Interested in this AI/ML Engineer role at NODUS?
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About This Role
Company Overview:
Nodus is an emerging technology and paid marketing agency boutique that specializes in data\-driven solutions for digital brands. We deliver a best\-in\-class marketing solution, through both our in\-house built technology and expert media buying team. Our solutions combine deep data integrations and data science to streamline information accessibility and speed\-to\-insight for a breadth of paid marketing tactics.
We’re a young company, quickly growing, on the grind to disrupt the digital marketing space with a unique SaaS technology and deeply\-integrated services for our clients. Founded with the goal of embracing and attacking the challenges of the evolving digital landscape, the Nodus culture is built around growth (personal \& professional) for everyone on our team; we strive for excellence, expertise, and excitement in the work we do. We provide significant flexibility in our work environment, but have an emphasis on high work ethic, ownership, and intellectual horsepower. We are looking for those that share in our entrepreneurial spirit.
As we continue our rapid growth, we are seeking a talented Marketing Associate with expertise in media execution, data and analysis, and strategic account management to join our team.
Position Overview:
As a Paid Marketing Associate at Nodus, you will be responsible for driving online advertising strategy and execution for key marketing clients. You’ll leverage your existing expertise, combined with our Nodus framework, to maximize ROI, optimize campaign performance, drive impactful testing, and effectively report to key client stakeholders. By utilizing and honing your knowledge across paid media platforms and advanced digital marketing analytics, you will play a crucial role in shaping our digital advertising efforts while simultaneously driving growth for the business. You’ll also be expected to strategically and autonomously communicate with clients to uphold Nodus’ expertise and push forward strategic initiatives.
You’ll also play a key role in product development by sharing marketing and execution best\-practices to inform our tech \& product division. Working with talented developers and fellow marketing enthusiasts, you’ll help spark ideas and provide feedback for the cutting\-edge solutions our tech teams are building for both internal use \& enterprise\-level scale.
Responsibilities:
Campaign Management:
- Manage campaigns across either paid social, display, or search accounts.
- Develop and execute campaigns end\-to\-end, including keyword research, ad trafficking, bidding strategies, targeting, and budget allocation.
- Monitor campaign performance, track key metrics, and analyze data to identify areas for improvement and optimization.
- Conduct empirically\-driven tests and implement data\-driven optimizations to improve ad performance and overall campaign effectiveness.
- Stay informed on platform updates, features, and best practices to leverage the latest advertising opportunities.
- Optimize ad placements, bid strategies, audience targeting, and other levers against key business goals.
- Conduct thorough keyword analysis and research to ensure ads target relevant and high\-intent keywords for maximum campaign performance.
Data Analysis and Reporting:
- Analyze campaign data and generate reports to measure the effectiveness of each dollar spent, providing insights and recommendations to stakeholders.
- Use analytics tools (e.g. Google Analytics, Google Data Studio, Tableau, Looker) to visualize and analyze data, identifying trends, patterns, and opportunities.
- Leverage SQL querying language to access, validate and transform marketing data.
- Collaborate with the marketing team to align campaign goals with overall marketing objectives and business targets.
- Regularly present campaign performance reports to stakeholders, highlighting key findings and recommending strategic adjustments.
- Stay informed about industry trends, competitive landscape, and changes in the digital advertising space.
Conversion Tracking \& Measurement:
- Manage the inner workings of digital tracking \& analytics. From browser pixels to server\-side eventing, you’ll be supported by our technical team, and expected to maintain a deep understanding of how we measure user\-behavior across the internet.
- Monitor and maintain conversion tracking mechanisms to measure campaign success and attribute conversions accurately.
Qualifications:
- Minimum of 1 year of proven experience as a Paid Marketing Analyst, Digital Advertising Specialist, or similar role, with a focus on managing social, search, and/or display campaigns.
- Bachelor's degree in Marketing, Advertising, Business Administration, Analytics, or a related field is a plus.
- Proficiency in digital marketing analytics tools, including Google Analytics or Segment.
- Demonstrated experience in data analysis, interpreting campaign metrics, and generating actionable insights.
- Strong knowledge of conversion tracking, landing page optimization, and A/B testing.
- Excellent organizational and project management skills, with the ability to manage multiple campaigns simultaneously.
- Strong communication and presentation skills, with the ability to convey complex data in a clear and concise manner.
- Familiarity with a wide variety of digital advertising platforms (e.g. Google Ads, Facebook Ads, Snapchat Ads, TikTok Ads, DV360, etc.) is a plus.
Job Type: Full\-time
Pay: $75,000\.00 \- $85,000\.00 per year
Benefits:
- Dental insurance
- Health insurance
- Paid time off
- Vision insurance
Application Question(s):
- Will you now, or in the future, require sponsorship (i.e. H\-1B visa, etc.) to legally work in the U.S.? (Yes/No)
- What is your level of proficiency with Excel / Google Sheets? Are you familiar with Relative Cell References and Pivot Tables? Please describe your experience.
- How have you used data to drive a decision a marketing decision?
Experience:
- Google Ads: 1 year (Preferred)
- Facebook Advertising: 1 year (Preferred)
Work Location: Remote
Salary Context
This $75K-$85K 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 NODUS, 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. Entry-level AI roles across all categories have a median of $76,880. This role's midpoint ($80K) sits 52% below the category median. Disclosed range: $75K to $85K.
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.
NODUS AI Hiring
NODUS has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $85K - $85K.
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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