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About This Role
Why choose us?
Are you ready to take the next step in your career? Join us for an exciting opportunity at Albertsons Companies, where innovation and customer service go hand\-in\-hand!
At Albertsons Companies, we are looking for someone who’s not just seeking a job, but someone who wants to make an impact. In this role, you’ll have the opportunity to lead, innovate, and contribute to the growth of a company that values great service and lasting customer relationships. This position offers the chance to work in a fast\-paced, dynamic environment that’s constantly evolving.
Bring your flavor
Building the future of food and well\-being starts with you. Join our team and bring your best self to the table.
What you will be doing
The AI Incubation team sits within the Data \& AI organization and helps identify, shape, and accelerate high\-value AI opportunities across the business. This includes advancing Albertsons’ Four Big Bets in AI: digital customer experience, merchandising intelligence, empowering associates and leaders, and end\-to\-end supply chain optimization.
The AI Incubation team has an opening for a Sr. Staff Engineer – AI (AI Incubation). This position is located in Pleasanton, California.
Position Purpose
The Sr. Staff Engineer – AI (AI Incubation) will partner with business, product, and technology leaders to identify, shape, and accelerate high\-value AI opportunities across the enterprise. This is a senior role for a leader who can move fluidly from problem framing to solution design, from stakeholder alignment to execution planning, and from incubation to enterprise scale.
Success in this role will come from the ability to convert ambiguity into clear priorities, credible solution paths, and measurable business outcomes. The role will help connect incubation priorities to Albertsons’ Four Big Bets in AI and improve the quality and speed with which ideas move from concept to deployment.
Why this role matters?
This role sits at the front end of Albertsons’ AI transformation, where enterprise priorities are translated into practical solutions with scale potential. It offers direct exposure to senior stakeholders, high\-value problem spaces, and the opportunity to shape how AI is deployed across one of the largest grocery and pharmacy retailers in the U.S.
Main responsibilities:
- Partner with senior leaders to identify, prioritize, and frame high\-value AI opportunities tied to enterprise strategy and measurable outcomes.
- Build trusted relationships across business, product, and technology teams to strengthen the AI incubation funnel and improve cross\-functional alignment.
- Translate ambiguous business problems into clear problem statements, solution hypotheses, business cases, and roadmaps.
- Orchestrate cross\-functional teams across product, engineering, data, architecture, security, and platform functions from discovery through pilot and production readiness.
- Shape AI initiatives across customer, merchandising, marketing, loyalty, operations, supply chain, pharmacy, and corporate domains.
- Design enterprise\-scale AI solution architectures spanning Data, ML, Foundation Models, RAG, Agentic Systems, AI Platforms, and enterprise integrations, with robust governance and production readiness.
- Build prototypes and evaluate emerging AI capabilities, including foundation models, prompting strategies, retrieval architectures, and agent orchestration patterns to accelerate production adoption.
- Establish reusable AI reference architectures, engineering standards, and solution accelerators that enable scalable, secure, and cost\-effective AI adoption across the enterprise.
- Establish success metrics, experimentation plans, and adoption pathways that improve speed\-to\-decision and value realization.
- Accelerate initiatives from concept to pilot or production\-ready design while improving the quality of governance, evaluation, and handoff into enterprise deployment.
- Provide technical leadership and mentorship across engineering, platform, and data science teams, influencing architecture and engineering decisions through deep technical expertise.
- Drive technical excellence by defining best practices for AI evaluation, observability, governance, performance, safety, and operational optimization.
We are looking for candidates who possess the following:
- Bachelor’s or master’s degree in computer science, Engineering, Data Science, Analytics, or a related field.
- 10 plus years of relevant experience in AI\-led transformation, AI solutions consulting, product strategy, enterprise architecture, or related roles.
- Demonstrated ability to move from executive\-level ambiguity to clear hypotheses, product prototypes, decision points, and action plans.
- Strong executive communication and stakeholder leadership skills, with the ability to influence across business, product, and technology teams.
- Demonstrated expertise designing and deploying production\-scale AI systems across multiple enterprise AI layers including Machine Learning, Foundation Models, Retrieval\-Augmented Generation (RAG), Agentic Systems, and AI Platforms, with Data Engineering serving as the foundational competency.
- Experience building enterprise\-grade AI applications using modern AI frameworks such as LangChain, Semantic Kernel, LlamaIndex, LangGraph, or equivalent technologies.
- Demonstrated ability to establish reusable engineering patterns, technical standards, and enterprise AI best practices.
- Ability to operate effectively in fast\-moving environments where priorities evolve and clarity must be created.
Preferred Background
- Experience in AI transformation, innovation, incubation, internal strategy, solutions consulting, product leadership, or enterprise architecture within large enterprises, with exposure on AI, Enterprise GenAI, AI Agents, Multi\-agent systems, AI Platform Engineering, Model Evaluation, AI Governance, LLMOps, MLOps, Vector Databases \& Enterprise AI Security
- Experience in or exposure to retail, grocery, ecommerce, loyalty, merchandising, supply chain, or pharmacy environments.
- Background from top\-tier consulting firms, Fortune 100\-scale retailers, hyperscaler AI/solutions organizations, or high\-growth AI companies is a plus.
- Familiarity with responsible AI, privacy, security, and risk considerations in enterprise or customer\-facing deployments.
We also provide a variety of benefits including:
- Competitive wages paid weekly
· Access to up to 50% of your earned wages before payday, via our partnership with Stream
- Associate discounts
- Health and financial well\-being benefits for eligible associates (Medical, Dental, 401k and more!)
- Time off (vacation, holidays, sick pay). For eligibility requirements please visit myACI Benefits
- Leaders invested in your training, career growth and development
- An inclusive work environment with talented colleagues who reflect the communities we serve
Our Values – Click below to view video: ACI Values
*A copy of the full job description can be made available to you.*
\#LI\-MF1
Pay Transparency:
Starting rates will be no less than the local minimum wage and may vary based on criteria such as location, experience, and qualifications. Candidates with unique qualifications may be considered for compensation above this range. Benefits may include medical, dental, vision, disability and life insurance, sick pay, PTO/Vacation Pay or Flexible Time Off, paid holidays, bereavement pay, and retirement benefits (pension and/or 401k eligibility). \[If applicable:] Associates in this position may be eligible for a quarterly bonus.
Albertsons Companies is at the forefront of the revolution in retail. Committed to innovation and fostering a culture of belonging, our team is united with a unique purpose: to bring people together around the joys of food and to inspire well\-being. We want talented individuals to be part of this journey!
Locally great and nationally strong, Albertsons Companies (NYSE: ACI) is a leading food and drug retailer in the U.S. We operate over 2,200 stores, 1,732 pharmacies, 405 fuel centers, 22 distribution facilities, and 19 manufacturing plants across 34 states and the District of Columbia. Our well\-known banners include Albertsons, Safeway, Vons, Jewel\-Osco, ACME, Shaw’s, Tom Thumb, United Supermarkets, United Express, Randalls, Albertson’s Market, Pavilions, Star Markets, Market Street, Carrs, Haggen, Lucky, Amigos, Andronico’s Community Markets, King’s, Balducci’s, and Albertson’s Market Street.
Our vision is to be a retail leader admired for national strength with deep local roots, offering an easy, fun, friendly, and inspiring experience, no matter how customers choose to shop with us. We celebrate the rich diversity of the communities we serve, and strive to create a workplace where everyone has equal access to opportunities and resources, and can fully contribute to their and our company’s success.
Bring your flavor
Building the future of food and well\-being starts with you. Join our team and bring your best self to the table.
Disclaimer
The above statements are intended to describe the general nature of work performed by the employees assigned to this job and are not the official job description for the position. All employees must comply with Company, Division, and Store policies and applicable laws. The responsibilities, duties, and skills of personnel may vary within store and/or from store to store and the official job description will be provided during the application process.
Albertsons is an Equal Opportunity Employer
This Company is an Equal Opportunity Employer, and does not discriminate on the basis of race, gender, ethnicity, religion, national origin, age, disability, veteran status, gender identity/expression, sexual orientation, or on any other basis prohibited by law. Consistent with applicable state and local law, the Company will consider for employment qualified applicants with arrest and conviction records.
We endeavor to make this site accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at 1\-888\-255\-2269(option \#4\).
Salary Context
This $144K-$188K range is below the median 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 Albertsons, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($166K) sits 23% below the category median. Disclosed range: $144K to $188K.
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.
Albertsons AI Hiring
Albertsons has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Pleasanton, CA, US. Compensation range: $188K - $188K.
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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