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About Sellers Dorsey
Sellers Dorsey is a healthcare impact strategy firm focused on improving care access, quality, and outcomes for our nation’s most vulnerable populations. We work with providers, managed care organizations, state entities, and others, to design, implement, fund, and optimize sustainable programs that deliver maximum impact to underserved communities. Built on decades of experience in Medicaid, our team includes former state Medicaid directors, healthcare policy experts, health plan execs, and hospital leaders who know how to navigate the complexities of the system and find creative, impactful solutions that drive the greatest impact for the individuals and communities that need it most.
About the Role
Sellers Dorsey is seeking a new Managing Director, Consulting who will be leading Client Servicing in the Northeast region, which may include all products and services for Sellers Dorsey like Medicaid Financing, strategic consulting, tech enabled solutions for our public and private clients. As the Managing Director, Consulting, you will focus on bringing the very best of Sellers Dorsey’s expertise, ideas, and solutions to our clients, and shaping our future capabilities to meet our clients’ evolving healthcare needs. You will be responsible for managing P&Ls for the states which fall within their responsibility, profitability of the projects they lead, client satisfaction, and employee utilization. You will have direct reports from the client servicing staff and will supervise, train, and ensure learning and development of your team. You will work collaboratively with the network of lobbyists, senior strategic advisors, and subject matter experts. You will also collaborate with Regional Vice President, Director of Healthcare Financing, and Director of Operations on the vision for and execution of their portfolio.
Key Responsibilities
- Client Work: Provide executive leadership across a portfolio of client engagements and projects, managing priorities, deliverables, and timelines within assigned Practice while ensuring exceptional client satisfaction. Oversee the delivery of high-quality project and engagement outcomes to clients according to the agreed schedule, maintaining client satisfaction as well as managing and developing client relationships.
- Corporate Function: Participate in internal work groups to develop new opportunities and offerings for clients, trend issues that impact the work we offer to clients and engage with corporate functions to improve processes to increase the organization’s efficiency and effectiveness.
- Program Knowledge: Continue to develop healthcare and Medicaid program knowledge internally and externally to better understand changing interpretations, identify new opportunities and assess new threats to the work of the practice and the work of the firm.
- Practice Sales Strategy: In coordination with the sales team and RVP, develop and execute a business development strategy, in alignment with the Firm’s overall strategic direction for services and solutions in assigned Practice as well as develop and achieve annual revenue targets and expense budgets for the assigned Practice.
- Contract Management: Oversee the overall portfolio of assigned practice within the Sellers Dorsey’s northeast region and lead in initial sales, renewals and extensions.
- Human Resources: Participate in the recruitment, development, utilization and retention of consulting staff. Provide appropriate mentoring; manage performance feedback, training and professional development opportunities to help individuals in assigned Practice.
- Financial: Manage and review project/engagement financials internally on a regular basis to ensure that Practice utilization targets are achieved, programs/projects maintain or exceed profitability, and firm and client revenues are properly forecasted. Work collaboratively with other members of the Management Team to ensure Firm resources, including both internal and external resources, are utilized in a manner that maximizes Firm long-term profitability and client account growth.
- Business Development: Participate in the development of strategies that respond to market trends and to develop intellectual capital and generate business ideas to enhance the Firm’s consulting services and products. Develop new products and services aligned with the Firm’s overall strategic direction. Work with internal teams to prepare innovative new products and services to the market.
- Internal Collaboration: Collaborate with other practices to share findings and lessons learned and to identify opportunities with other Practices and additional service offerings to existing clients that maximize long term benefits and relationship between the client and Sellers Dorsey.
Key Qualifications
- Bachelor's degree in Public Policy, Public Administration, Public Health, Health Administration, politics, business, economics. Advanced degree in Public Policy, Public Administration, Public Health, Health Administration, business, economics or MBA preferred but not required.
- Fifteen (15) or more combined years in public policy, healthcare management, or the consulting industry. Medicaid experience preferred.
- Experience managing large or complex projects; able to manage several projects simultaneously.
- Recognized leader in the health care industry with demonstrated expertise in strategy and management; possesses established reputation for industry-leading expertise and thought leadership in one or more specialties pertaining to healthcare, preferred Medicaid.
- Proven expertise in developing and managing relationships with providers, stakeholders, clients, key decision makers and contractors.
- Experience managing remote employees and dynamic teams, ensuring staff development and appropriate utilization.
- Advanced oral, written and presentation skills.
- Experience leading negotiations in complex situations.
- Expertise in Medicaid Financing initiatives. Experience serving as state Medicaid Director or state Executive leadership level preferred.
- Strong experience with Microsoft office.
Compensation & Benefits
The anticipated salary range for candidates is $186,800/year in our lowest geographic market range to up to $235,000/year in our highest geographic market range. The final pay offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and years of experience within the job, the type of years and experience within the industry, the candidate’s education, and the candidate’s market location. Typically, candidates are not hired near the top of the range and compensation decisions are made based upon Sellers Dorsey’s Total Compensation Policies & Guidelines. The successful candidate will also be eligible to participate in our annual Corporate Incentive Plan (CIP) that can range to up to 20% of annual salary.
Provided they meet all eligibility requirements under the applicable plan documents, the successful candidate (and their eligible dependents) will be eligible to enroll in group healthcare plans that offer medical, dental, and vision and for insurance plans offering short term disability, long term disability, and basic life. Employees are also able to enroll in Sellers Dorsey’s 401k plan provided they meet plan requirements. Sellers Dorsey offers a Flexible Time Off that allows employees to use what they need. Additionally, we offer 10 paid holidays throughout the calendar year, paid time off for qualifying medical leave, and up to 12 weeks of combined paid parental and bonding leave. The foregoing benefits and paid time off, including an employee’s eligibility therefore, will be controlled by applicable plan documents and Sellers Dorsey policy.
This is intended to provide a general description of benefits and other compensation and is not a substitute for applicable plan documents or company policies.
Sellers Dorsey is an Equal Employment/Affirmative Action employer. We do not discriminate in hiring on the basis of sex, gender identity, sexual orientation, race, color, religious creed, national origin, physical or mental disability, protected Veteran status, or any other characteristic protected by federal, state, or local law.
If you need a reasonable accommodation for any part of the employment process, please contact us by email at HumanResources@sellersdorsey.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this e-mail address.
Sellers Dorsey maintains a Drug-Free workplace.
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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Sellers Dorsey, 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 in Demand for This Role
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 $154,000 based on 8,743 positions with disclosed compensation. Director-level AI roles across all categories have a median of $230,600.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Sellers Dorsey AI Hiring
Sellers Dorsey has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $160,000 across 1,226 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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