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About This Role
At Similarweb, we are revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online.
We're looking for a Field Marketing Manager to support our LLM and OEM Partnerships team, one of the most strategically important and fastest-growing areas of our business. AI is transforming entire industries, and the data that powers it has to come from somewhere. Similarweb is one of those sources, and demand for what we provide to the world's leading AI companies is growing fast. This role exists to build the marketing engine that gets us in front of the right people, at the right companies, at the right time.This role comes with real ownership and few constraints - if you have an idea, you can run with it.
This role is based in Burlington, MA with regular travel to San Francisco, where much of the AI and data ecosystem lives, and building presence there is a core part of the job.
You will report to the Americas Field Marketing Director and work closely with our AI & OEM team to build brand presence, deepen relationships, and create meaningful moments with some of the biggest names in AI and tech.
So, what will you be doing all day?
- Build and execute multi-channel marketing programs: digital, direct, and in-person - that get us in front of new buyers and nurture existing relationships at our highest-priority target accounts across tech companies
- Own conference sponsorships and speaking opportunities end-to-end - strategy, logistics, on-site execution, and ROI measurement, with a focus on establishing Similarweb as a recognized name in the AI and data space
- Plan and execute owned and co-hosted events, from intimate executive dinners to flagship activations
- Run executive entertainment and on-site engagement programs with senior stakeholders at major tech companies
- Support the buildout of a dedicated microsite, content calendar, and social presence for our AI and data partnerships business - including case studies, whitepapers, press releases, and blog content
- Influence how Similarweb shows up in the AI and data ecosystem - from branding and messaging to in-person activations
- Collaborate daily with the sales team to identify new opportunities, support active accounts, and keep marketing aligned with pipeline goals
- Bring new ideas to the table and own them from first concept through final execution
This is the perfect job for someone who:
- 4+ years of experience in field marketing or partnerships marketing in a B2B environment
- A track record of running events and programs end-to-end with complete ownership, the venue, the vendor, the internal approvals, the client-facing materials, and the follow-through
- Experience managing budgets, vendors, and multiple workstreams simultaneously without losing track of the details
- Strong relationship-building skills, both internally with fast-moving teams and externally with senior stakeholders at major tech companies
- A proactive communication style - with their manager, with sales, with vendors
- Curiosity and enthusiasm for the AI and data space - prior experience not required, but a hunger to learn is a must
- Comfort with regular travel to San Francisco and to events and activations as needed
- A self-starter mentality, someone who thrives with ownership and few constraints
- Someone who brings creative energy to every touchpoint and is always looking for new ways to bring the brand to life
At Similarweb, collaborating with our colleagues in-office creates a more connected, unified culture. Our best work is a product of our face-to-face collaboration, with the ability to work partially from home.
The base salary range for this position in Burlington, MA is $120,000 to $155,000 plus benefits including: medical, dental and vision insurance, 401K plan, potential equity, employee stock purchase plan and paid sick and parental leave.
Individual compensation is based upon several factors, including qualifications and relevant experience.
The base salary range above is for the Burlington, MA area and could vary for candidates in other locations.
Why you'll love being a Similarwebber:
You'll get to sell a product you actually believe in: Our customers aren't our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said "the product." Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world.
You'll find a home for your big ideas: We encourage an open dialogue and empower employees to bring their ideas to the table. You'll find the resources you need to take initiative and create meaningful change within the organization.
We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours.
You can grow your career in any direction you choose: Interested in becoming a VP or want to transition into a different department? Whether it's Career Week, personalized coaching, or our ongoing learning solutions, you'll find all the tools and opportunities you need to develop your career right here.
Diversity isn't just a buzzword: People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience. We believe our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day.
Please note: We're unable to sponsor employment visas at this time.
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Salary Context
This $120K-$155K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At SimilarWeb, 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 $212,040 based on 13,780 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($137K) sits 35% below the category median. Disclosed range: $120K to $155K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
SimilarWeb AI Hiring
SimilarWeb has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Burlington, MA, US. Compensation range: $155K - $155K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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