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About This Role
Arnold \& Porter is a leading international law firm with offices throughout the United States, Europe, and Asia. The firm advises clients across a broad range of regulatory, litigation, and transactional matters, including many of the world's largest companies and organizations.
We are seeking a Director of Technology Experience \& AI Training to lead the evolution of our technology experience and AI enablement strategy. This highly visible leadership role will oversee enterprise Audio \& Video Services and AI\-focused Training programs, helping shape how attorneys and business professionals leverage emerging technologies to deliver exceptional client service.
As Director of Technology Experience \& AI Training, you will be responsible for driving the firm's technology experience strategy while accelerating the adoption of AI\-powered tools and workflows across the organization. You will lead teams responsible for enterprise collaboration technologies, meeting and event experiences, and firmwide AI learning initiatives.
Working closely with the CIO, senior leadership, and key stakeholders across the firm, you will play a critical role in defining how technology and artificial intelligence enhance productivity, collaboration, and innovation.
Key Responsibilities
- Lead and develop teams responsible for Audio \& Video Services and AI Training.
- Drive the firm's AI adoption strategy, including training, change management, and user enablement initiatives.
- Design and oversee learning programs that help attorneys and business professionals effectively leverage AI\-enabled technologies.
- Partner with firm leadership, Practice Groups, HR, and IT teams to identify technology and AI learning needs and develop targeted solutions.
- Oversee enterprise collaboration technologies, conference room experiences, hybrid meeting environments, and firmwide event support.
- Evaluate and implement emerging technologies, including AI\-powered productivity, collaboration, meeting intelligence, and transcription solutions.
- Establish policies, standards, and best practices that promote innovation, operational excellence, and an exceptional user experience.
- Manage vendor relationships, budgets, and service delivery across both functional areas.
- Measure technology adoption, training effectiveness, and user experience outcomes through data\-driven insights and continuous improvement initiatives.
- Serve as a trusted advisor to senior leadership on technology experience, AI enablement, and workforce readiness.
Qualifications
- 7\+ years of leadership experience in enterprise information technology environments.
- 7\+ years of experience managing, implementing, or supporting enterprise technology solutions.
- Experience leading AI enablement, technology training, digital transformation, organizational change management, or related initiatives.
- Knowledge of generative AI technologies and platforms, including Microsoft 365 Copilot, ChatGPT Enterprise, Claude, Harvey, or similar solutions.
- Experience with enterprise collaboration technologies, including Microsoft Teams, Zoom, and modern AV environments.
- Familiarity with instructional design, learning management systems, and technology training programs.
- Strong leadership, communication, stakeholder management, and project management skills.
- Experience in a professional services, legal, consulting, financial services, or similarly complex environment is preferred.
- Bachelor's degree or equivalent combination of education and experience preferred.
The anticipated base salary for this position is $150,000 to $200,000\. The actual base salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location in which the applicant lives and/or from which they will be performing the job.
The firm may provide a discretionary bonus annually
*\#LI\-HYBRID*
Salary Context
This $150K-$200K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1889 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 3,736 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At ARNOLD & PORTER LLP, 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 $181,357 based on 12,694 positions with disclosed compensation. Director-level AI roles across all categories have a median of $248,100. Disclosed range: $150K to $200K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,650. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $248,100; VP: $250,000.
ARNOLD & PORTER LLP AI Hiring
ARNOLD & PORTER LLP has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $200K - $200K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% 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 3,736 open positions tracked in our dataset. By seniority: 109 entry-level, 1,755 mid-level, 1,486 senior, and 386 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (562 positions). The remaining 3,158 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,650. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,736 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,564), Data Scientist (311), AI Software Engineer (277). 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 (109) are outnumbered by mid-level (1,755) and senior (1,486) 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 386 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (562 positions), with 3,158 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 $200,100. Top-quartile roles start at $253,650, and the 90th percentile reaches $307,500. 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 $275,000 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 (1,942 postings), Aws (1,175 postings), Azure (881 postings), Rag (827 postings), Gcp (718 postings), Prompt Engineering (590 postings), Pytorch (586 postings), Claude (528 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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