Interested in this AI/ML Engineer role at Shutterstock?
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About the Opportunity
Shutterstock enables our customers, partners, contributors, and employees to achieve their goals and realize new opportunities. Our continued growth opens new doors as we scale our platform, expand our offerings and build a company that’s ready for the future!
The newly formed custom content and branded production arm of Shutterstock – Shutterstock Studios – has an opening for a critical role within the global organization, one that will be tasked with owning the AI Services bidding process and in doing so create compelling, market\-ready bids to fuel our rapidly growing business. The Studio is made up of best\-in\-class producers and creatives designed to execute creative excellence while delivering an exceptional client experience.
Shutterstock Studios has had an incredible year of growth – the global production studio has scaled from producing highly creative social content to producing TV spots, integrated digital campaigns, custom 3D animation, and original long form documentaries for the world's biggest brands and agencies. The Studio is a highly sophisticated, global interconnected creative and production solution – designed to service across all content needs for video, photo, experiential, music, 3D, Generative AI, animation, and XR.
We’re seeking an experienced Bidding Producer with extensive experience working across commercial global production with the ability to support multiple bids at once. The ideal candidate is proactive, highly collaborative and has exceptional organizational skills.The candidate will be integral to the growth of the business, partnering with sales, production team and clients to make sure responses are to a high standard, matching clients needs and helping to drive growth and client relationships.
*Note \- This is starting as a temporary, 6 months fixed\-term assignment with the possibility to extend.*
The day to day
- Strategically respond to RFPs and new business opportunities in partnership with the Director of AI Services \& Ops, VP of Product Innovation
- Support client discovery sessions to identify client needs, project goals and technical requirements
- Develop scopes, budgets and timelines that balance client objectives, technical feasibility, operational efficiency, and profitability
- Partner with Director of AI Services \& Ops and VP of Product Innovation to create client\-facing materials
- Collaborate with subject matter experts to shape scalable solutions
- Serve as the primary liaison between Client Partner and Production during the presale handoff process, ensuring opportunities are clearly scoped and set up for successful onboarding
- Lead presale communications and workflows, keeping stakeholders aligned on scope, assumptions, timelines, and project status
- Maintain pricing frameworks, rate cards, and scoping standards in line with market conditions and evolving AI service models
- Organize and maintain bidding trackers and production finance trackers
- Stay informed of industry trends, emerging technologies, and market pricing
What you’ll bring to the role:
- Minimum of 5 years experience in commercial production, creative services, technical production, or related fields; 3\+ years working in a client\-facing capacity
- Exceptional problem\-solving skills with the ability to operate effectively in ambiguous environments and make informed recommendations with incomplete information
- Expertise in varying production outputs with a specialism in post production
- Strong production finance understanding (budgeting critical)
- Experience in all forms of production, video, stills, animation, motion graphics, generative AI at different budget levels
- Experience working and negotiating with all talent levels
- Can\-do attitude is a must
- Experience leading bid responses, RFP’s, pitch materials
- Excellent time management and attention to detail
- Excellent written \& verbal communication skills
Why Shutterstock:
- You have a direct impact on the success of the company. Your team’s work matters and is essential to the evolution of our core business!
- Executive leadership cares personally. They prioritize growth and planning your career path with your goals and passions in mind.
- Flexibility to work between home and office with everything you need to be successful in both
- A generous and competitive benefits package.
Shutterstock connects diverse artists and creative professionals around the globe with the agencies, brands and people who need their work and services. It’s a place where creators come to be inspired and discover new ways to produce their best work.
Shutterstock enables its employees to drive culture and tap into the world around them to develop the toolbox and solutions that help others share their world views. At Shutterstock, your ideas will be welcomed, your uniqueness will be celebrated, and you will be supported in presenting your view of the world as you experience it. We’re champions of resiliency; quickly learning from our shortcomings in our pursuit of continuous growth.
Diverse teams are critical to our success. We encourage people from different backgrounds to apply and we commit to creating and maintaining a culture where employees know they belong and have equal opportunities to succeed.
*Hourly rate range for this role in the New York City Area is $52\.88\-$57\.69 per hour.*
Shutterstock Values
We are one team collectively focused on creating an unrivaled experience for our Customers and Contributors. Our Values represent the mindset of the employee who will thrive at Shutterstock. If you are passionate about what you do, and want to become part of a cutting\-edge technology company building industry leading products, please apply.
Shutterstock is an Equal Opportunity Employer. Suitably qualified and eligible candidates are encouraged to apply regardless of age, color, disability, national origin, ancestry, race, religion, gender, sexual orientation, gender identity and/or expression, veteran status, genetic information, or any other status protected by applicable law.
Shutterstock ensures that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence, accommodation\[email protected].
Salary Context
This $108K-$118K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Shutterstock, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($113K) sits 47% below the category median. Disclosed range: $108K to $118K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Shutterstock AI Hiring
Shutterstock has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $118K - $245K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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