Interested in this AI/ML Engineer role at Miva, Inc.?
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About This Role
Miva is currently looking for a full\-stack Web Developer with solid solution engineering skills and deep ecommerce experience to join Miva’s Professional Services team. This role focuses on building high\-performing ecommerce experiences on the Miva platform using core web technologies—no heavy frameworks, just solid engineering fundamentals enhanced by modern AI tooling.
This is a client\-facing delivery role, not an internal product or R\&D position. The chosen Web Developer will collaborate closely with Product Managers, UX Designers, and other delivery team members to translate business requirements and user needs into high\-performing solutions that adhere to defined scope and timelines and maximize platform capabilities. As a key technical liaison, you will communicate effectively with clients in both written and verbal forms and translating complex technical concepts into clear, actionable guidance for non\-technical stakeholders.
AI\-Driven Development \| We are an AI\-first web development team. You’ll be expected to:
- Use AI tools for rapid prototyping, first\-pass code generation, and workflow automation
- Accelerate integrations, data transformations, and repetitive development tasks with AI assistance
- Leverage AI for documentation, code reviews, testing, and performance optimization
- Maintain high code quality while using AI as a force multiplier—not a crutch
Things you will do:* Develop and maintain ecommerce storefronts using HTML5, CSS3, and modern vanilla JavaScript (ES6\+) within Miva’s templating environment
- Write efficient server\-side logic using Miva Template Language (MVT) to power dynamic content
- Build and support integrations with external systems (REST/SOAP APIs, ERPs, CRMs, payment, shipping, analytics, and marketing tools)
- Act as the technical bridge between client storefronts and their broader business ecosystem
- Troubleshoot and resolve frontend, backend, and configuration issues across platforms
- Optimize performance, SEO, accessibility, and conversion (Core Web Vitals, GA4, GTM, etc.)
- Implement merchandising strategies, personalization, promotions, and optimized purchase flows
- Ensure cross\-browser/device compatibility with a mobile\-first approach
- Collaborate with Product Managers, UX Designers, and delivery teams to execute within scope and timelines
- Communicate clearly with clients, translating technical concepts into actionable insights
Things you will bring:* 3\+ years of professional web development experience (1\+ year in ecommerce)
- Strong proficiency in HTML5, CSS3, and vanilla JavaScript (ES6\+)
- Advanced mastery of AI coding assistants (e.g., GitHub Copilot, Cursor, Claude Code) integrated into daily development workflows to accelerate output without sacrificing underlying code quality or engineering fundamentals
- Ability to write CSS that works across browsers without relying on CSS\-in\-JS libraries
- Experience building API integrations (REST and/or SOAP)
- Working knowledge of PHP and SQL\-based databases (MySQL/PostgreSQL)
- Strong understanding of DOM manipulation without relying on libraries
- Experience with Git\-based workflows, including experience with AI\-enhanced pull request generation, merge conflict resolution, and automated commit messaging
- Solid grasp of performance optimization, SEO, and accessibility (WCAG)
- Ability to manage multiple projects in a client\-facing delivery environment
- Strong communication skills in a remote, collaborative setting
Bonus points if you have:
- Experience with platforms like Miva, Shopify, BigCommerce, or Magento
- Familiarity with ERPs/CRMs (NetSuite, Salesforce, Microsoft Dynamics, etc.)
- Experience with build tools (Webpack or similar) and modern PHP frameworks (Laravel) with a focus on MVC design patterns, RESTful API development, and scalable backend architecture
- Experience using containerization or local development tooling such as Docker
- Agency or Professional Services experience
- Experience building AI automation scripts, leveraging LLM APIs directly, or integrating AI agents into CI/CD deployment pipelines and testing workflows
Our awesome perks!
- Remote company \- work from anywhere
- Unlimited PTO
- Maternity/Paternity leave
- Medical/Dental/Vision/FSA/Life
- 401k with company match
- Flexible work schedule
- Inspiring \& collaborative peers
- Work within a company that has been recognized multiple times as a top employer, most notably being named one of the “Best Places to Work in San Diego” by the San Diego Business Journal!
The salary range for this position is $90k \- $115k annually. This information is current as of the initial date of this job posting and may be modified in the future. The actual pay determined for an individual will vary based on job\-related factors such as relevant experience and/or education, particular skills, and location.
Miva is a fully remote company with employees distributed across the U.S. Our ideal candidate for this role will reside in one of the following states: AZ, CA, CO, FL, GA, ID, IL, KS, MA, MI, MO, NC, NH, NJ, NV, NY, OH, OR, PA, SD, TN, TX, UT, VT, or WA.
Miva is a leading eCommerce software dedicated to empowering enterprise merchants and agencies with a state\-of\-the\-art online storefront. To date, Miva software has powered over $100 billion in online sales for retailers worldwide.
Our success and the success of our clients are driven by high\-performing teams of talented professionals. By creating a culture in which passion, ingenuity, and collaboration are rewarded, we have become the driving force for the advancement of independent commerce.
Miva is backed by Equality Asset Management, a private equity firm who is committed to supporting Company growth.
Miva has been named a Best and Brightest Company in 2018, 2019, 2020, 2021, 2022, 2023 and 2024\.
Miva, Inc. is an Equal Opportunity Employer.
Read Miva's Applicant Privacy Notice Here.
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Salary Context
This $90K-$115K 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 Miva, 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 ($102K) sits 39% below the category median. Disclosed range: $90K to $115K.
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.
Miva, Inc. AI Hiring
Miva, Inc. has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $115K - $115K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% 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 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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