Interested in this AI/ML Engineer role at Wpromote, LLC?
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About This Role
The Role
As an Senior Manager, Paid Social B2B, you will play a key role in developing and executing high\-performing, data\-driven social strategies that support pipeline growth for enterprise and mid\-market B2B clients. You’ll work closely with Directors and cross\-functional partners to translate complex buyer journeys into effective full\-funnel paid social programs.
Reporting into the Associate Director, Social B2B, this role is ideal for a strong B2B social practitioner who blends hands\-on expertise with emerging leadership skills. You’ll contribute to the evolution of our B2B social media approach, help operationalize best practices across LinkedIn, Meta, Reddit, and emerging platforms, and ensure campaigns are optimized toward meaningful business outcomes—not just engagement.
At Wpromote, we believe that great work is only possible with great people. Our goal is to build a better, more inclusive work environment and support our people at every stage of their careers by prioritizing a strong work\-life balance through our policies and benefits listed below. As a Best Place to Work according to both Ad Age and Glassdoor and Adweek’s Fastest Growing Digital Agency, we are moving fast to expand our teams and bring new experts into the fold to keep pushing the boundaries of what’s possible in marketing.
We offer:
- Remote\-first culture
- Unlimited PTO
- Extended Holiday break (Winter)
- Flexible schedules
- Work from anywhere options\*
- 100% paid parental leave
- 401(k) matching
- Medical, Dental, Vision, Life, Pet Insurance
- Sponsored life insurance
- Short Term Disability insurance and additional voluntary insurance
- Annual Class Pass credits and more!
The anticipated annual salary for this role will range from $84,000\- $100,000, based on consideration of a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, education and certifications, competitive benchmarks, scope of responsibility, market dynamics, geographic location, and respective state’s salary threshold for exempt employees. At Wpromote, pay ranges are subject to change and are based on specific market medians for similar jobs according to third\-party salary benchmark surveys. Individual pay within that range can vary due to skills, experience, and available budget. The total compensation package for this role will include benefits (listed above).
- This position may be performed remotely in most states within the US, with some exclusions
\*\*While this role offers the flexibility to work remotely, we have office hubs in Los Angeles, Chicago, and New York, where you can join in on learning and development opportunities, fun events, take advantage of a space to work, and collaborate in person!
\*\*\*This position is not eligible for immigration sponsorship
*Important Notice: Beware of Job Scams*
Wpromote recruiting communications will only be sent through our official channels via wpromote.com email addresses. If you see a posting elsewhere that is not reflected on Wpromote.com/careers, it may be a fraudulent posting. We do not require payment or fees during the hiring process nor do we request sensitive information, such as Social Security numbers or payment details. Please safeguard yourself against possible scams and contact us if you encounter any suspicious activity.
\#LI\-SD
\#LI\-Remote
### You Will Be
- Leading day\-to\-day social strategy development and activation for assigned B2B clients, under the guidance of senior leadership.
- Translating B2B buyer journeys into tactical, data\-informed campaign architectures across awareness, consideration, and conversion stages.
- Executing and optimizing multi\-stage funnel strategies, including content amplification, gated asset promotion, event support, ABM initiatives, and CRM\-based retargeting.
- Partnering with analytics, paid search, and programmatic teams to deliver integrated demand generation programs.
- Supporting measurement and reporting efforts by tying paid social performance to lead and pipeline indicators using tools such as Salesforce, HubSpot, Marketo, or Pardot.
- Assisting with B2B new business efforts, including research, POV development, and pitch support.
- Preparing client\-facing performance recaps and insights, with guidance from Directors, translating results into clear business implications.
- Staying current on platform updates and innovations across LinkedIn, Meta, Reddit, X, and other B2B\-relevant environments, and recommending opportunities to test new features or targeting approaches.
### You Must Have
- 3\-5 years of experience in paid social media advertising, with a strong focus on B2B, SaaS, or lead generation programs.
- Demonstrated experience executing full\-funnel B2B social campaigns that support pipeline and lead quality goals (MQLs, SQLs, efficiency metrics).
- Strong hands\-on expertise in LinkedIn Ads and Meta, with familiarity across additional B2B platforms and targeting strategies (ABM, firmographics, CRM lists).
- Working knowledge of B2B analytics and martech ecosystems (Google Analytics, Salesforce, HubSpot, Demandbase, 6sense, or similar).
- Solid understanding of B2B creative strategy, testing methodologies, and messaging for professional and buying committee audiences.
- Experience using social management, reporting, or automation tools such as Smartly or Google Ads Manager.
- Strong communication skills, with the ability to clearly articulate performance insights to internal teams and clients.
- Bachelor’s degree in Marketing, Business, Analytics, or a related field.
Wpromote is committed to bringing together individuals from different backgrounds and perspectives, providing employees with a safe and welcoming environment free of discrimination and harassment. We strive to create a diverse \& inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together. As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family or parental status, disability\*, age, veteran status, or any other status protected by the laws or regulations in the locations where we operate. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our workplace.
Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Wpromote.
This employer participates in E\-Verify and will provide the federal government with your Form I\-9 information to confirm that you are authorized to work in the U.S. If E\-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E\-Verify once you have accepted a job offer and completed the Form I\-9\. For more information on E Verify, or if you believe that your employer has violated its E\-Verify responsibilities, please contact DHS.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $84K-$100K 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 Wpromote, LLC, 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 ($92K) sits 45% below the category median. Disclosed range: $84K to $100K.
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.
Wpromote, LLC AI Hiring
Wpromote, LLC has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $100K - $104K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
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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