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About This Role
Job Description
Hello, Blue Hour
Blue Hour Studios is a social\-first content agency formed in 2019 and is an affiliate of Horizon Media. Blue Hour builds community and fandom by playing at the intersection of creators, culture, content, and commerce. The company is headquartered in New York and Los Angeles.
At Horizon and Blue Hour Studios, we understand the value that different perspectives can bring to our clients and culture, so we strive for an environment where our employees feel welcomed, safe and empowered. We value you and believe that your authentic voice and unique perspective allows us to create a more rewarding culture, and experience, together. We hire talented people, challenge them, and give them every opportunity to grow.
What You’ll Do
65% \- Campaign Management
10% \- Strategic Planning \& Thought Leadership
10% \- Creative Strategy \& New Business
15% \- Insights \& Marketing
Job Summary
The Creative \& Creator team is responsible for the output of content we create for our brand partners. Combining creator/influencer practices and creative practices allows us to imprint community\-driven creativity into every post, partnership, campaign or video we create.
The role of the Campaign Manager, Influencer within Blue Hour Studios is to lead influencer and creator marketing projects and deliverables. This person will work to deliver exceptional and inspired content across Blue Hour Studios clients’ influencer programs using their rich account and influencer strategy experience to translate key business objectives into clear and concise deliverables.
This position reports to the XX and will lead and support all social media and influencer/creator programs, working closely with the team to develop proposals and content in collaboration with creators, contract creators, execute campaigns, manage team administration, and analyze campaign results. The ideal candidate is passionate about the social ecosphere, actively participates within it, and understands the social/digital media landscape.
Main Duties and Responsibilities
65% Campaign Management:
- Lead in the development, execution and production of annual and seasonal influencer campaigns with internal and external business partners, including but not limited to:
- Influencer identification and outreach
- Support the development of campaign briefs for clients and influencers
- Presentation of influencer lists for client ranking and approval
- Analytics and reporting for campaigns
- Managing day to day client and team communication around campaign progress, updates, and key milestone deliverables, as it pertains to key accounts and clients
- Develop and customization of influencer agreements, contracts, addendum, and scopes of work, working closely with Horizon Media’s Legal and Business Affairs Team
- Working closely with the team in the development of post\-campaign reporting
- Utilize knowledge and understanding of influencer industry to help inform brainstorms, strategy development, and execution
Partner closely with cross\-functional agency teams to optimize social media presence/social influencer integration across channels
*
10% \- Strategic Planning \& Thought Leadership
- Translate client goals into strategic, innovative creative and media solutions
- Provide strategic counsel to clients and prospects
- Develop and deliver effective and persuasive points of view
- Understand our client’s business, competitive set and generate new ideas and see opportunities for growth
- Ensures best practices are applied across disciplines
- Oversee the development and maintenance of timelines, deadlines, processes and integration points for all digital projects
- Lead teams to produce all campaign components seamlessly
- Proactively manage client and internal team expectations
- Ensure Influencer team is providing innovative solutions to feed into clients’ goals, evaluating health of client business via analysis of relevant business metrics
- Bring powerful thought leadership to consult on complex issues and identifies innovative solutions
- Tap into Blue Hour resources/tools and collaborate with partner agencies to offer clients holistic business solutions
10% Creative Strategy \& New Business:
- Research \& develop insights around social media platforms, influencers, competitive brands, and trends to assist in the development of new business proposals
o Lead in the development of new business proposals including but not limited to:
- Proposal development inclusive of PowerPoint building, writing, and organizing relevant materials
- Development of influencer strategies and tactical plans to support client goals
- Utilizing tools and working with cross\-functional agency teams to develop insights that shape our recommendations
- Vetting influencers, vendors, and technologies with an eye to operational and cost efficiencies
o Manage communication with teams and clients as it pertains to new business proposals, leads, and consultations
o Assist in the development of any materials for agency pitches as it pertains to influencer marketing
o Participate in internal brand and client meetings, build and foster open communication with internal teams, serving as a key team contact
10% Insights \& Marketing:
- Thought leadership in identifying social media influencer platforms, partners, and technologies, constantly looking for operational and cost efficiencies
- Continuously assess the competitive social media landscape and constantly innovate to differentiate Blue Hour Studios’ practice
- Lead key projects related to marketing Blue Hour’s influencer/creator practice ( i.e. development of thought leadership, events, marketing materials, conference attendance, etc.)
Attend industry events to share insights with Blue Hour
*
Supervisory Responsibilities
The Campaign Manager may manage junior members of the Influencer Team
Preferred Skills \& Experience
- Minimum 2\+ years of influencer marketing experience required
- Maintains strategic relationships with digital influencers, talent management, and other key stakeholders within the influencer industry
- Has a proven track record of managing successful social/digital campaigns across social platforms (TikTok, Facebook, Twitter, Instagram, YouTube, etc )
- Experience with digital reporting, data, and analytics
- Ability to thrive in a fast\-paced environment and handle multiple projects
- Must have strong verbal and written communication skills
- Very proficient with Microsoft Office (Word, Powerpoint , and Excel) and presentation formats like Google Slides
- BA/BS required (Communications, Advertising, Marketing or related field)
The statements herein are intended to describe the general nature and level of work being performed by employees, and are not to be construed as an exhaustive list of responsibilities, duties and skills required of personnel so classified. Furthermore, they do not establish a contract for employment and are subject to change at the discretion of the employer.
*Horizon Media is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.*
Salary Range
$66,300\.00 \- $100,000\.00
\#BHS
\#LI\-TV1
\#LI\-HYBRID
*A successful applicant’s actual base salary may vary based on factors such as individual’s skill sets, experience, training, education,* *licensure/certifications,* *and qualifications for the role.* *As an organization, we take an aptitude and competency\-based hiring approach.* *We provide a competitive total rewards package including a discretionary bonus and a variety of benefits including health insurance coverage, life and disability insurance, retirement savings plans, company paid holidays and unlimited paid time off (PTO), mental health and wellness resources, pet insurance, childcare resources, identity theft insurance, fertility assistance programs, and fitness reimbursement.*
*Horizon Media is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.*
Salary Range
$66,300\.00 \- $100,000\.00
*A successful applicant’s actual base salary may vary based on factors such as individual’s skill sets, experience, training, education, licensure/certifications, and qualifications for the role.* *As an organization, we take an aptitude and competency\-based hiring approach.* *We provide a competitive total rewards package including a discretionary bonus and a variety of benefits including health insurance coverage, life and disability insurance, retirement savings plans, company paid holidays and unlimited paid time off (PTO), mental health and wellness resources, pet insurance, childcare resources, identity theft insurance, fertility assistance programs, and fitness reimbursement.*
Salary Context
This $66K-$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 Horizon Media, Inc., 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 ($83K) sits 50% below the category median. Disclosed range: $66K 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.
Horizon Media, Inc. AI Hiring
Horizon Media, Inc. has 6 open AI roles right now. They're hiring across AI/ML Engineer. Positions span New York, NY, US, Los Angeles, CA, US. Compensation range: $85K - $235K.
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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