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About This Role
Are you our next Legal Innovation Strategist and Advisor?
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You've practiced law. You've drafted the documents, sat through the meetings, and worked around the inefficiencies. And when AI tools hit your radar, you didn't wait. You dove in\-prompting, testing, optimizing\-finding faster, smarter ways to get legal work done.
You're not just curious about AI. You're already using it to transform how you work\-and now, you want to help law firms do the same.
At Affinity Consulting, we're looking for someone with the executive presence to earn the trust of law firm partners quickly, the strategic mindset to guide them through meaningful change, and the communication skills to make complex ideas feel clear and actionable. In this role, you'll help skeptical leaders rethink how their firms operate, uncover smarter systems, and identify practical ways to leverage AI in ways that create genuine excitement about innovation.
This is an opportunity to:
- Design new systems
- Help law firms embrace change\-and thrive in it
- Be seen and heard as a national voice on legal innovation
- Work with a team of smart, kind humans doing work that matters
- If you're ready to stop keeping up with change and start *leading* it, this might be your next big move
What you'll do
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Lead the relationship. You'll lead our AI engagements at the executive level. You'll serve as the bridge between the law firm's real\-life headaches and our team of brilliant AI builders. It's a high\-impact translator role\-perfect for someone who knows what it's like to work inside a law firm, can spot inefficiencies instantly, and can imagine how thoughtful AI adoption, intelligent workflows, and automation can make their work radically better.
You'll get inside practice groups, ask why until the real friction surfaces, and resist the urge to just bolt AI onto a broken process.
You'll build working fluency across the legal AI tools that matter \- Claude, Harvey, Copilot, ChatGPT, Clio Work/Vincent, NetDocs AI \- and turn what you learn into roadmaps that firms can use.
Train differently for different rooms. Partners, associates, paralegals, and staff each use AI differently. You'll need to work side\-by\-side with legal professionals and translate how they can leverage AI to do their work differently.
Put your name on the thinking. You'll also speak, teach, and write\-helping position Affinity as the national leader in legal AI transformation.
What you need on day one
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Executive presence, full stop. The ability to walk into a partner\-level room and be trusted immediately, deliver a hard message without losing the room, and hold your own when smart, senior people disagree with each other and with you.
Real legal practice experience because it gives you built\-in fluency in how legal work moves, and where it gets stuck.
A working understanding of the major AI tools already in or circling legal (Claude, ChatGPT, Copilot, Harvey, Clio Work, etc.). You don't need to be an expert power user in all of them, but you'll need a general understanding of how firms can leverage these tools, so you can hold a credible conversation about them with a skeptical partner.
The ability to connect the two. This is the real job: knowing legal process well enough to see where a firm is stuck, and knowing AI's capabilities well enough to see what's possible and then translating between them, so a firm invests in the right thing instead of the loudest thing.
What you don't need yet
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Developer\-level AI skills. Your job is to lead, advise, translate, and train. Depth on any single platform will sharpen fast once you're working with real client environments.
Your responsibilities.
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Client StrategyDiscovery
- Lead discovery sessions with law firms to understand workflows, uncover frustrations, and identify high\-value opportunities for AI
- Develop strategic roadmaps that show how AI and automation can drive efficiency, quality, and profitability
- Build trust with lawyers, firm leaders, and staff by meeting them where they are\-and showing them where they can go
Internal Collaboration
- Translate client needs into usable documentation for internal AI solution specialists
- Partner with team members to bring strategies to life through implementation and enablement
- Spot patterns and help us standardize our offerings into repeatable, scalable frameworks
TrainingEvangelism
- Deliver live and virtual education sessions for law firms and industry groups
- Participate in podcasts, webinars, and conference panels to help demystify AI for the legal world
- Create enablement assets and thought leadership content that drives demand and trust
Market IntelligenceLearning
- Stay up to date on emerging AI tools, legal tech platforms, and best practices
- Test new tools, evaluate their fit for legal use cases, and contribute to internal evaluations
- Help evolve our AI services based on what's working (and what's not)
What we're looking for.
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We're not just looking for someone who understands law firm life\-we're looking for someone who's lived it *and* reimagined it.
You've practiced recently enough to know how legal work really gets done\- and you're using AI tools to do it better. You understand prompts/skills/workflows, risks, and ROI. You're not just curious about AI\-you're *doing* it, and you want to help others catch up.
You're ready to take that experience and help others transform how they operate\-from solo attorneys to enterprise firms. You ask sharp questions, connect dots others miss, and know how to turn friction into opportunity.
### Bonus points if you bring:
- Experience mapping legal workflows or implementing new systems
- Comfort leading workshops, speaking on panels, or training teams
- A bias toward action and a deep respect for both people and process
You're Our Person If You:
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- Have recent, real\-world experience practicing law
- Are excited\-not intimidated\-by AI, automation, and systems thinking
- Can talk to a skeptical managing partner and a savvy software consultant in the same day
- Love making people feel empowered, not overwhelmed, by new tools
- Want to help shape the future of the legal profession\-and enjoy the ride along the way
More about us and details you'll want to know.
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We're Affinity and Lawyerist (one team; two brands) and we're changing the legal industry by helping legal professionals build healthy businesses and better lives. Alongside our consulting and coaching work, we produce a podcasts (*The Lawyerist*), publish several best\-selling books (*Be a Next Level Leader*), speak at national conferences, and build bold partnerships with the tools and organizations reshaping the legal landscape.
### We also share a commitment to these Core Values:
- Be Inclusive.
- Act with Integrity.
- Grab the Marker.
- Stay Curious.
- Drive Change.
We're 100% remote, so we expect you to have reliable internet, a professional workspace, and the ability to travel for client meetings, conferences and events, and team gatherings.
We work 8:30–5 ET, M–F, with flexibility and trust.
We're hiring for a full\-time role with a starting base salary set based on your experience in the range of $120,000 \- $150,000 plus a performance\-based bonus. Benefits include healthdental, LTD/STD and life insurance, 401(k) matching, an Employee Assistance Program, a professional development budget, a healthwellness stipend, flexible PTO, and a team you'll be proud to work with.
We embrace diversity.
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We strongly encourage candidates from all backgrounds to apply. If you feel unsure, please apply anyway. If you're excited about this role but feel like you're missing a piece or two, let's talk. Imposter syndrome has no place here.
We don't discriminate based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or other differences.
If you have a disability and there's a way we can make the interview process better, please let us know ([email protected] with the subject "AI Strategist Accommodations"). We're happy to accommodate.
Ready to change how law firms work?
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We'd love to hear from you. Click below to apply. You'll be prompted to answer a few questions and upload your resume.
Please note: Candidates must reside and be eligible to work in the United States.
Salary Context
This $100K-$130K 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 Affinity Consulting Group LLC, 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 $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 ($115K) sits 46% below the category median. Disclosed range: $100K to $130K.
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.
Affinity Consulting Group LLC AI Hiring
Affinity Consulting Group LLC has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Miami, FL, US. Compensation range: $130K - $130K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 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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