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About This Role
Who is Nexxen?
Flexible advertising, unified by data. Nexxen empowers advertisers, agencies, publishers and broadcasters around the world to utilize data and advanced TV in the ways that are most meaningful to them. Our flexible and unified technology stack comprises a demand\-side platform (“DSP”) and supply\-side platform (“SSP”), with the Nexxen Data Platform at its core.
Why join the Nexxen team?
With a global footprint, you can be part of a team that is transforming advertising through our creative, flexible and unified solutions. Employees hustle, commit and dedicate themselves to pillars that make up the Nexxen Way – the 3Cs \- Customer Centric, Curious Mindset, Collaborative with No Ego.
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You'll drive Nexxen SSP, our exchange that connects publishers and media buyers. You’ll be working cross\-functionally with various teams to help drive demand facilitation for our premium publishers. This role is also a leadership role and you will help shape the direction of the team as well as mentor junior members of the team. This role is crucial to the success of this fast\-growing piece of our business.
This role will be based in the New York office. Our team follows a hybrid schedule working in\-office three days a week and remotely for the rest.
Each day can be different here at Nexxen, but some of the things you can expect to be doing daily are:
What you’ll do:
- Strategic Sales Leadership: Provide strategic direction and leadership in developing and executing high\-impact sales strategies targeted towards DSPs, aligning closely with the SSP's overarching business objectives.
- Strategic Partner Identification: Spearhead the identification and prioritization of potential DSP partners, leveraging deep industry insights and market analysis to focus efforts on high\-value opportunities.
- Executive\-Level Relationship Management: Cultivate and nurture executive\-level relationships with key stakeholders at DSPs, fostering long\-term partnerships built on trust, collaboration, and mutual benefit.
- Complex Negotiations and Deal Structuring: Lead complex negotiations and deal structuring processes with DSP partners, ensuring favorable terms and conditions that maximize value for both parties while mitigating risks.
- Strategic Product Alignment: Collaborate closely with product management and development teams to align product roadmap and feature enhancements with the evolving needs and priorities of DSP partners.
- Cross\-Functional Collaboration and Influence: Engage cross\-functional teams including product, engineering, marketing, and operations to drive alignment and ensure seamless execution of partnership initiatives and deliverables.
- Market Intelligence and Competitive Analysis: Maintain a deep understanding of market dynamics, competitive landscape, and emerging trends within the DSP ecosystem, leveraging insights to inform strategic decision\-making and identify new opportunities for growth.
- Performance Measurement and Optimization: Establish key performance indicators (KPIs) and metrics to track the effectiveness of sales initiatives, continuously optimizing strategies and tactics to drive revenue growth and maximize ROI.
- Strategic Revenue Growth Initiatives: Lead the ideation and execution of strategic initiatives aimed at driving revenue growth, including upselling, cross\-selling, and introducing new revenue streams within existing DSP partnerships.
- Compliance and Risk Management: Ensure compliance with industry regulations, legal requirements, and company policies across all aspects of partnership activities, proactively addressing potential risks and mitigating liabilities.
- Executive Reporting and Communication: Deliver concise and insightful executive\-level reports and presentations to senior leadership, providing visibility into sales performance, partnership status, market trends, and strategic opportunities.
- Thoughtful Talent Development and Mentorship: Provide mentorship and guidance to junior team members, fostering a culture of continuous learning and professional growth within the sales organization.
- High\-Impact Industry Engagement: Represent the SSP at industry conferences, forums, and events, leveraging networking opportunities to forge new partnerships, strengthen existing relationships, and elevate the SSP's brand presence.
- Strategic Planning and Innovation: Drive strategic planning initiatives and innovation projects aimed at enhancing the SSP's competitive positioning and driving long\-term value creation within the digital advertising ecosystem.
What You'll Bring:
- Bachelor's degree
- 5\+ years of experience in digital sales or business development experience
- Programmatic/ Buy\-side experience, especially with SSP and/ or DSP platforms
- Knowledge of CTV and In\-Mobile Applications
- Proven track record of successful sales and revenue growth
- Adaptable and eager to learn new products and technology, and communicate capabilities to clients
- Energetic with a high level of initiative and motivation
- You enjoy working independently and collaboratively in a team environment
- You're a go\-getter, new products and problem\-solving excite you
- Excellent communication skills in writing and verbal
- Strong list of contacts within the programmatic ecosystem
- Willingness to travel (\< 20% of the time)
In support of pay transparency and equity, the minimum and maximum full\-time annual base salary for this role is $80,000 \- $135,000 at the time of posting. While this is our reasonable expectation this is not a guarantee of compensation or salary, actual compensation is influenced by a wide range of factors including but not limited to skill set, level of experience, education, certifications, responsibility, and geographic location. Candidates hired to work in other locations will be subject to the pay range associated with that location. We offer a variety of benefits, including medical, dental, vision, disability insurance, 401(k), EAP, parental leave, unlimited vacation, and company\-paid holidays. The specific programs and options available will vary depending on the state, start date, and employment type. Our Talent Acquisition team will be happy to answer any questions you may have.
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Salary Context
This $80K-$135K 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 Nexxen, 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 ($107K) sits 36% below the category median. Disclosed range: $80K to $135K.
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.
Nexxen AI Hiring
Nexxen has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $135K - $260K.
Location Context
AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% 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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