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Description: WHO WE ARE
AVI-SPL is a digital enablement solutions provider who transforms how people and technology connect to elevate experiences, create new value, and enable organizations to thrive and grow. We are the largest provider of collaboration technology solutions, which include our award-winning managed services.
Our highly certified industry experts and innovation leaders share a vision to help people work smarter and live better. We believe that success starts with a sound team and that an inclusive and diverse workplace moves us all forward.
WHAT YOU’LL DO
The Producer / Gen AI Producer is a key member of AVI-SPL’s Technology & Innovation Group, responsible for managing end-to-end video and creative content production—from concept through delivery. The role combines traditional production responsibilities, with a primary focus on virtual and hybrid events and occasional field production, with an expanding role in generative AI-enabled content creation. The ideal candidate is a strong client-facing producer who can independently lead projects, manage budgets and logistics, collaborate across creative and technical teams, and develop hands-on fluency with emerging generative AI tools and workflows. Excellent client communication, organization, creative judgment, technical adaptability, and a demonstrated eagerness to grow in this rapidly evolving area are essential.
Day-To-Day Responsibilities:
- Lead and manage video, virtual event, and hybrid event productions from pre-production through post, ensuring on-time and on-budget delivery.
- Serve as the primary client liaison, independently managing communications, meetings, technical rehearsals, presentation training, and expectations with senior and executive stakeholders.
- Produce virtual and hybrid events using platforms such as Microsoft Teams, Zoom, and related collaboration and streaming technologies, coordinating technical teams and event workflows from planning through execution.
- Generate creative concepts and collaborate with the Creative Practice Director to align production strategies with client goals, audience needs, and brand vision.
- Plan and execute occasional field productions, including shoot logistics, equipment coordination, crew scheduling, vendor management, and on-site production support.
- Draft project budgets, secure production equipment, and source freelance crews and vendors, including rate negotiation and onboarding compliance.
- Develop hands-on generative AI production skills and contribute to the creation of concept frames, storyboards, visual tests, prototypes, and simple AI-generated video sequences.
- Experiment with and stay current on leading generative AI platforms such as Seedance, Runway, Omni, Midjourney, and other tools as they emerge and evolve.
- Collaborate with creative directors, editors, designers, technical teams, and Gen AI specialists to integrate AI-generated assets into traditional production workflows while maintaining client brand standards and visual consistency.
- Schedule and lead project-level meetings, maintaining ongoing communication with clients and internal teams to ensure alignment and status transparency.
- Maintain and update project tracking tools, production documentation, templates, and workflows for virtual, hybrid, field, and Gen AI-enabled productions.
- Act as a cross-functional bridge between production, creative, and technical teams, contributing to a collaborative culture of experimentation, innovation, and continuous improvement.
- Perform additional tasks, responsibilities, and projects as needed to support the team and organization, ensuring flexibility in adapting to evolving priorities, client needs, and production technologies.
WHAT WE’RE LOOKING FOR
Must-Haves:
- Minimum of a 4-year degree or comparable industry experience is required.
- 5+ years of experience in a leadership role focused on technology Strategy
- 5+ years of experience in the audio visual or collaboration industry is preferred
- 3-5 years of professional producing experience in video production, virtual or hybrid events, corporate media, or a related field.
- Proven ability to independently manage end-to-end productions, including pre-production, production logistics, post-production, budgets, resource coordination, and delivery.
- Demonstrated experience producing virtual or hybrid events, with familiarity with Microsoft Teams, Zoom, and related collaboration or streaming platforms.
- Strong client-facing experience, including running meetings, managing expectations, and communicating effectively with senior and executive-level stakeholders.
- Demonstrated familiarity with generative AI video and image tools, workflows, or use cases, along with strong technical aptitude, curiosity, and a clear eagerness to build hands-on proficiency as the technology evolves.
- Excellent written and verbal communication, organization, and project management skills, with the ability to synthesize and relay complex production plans.
- Ability to work independently under pressure, adapt to shifting priorities and emerging technologies, and manage multiple projects simultaneously.
Nice-To-Haves:
- Master’s degree is preferred.
- Prior hands-on experience with generative AI platforms such as Seedance, Runway, Omni, Midjourney, or comparable emerging tools is strongly preferred.
- Experience with traditional video editing in Adobe Premiere Pro is preferred; familiarity with After Effects and Photoshop is a plus.
- Experience with live streaming platforms, AV production equipment, studio workflows, or virtual event technology.
- Background in creative direction, scripting, storytelling, or visual development for corporate media, including the ability to translate briefs and abstract ideas into effective visual concepts.
- A portfolio or reel demonstrating relevant production, creative, or Gen AI work is preferred; please provide a link if available. Comfort working across time zones and with global teams or clients is also valued.
WHY YOU’LL LIKE WORKING HERE
- Medical benefits, including vision and dental
- Paid holidays, sick days, and personal days
- Enjoyable and dynamic company culture
- Training and professional development opportunities
Pay Type
Min Base
Max Base
Salary
$77k
$85k
Salary Context
This $77K-$85K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At AVI-SPL, 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 in Demand for This Role
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 $212,000 based on 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($81K) sits 62% below the category median. Disclosed range: $77K to $85K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
AVI-SPL AI Hiring
AVI-SPL has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Newton, MA, US. Compensation range: $85K - $85K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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