Interested in this AI/ML Engineer role at KIZEN Technologies, Inc.?
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About This Role
Location: New York (Grand Central), NY (In\-office 4x per week)
About Us
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Kizen's Platform, AI Agents \& True Context Technology (TCT) power millions of mission\-critical experiences for leading organizations in highly regulated industries (insurance, healthcare, financial services).
Our platform helps organizations automate the workflows that matter most — from helping insurance agents manage contracting and commissions, to enabling healthcare providers to deliver proactive patient care, to empowering financial institutions to classify documents and extract data automatically.
And that's just the beginning. With Kizen, developers can build new enterprise applications and impactful AI agents, while business users can customize dashboards and agents using natural language, low\-code, or code — all on the same platform.
What used to take months or years to build, configure, and connect now takes just days. Kizen combines powerful pre\-built agents and use cases with an enterprise platform for automation and data connection — all built on an AI\-first architecture that's easy to adopt, scale, and trust.
We're solving real operational problems and helping the world's most complex organizations work faster, smarter, and more humanely.
Join us in transforming how industries work — one workflow, one agent, and one customer success story at a time.
About the Role
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Are you ready to rewrite the growth playbook for the AI era? We are looking for a hands\-on Growth Marketer with a history of scaling high\-growth B2B SaaS companies and building robust revenue pipelines as we bring our next\-gen platform to the world.
This is an opportunity of a lifetime for someone who wants to be at the heart of the AI movement. As our first Growth Marketer, you'll be working directly with our VP of Marketing to build a predictable, scalable demand\-generation engine that adapts at the speed of artificial intelligence.
In this highly dynamic role, you'll lead our teams responsible for:
- Pipeline Generation: You will own the numbers, driving the strategy and execution to generate qualified leads and measurable ARR.
- Rapid Experimentation: You will design, test, and iterate on growth hacks across multiple channels, knowing when to double down and when to pivot. From paid search, to SEO/GEO/AEO to email to other digital channels, you own it.
- AI\-First Marketing: You won't just market AI; you will use AI to market, integrating cutting\-edge tools to personalize, scale, and optimize campaigns faster than a traditional team ever could.
- Cross\-Functional Alignment: Working closely with Sales, Product, Partners and Engineering teams to ensure marketing initiatives are tightly integrated with product launches and sales goals.
Key Responsibilities
- Pipeline Generation \& Scaling You will be the architect of our demand generation engine. This means developing and executing multi\-channel campaigns (SEO, GEO, SEM, paid social, email, events) to drive sales qualified leads (SQLs), and ultimately, revenue.
- Rapid Experimentation \& "Growth Hacking" We operate in a fast\-paced environment where yesterday's tactics might not work tomorrow. Develop and manage high\-impact digital marketing campaigns. You will implement a vigorous A/B testing framework across landing pages, ad copy, and email sequences. You will ruthlessly analyze data to find the lowest Customer Acquisition Cost (CAC) and highest lifetime value (LTV) channels.
- AI\-Integrated Campaign Strategy You will leverage AI tools to automate workflows, personalize outreach at scale, and uncover hidden data trends that inform our growth strategy.
- Cross\-Functional Alignment \& Analytics Own the marketing funnel (MQL, SQL, Pipeline) and provide clear, actionable reporting on campaign performance, cost per acquisition (CPA), and return on investment (ROI). Growth also doesn't happen in a silo. You will partner tightly with Sales to ensure lead quality and smooth handoffs, and collaborate with Product to align marketing messaging with rapid feature releases. You will also own the growth dashboard, reporting on key metrics to leadership weekly.
- AI\-Driven Account\-Based Marketing (ABM) Partner closely with Sales leadership to identify, target, and win high\-value enterprise accounts. You will design and execute highly personalized, multi\-touch ABM campaigns, treating our biggest prospects as a "market of one." By leveraging AI to predict buyer intent, map complex buying committees, and hyper\-personalize outreach at scale, you will drive engagement with key decision\-makers and accelerate our highest\-value deal cycles.
- Website \& Conversion Rate Optimization Lead A/B testing initiatives on the company website and landing pages to improve user experience and optimize lead capture conversion rates.
Requirements
- Experience: 4\+ years in a growth marketing, demand generation, or performance marketing role within a B2B SaaS/tech/services environment.
- Track Record: Proven success in taking a company from early\-stage revenue to a scaled pipeline (e.g., $10M to $50M\+ ARR).
- The "Athlete" Mindset: Exceptional agility; you are comfortable with ambiguity, can think on your feet, and pivot strategies based on real\-time data.
- AI Fluency: Strong familiarity with, or a deep desire to master, AI tools for marketing (e.g., LLMs for copywriting, predictive scoring, automated workflows).
- Technical Chops: Proficiency in MarTech stacks (e.x., HubSpot, Salesforce, Google Analytics, Looker, SEMrush, Apollo).
- Analytical Prowess: You are highly data\-driven. You dream in CAC, LTV, conversion rates, and cohort analysis.
- Channel Expertise: Hands\-on experience managing and scaling paid search, paid social (especially LinkedIn), and outbound email campaigns.
- Copywriting Skills: Ability to write compelling, conversion\-focused copy for ads, landing pages, and emails both with or without AI.
- Execution\-Oriented: You have a strategic mind but love rolling up your sleeves to build campaigns in the trenches.
- Problem Solver: A history of identifying funnel bottlenecks and systematically testing solutions to unblock them.
- Communication: Excellent verbal and written communication skills to articulate growth strategies to stakeholders across the business.
- Resilience: A high tolerance for failure in the pursuit of innovation—you know that 7 out of 10 experiments might fail, but the 3 that succeed will 10x the business.
- A growth mindset: curious, proactive, and comfortable operating in a fast\-paced, ambiguous environment.
- Proficiency in HTML/CSS for minor landing page adjustments is a plus.
Why Kizen
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We're a fast\-growing company that values innovation, growth, and continuous improvement. By joining Kizen, you'll play a pivotal role in shaping the future of the company while enjoying a supportive, dynamic, and collaborative workplace. You'll have opportunities for professional development, impact, and career advancement.
What We Offer
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- Career Growth Opportunities
- Engaging Work Culture
- Top\-Tier Compensation
- Equity Package
- Healthcare Coverage
- Health and Fitness Stipend
- Professional Development Stipends
- PTO
Kizen is proud to be an equal\-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics. At Kizen, we fully comply with the Americans with Disabilities Act (ADA). We are dedicated to embracing challenges and creating an accessible, inclusive workplace for all individuals.
The base salary range for this position is $120,000\-$175,000. However, base pay offered may vary depending on job\-related knowledge, skills, and experience. In addition to base salary, we also offer generous equity and benefits packages.
If you're excited about creating impactful experiences and contributing to a fast\-paced, people\-focused team, we'd love to meet you!
OTE \- $220,000
Salary Context
This $120K-$175K 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 KIZEN Technologies, 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 ($147K) sits 12% below the category median. Disclosed range: $120K to $175K.
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.
KIZEN Technologies, Inc. AI Hiring
KIZEN Technologies, Inc. has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $175K - $175K.
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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