Interested in this AI/ML Engineer role at Accenture?
Apply Now →Skills & Technologies
About This Role
We Are:
The beginning of a new Data \& AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data \& AI — backed by a $3B investment and commitment to our people to do industry\-defining work.
With over 77,000 professionals dedicated to Data \& AI, Accenture’s Data \& AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.
You are:
A growth focused sales professional who has successfully created positive impact through year\-on\-year business expansion. You know – and have run all phases of a sales cycle, including qualification, sales pursuit and close by applying deep sales process and technical expertise. You develop relationships with key buyers and decision\-makers at new and existing clients by utilizing a differentiated roadmap and framework leveraging the latest cloud\-based technologies.
As a Sales capture, you will originate new sales opportunities unrelated to extensions or renewals in a complex environment, typically cross service\-group. Lead early\-stage positioning with clients and develop and execute the origination strategy to identify and qualify specific opportunities. Continue working with the sales team to ensure closure of sales. May focus on a single large account, leveraging deep content knowledge and client relationships to originate and close opportunities at that client.
The work:
- Create solutions to complex technology business problems/opportunities requiring in\-depth knowledge of client buyer needs.
- Interacts with senior management levels at clients and within Accenture, determines pursuit strategies, develops client messaging plans and relationships, and applies industry\-leading Snowflake or Databricks transformation strategies and practices.
- Has latitude in decision\-making and determining objectives and approaches to critical assignments.
- Operates within large teams and directs specific team sales activities.
- Ability to mobilize the Ecosystem partners ( AWS , MS , SAP etc ) for driving larger Mega deals – driving business outcomes tied to RPO ( remaining performance obligations) of the ecosystem.
Travel may be required for this role. The amount of travel will vary from 25% to 100% depending on business need and client requirements
What you need:
- Minimum of 8 years of experience in selling data solutions, analytical data warehouses, cloud data migration solutions, analytics/reporting solutions to harness the power of AI and GenAI for our clients.
- Minimum of 2 years of experience in selling Snowflake and/or Databricks platforms.
- Minimum of 5 years previous experience of selling into any of these industries is required; Financial Services, Communications/Media/Technology, Products (Consumer, Retails, Industrial), Public Sector, Resources (Utilities, Oil \& Gas, Energy)
- Minimum of 8 years’ Sales Pursuit Management experience.
- Minimum of 2 years’ experience in direct sales, preferably with quota of $10M\+
- Proven ability to manage the entire sales cycle (customer identification, outreach, proposal creation, contract negotiations, closing, metrics reporting)
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If associate’s degree, must have minimum 6 years work experience)
Bonus points if you have:
- Thought leadership in data migration, modernization and managed services, building new data architectures (Mesh/Fabric), data products and marketplaces, cloud data \& analytics platforms and use cases, AI and Gen AI foundation model services.
- Experience working within G2000 customers.
- Experience with C\-Level client relationship building and relationship management.
- Proven ability to operate within a team\-oriented environment.
- Demonstrated commitment, teamwork and collaboration in a professional setting; either military or civilian.
- High energy level, focus and ability to work well in demanding client environments.
- Excellent communication (written and oral) and interpersonal skills.
- Strong leadership, problem solving, and decision\-making abilities.
- Unquestionable professional integrity, credibility and character.
- Strong Ecosystem selling experience with AI led Data engineering transformational programs.
What’s in it for you?
- You will be part of a diverse, vibrant, global Accenture community; teams pushing the boundaries of new business capabilities and emerging technologies and services, sharing their experiences and lessons learned with each other. You’ll have the chance to thrive in an environment where your ideas are valued and your voice matters.
- At Accenture, you will be able to work on meaningful and innovative projects, powered by the latest technologies and industry best practices such as event\-driven architectures and domain driven design.
- Accenture will continually invest in your learning and growth. You'll learn from and work with Accenture’s certified practitioners and Accenture will support you in growing your own tech stack, sales skills, and certifications.
- You'll be immersed in the design and implementation of human\-centric solutions to help solve complex challenges with some of the world’s largest companies.
In addition to base pay, this Sales role is eligible for additional incentive compensation which is based on achievement toward individual sales metrics, subject to Plan terms
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 anticipate this job posting will be posted until 07/24/2026\. Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long\-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits \| Accenture
Role Location Annual Salary Range California $136,800 to $237,600 Cleveland $136,800 to $237,600 Colorado $136,800 to $237,600 District of Columbia $136,800 to $237,600 Illinois $136,800 to $237,600 Maine $136,800 to $237,600 Maryland $136,800 to $237,600 Massachusetts $136,800 to $237,600 Minnesota $136,800 to $237,600 New York $136,800 to $237,600 New Jersey $136,800 to $237,600 Virginia $136,800 to $237,600 Washington $136,800 to $237,600Requesting 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.
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.
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 $136K-$237K 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, 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 $181,170 based on 12,692 positions with disclosed compensation. Director-level AI roles across all categories have a median of $247,800. Disclosed range: $136K to $237K.
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 AI Hiring
Accenture has 6 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, Research Engineer. Positions span New York, NY, US, Morristown, NJ, US, San Francisco, CA, US. Compensation range: $195K - $338K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.