Interested in this AI/ML Engineer role at Accenture Federal Services?
Apply Now →About This Role
At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000\+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations.
Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands\-on experience, certifications, industry training and more.
Join us to drive positive, lasting change that moves missions and the government forward!
Accenture Federal Services (AFS) is seeking a strategic, business\-savvy, and forward\-thinking Product, IP, and AI Counsel to join our Cyber and Emerging Technology team. This is a rare opportunity to shape how AFS develops, licenses, protects, and governs proprietary AFS and partner technologies, including software and hardware assets, artificial intelligence, and other intellectual property. In this highly visible role, you will partner with AFS and Accenture leadership.
The ideal candidate brings judgment, subject matter expertise, and the ability to translate complex legal and commercial considerations into clear business guidance. To excel, you should be adept at leading IP and data aspects of product development and sales involving software, SaaS, managed services, and technology partnerships, with a strong understanding of federal and commercial practices.
This role can be performed 100% remotely with a flexible work schedule—giving you the autonomy to do your best work. Ideally, the successful candidate will have the ability to attend key leadership meetings and industry events in\-person in the Northern Virginia/DC area.
Key Responsibilities
This role serves as a trusted advisor on the full lifecycle of AFS technology creation, commercialization, deployment, and governance. Core responsibilities include:
- Interpret and apply evolving legal requirements, government policy, and industry best practices relating to IP, Federal data rights, AI, open\-source software, and secure software development.
- Partner with cross\-functional teams, including product/asset, proposal, delivery, contracting, pricing, cybersecurity, and supply chain to develop innovative commercialization paths.
- Structure, draft, and negotiate contracts, terms of use, and templates for emerging software, SaaS, and managed services.
- Advise on IP protection, inbound and outbound IP licensing, strategic partnerships, and the resolution of IP disputes.
- Manage intercompany IP initiatives and transfers in coordination with global IP and asset licensing teams.
- Lead efforts involving open\-source software, technology partnerships, integration of acquired technologies, asset and service readiness and delivery, and responsible AI—developing robust mitigation strategies and preparing periodic risk assessments.
Knowledge, Skills and Experience
- Deep subject matter expertise in IP, data rights, and contracting.
- Understanding of related technology and services, including cloud services, managed services, and software development.
- Command of software and service deployment models, technology partnerships, and resale arrangements.
- Experience designing, operationalizing, and implementing go\-to\-market, monetization, and compliance strategies for technology solutions.
- Familiarity with secure software development frameworks, open\-source licenses, compliance tools, and risk assessment methodologies.
- Ability to drive complex, cross\-functional projects to successful completion.
- Significant experience in drafting and negotiating government and commercial terms of service and other types of agreements and policies.
Behaviors and Attributes
- Ability to synthesize complex legal analysis into clear, consistent, and actionable business recommendations.
- Ability to efficiently assess risk and drive change to achieve business and legal objectives.
- Motivated and proactive, with a strong desire to understand and address complex legal issues.
- Curiosity for learning about new technologies and industry best practices.
- Strong commitment to ethics, values, and company culture.
- Ability to perform as a leader and a team player.
- Executive presence \- ability to collaborate and influence executives and technical teams
- Ability to work effectively with others remotely.
Minimum Qualifications
- U.S. citizenship.
- Juris Doctor (JD) degree from an accredited law school.
- Active membership in a state bar. If not a member of the Virginia State Bar, must have or obtain a corporate counsel certificate from the Virginia Board of Bar Examiners or register as an in\-house counsel with the Virginia State Bar.
- A minimum of 5 years of legal experience concentrated in IP, software or cloud service product counseling, AI, and/or government contracting.
Strong Candidates Will Have
- 5 to 10 years or more of legal experience in technology transactions, IP, data rights, and/or data governance, focused on U.S. federal business for companies delivering software, SaaS, managed services, and/or other outsourced services.
- Prior experience in a law firm, the legal department of a technology or professional services company, or a relevant U.S. government role.
- Relevant industry or legal certifications.
- Experience applying federal acquisition regulations, including the FAR, DFARS, and other agency supplements and/or rules on safeguarding and dissemination of Controlled Unclassified Information (CUI).
- Experience supporting asset, proposal, and/or delivery teams in the professional services, defense, intelligence, national security, or software development sectors.
- Demonstrated intellectual curiosity and a proactive commitment to professional development in rapidly evolving technology fields.
- The ability to obtain a U.S. government security clearance in the future if needed.
*What We Believe**As a company wholly dedicated to serving the US federal government, we bring together the best talent to help reinvent how federal agencies operate and deliver greater value for their mission and the American people. We have an unwavering commitment to creating a culture in which all our people are respected, feel a sense of belonging, and have equal opportunity. As a business imperative, every person at Accenture Federal Services has the responsibility to create and sustain a culture where everyone feels welcomed and included. This is grounded in our core values and our experience that hiring and developing great people who reflect different perspectives, experiences, and backgrounds is key to driving innovation and delivering the results that our clients and the country count on.*
*Equal Employment Opportunity Statement*
*We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. For details, view a copy of the* *Accenture Federal Services Equal Opportunity Policy Statement.*
*Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women.*
*Requesting An Accommodation*
*Accenture Federal Services is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture Federal Services and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.*
*If you**are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter.*
*Other Employment Statements*
*Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.*
*Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration.*
*Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.*
*The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.*
*California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please* *click here* *for additional important information.*
Salary Context
This $131K-$276K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Accenture Federal Services, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($204K) sits 13% above the category median. Disclosed range: $131K to $276K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. 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: $247,800; VP: $250,000.
Accenture Federal Services AI Hiring
Accenture Federal Services has 8 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer, Data Scientist. Positions span Tampa, FL, US, Chantilly, VA, US, Remote, US. Compensation range: $184K - $360K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $253,500, 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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