee at Fortra, you’ll enjoy a comprehensive benefits package that includes:
- Health, dental, and vision coverage as of hire
- Immediate enrollment in 401(k), HSA, and FSA plans
- Flexible PTO policy
- Tuition and personal enrichment reimbursement
- Option to enroll in ID Theft Protection Program
*At Fortra, work is only part of the story. Explore what Life at Fortra is all about, from perks that support holistic wellbeing to a culture that keeps you connected and empowered to make an impact beyond the job.*
Visit our website to learn more about why employees choose to work for Fortra. Remember to connect with us on LinkedIn.
As an EEO/Affirmative Action Employer, all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, veteran or disability status.
Salary Context
This $75K-$90K range is below 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 Fortra, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($82K) sits 51% below the category median. Disclosed range: $75K to $90K.
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.
Fortra AI Hiring
Fortra has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in US. Compensation range: $90K - $90K.
Location Context
AI roles in Austin pay a median of $212,800 across 317 tracked positions. That's 16% above the national 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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