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About This Role
We are:
Accenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. With strong client relationships and deep industry expertise, we help our clients operate at the speed of life through the unlimited potential of imagination, technology, and intelligence. Visit us at: www.accenture.com/song.
You are:
You have proven work experience in Retail and digital. You are a strategic problem solver with extensive consulting and/or retail industry experience. You are a clear and effective communicator, and you have an open, relatable manner with clients and colleagues. You perform well in an agile, fast-paced working environment. You know how to balance being a leader with contributing to the collective efforts of the team.
You have energy and drive in abundance, along with personal resilience, a passion for serving clients, and a love of continual learning. You have a flair for breaking down processes into logical parts and constructing crystal-clear reasoning and analyses—an aptitude you use to decimate problems.
You have experience working with senior and executive-level client partners, facilitating workshops, developing business recommendations, and building business cases for new innovative solutions (e.g. AI / Gen-AI enabled capabilities). You know how to balance project delivery responsibilities of your team, as well as managing project progress up to internal and client leadership.
You also are:
- Passionate about helping clients solve complex growth and customer experience challenges, as well as supporting them through strategic transformations.
- Knowledgeable about the nuances of Retail industry broadly as well as digital and marketing organizations and are ready to apply your knowledge to help clients optimize and transform their sales and service solutions.
- Have a high-level understanding of how technology platforms and ecosystems fit into the digital world and how digital technology is changing business
- Get lost in researching the latest innovation in digital customer experience across all industries and thinking about how it might transform the retail industry in the future.
- Ready to dive deep into problem solving using creative and analytical thinking to transform challenges into opportunities.
- Energized by working in an agile, fast-paced environment and are at your best when collaborating with a team.
- Excellent communication (written and oral) and interpersonal skills, including compelling storytelling around insights, challenges, and solutions for an executive audience
The work:
As a Strategy Manager, you will apply your expertise in customer growth strategy and digital channel execution, and to define and enable front office growth strategies and approaches to help clients achieve top line growth objectives with a focus on demand generation and channel activation. You will deliver on engagements in the following areas:
Thought Leadership
- Able to understand client needs, support the development of proposed solutions, and deliver high-impact projects by partnering with clients to help them support and transform their sales organizations and advance their position in Retail.
- Build client relationships to sustain Accenture’s profile as a long-term trusted advisor and partner.
- Manage and coach junior team members while continuing to grow your own expertise to help Accenture maintain its thought leadership position.
Delivery Execution
- Design and execute large scale and complex transformation programs and strategy engagements including current state assessments, target state design, and operating model transformations.
- Implement business changes that drive industry-specific, functional, and digital operating model transformation.
- Deep understanding of digital channel metrics across web, mobile, and social commerce, with demonstrated success driving business value with data-led action.
- Comfort and functional knowledge of core technology enablers used by leading retailers and consumer goods companies. Ability to analyze potential solutions, understand fit for functional business needs, confidence to select the most relevant tools/techniques to meet business requirements.
- Ability to lead teams to execute analysis or delivered recommended solutions including business case development, process design, and capabilities improvement.
Here’s what you’ll need:
- 6+ years of Retail industry experience, driving digital growth and/or channel expansion in a business, product or strategy role. A robust understanding of the Retail industry is required, along with familiarity with topic areas such as:
- Retail marketplace strategy, activation, and optimization
- Direct to consumer and digital commerce growth
- Retail media strategy, activation, measurement, and operations
- Digital channel operations
- Product and content management
- Go-to-market strategies
- Supporting the development strategic recommendations (or decisions) for critical experiences, products, or services of the organization (and/or)
- Managing a P&L or a pipeline of business development opportunities (and/or)
- Providing enterprise level business or technology advisory all the way to various executives (AVP / VP / SVP or c-suite level)
Bonus Points If:
- MBA or equivalent graduate degree.
- Strong quantitative skills and analytical thinker with at least 2 years of prior experience driving insights using analytical tools
- High degree of comfort in client relationship development and business development.
- You have experience working with onshore and offshore delivery teams.
- You bring an existing network of relationships within the Retail industry at decision making levels (AVP / VP / SVP or c-suite level).
- You are familiar with AI, GenAI, or other emerging technologies.
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.
We accept applications on an on-going basis and there is no fixed deadline to apply.
Information on benefits is here.
Role Location Annual Salary Range
California $87,400 to $253,000
Cleveland $87,400 to $253,000
Colorado $87,400 to $253,000
District of Columbia $87,400 to $253,000
Illinois $87,400 to $253,000
Maryland $87,400 to $253,000
Massachusetts $87,400 to $253,000
Minnesota $87,400 to $253,000
New York/New Jersey $87,400 to $253,000
Washington $87,400 to $253,000
Requesting an Accommodation
Accenture 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 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 would like to be considered for employment opportunities with Accenture and have accommodation needs such as for a disability or religious observance, please call us toll free at 1 (877) 889-9009 or send us an email or speak with your recruiter.
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 Equal Opportunity Statement
Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.
Accenture is committed to providing veteran employment opportunities to our service men and women.
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 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. Further, at Accenture a criminal conviction history is not an absolute bar to employment.
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.
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Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.
Salary Context
This $87K-$253K range is above the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 33,423 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Accenture, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($170K) sits 11% above the category median. Disclosed range: $87K to $253K.
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.
Accenture AI Hiring
Accenture has 6 open AI roles right now. They're hiring across AI/ML Engineer. Positions span New York, NY, US, San Francisco, CA, US, Seattle, WA, US. Compensation range: $253K - $253K.
Location Context
AI roles in Chicago pay a median of $203,250 across 214 tracked positions. That's 7% 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 33,423 open positions tracked in our dataset. By seniority: 3,283 entry-level, 20,769 mid-level, 6,381 senior, and 2,990 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,320 positions). The remaining 30,984 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 33,423 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (30,275), AI Software Engineer (749), AI Product Manager (741). 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 (3,283) are outnumbered by mid-level (20,769) and senior (6,381) 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 2,990 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,320 positions), with 30,984 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 (21,235 postings), Aws (11,126 postings), Rust (9,803 postings), Python (4,999 postings), Azure (3,220 postings), Gcp (2,707 postings), Prompt Engineering (1,817 postings), Openai (1,487 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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