Interested in this AI/ML Engineer role at Conagra Brands?
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Location
Omaha, Nebraska, United States of America
Category
IT \& Business Services
Job Id
Req\-038431
Job Type
Full time
Office
Conagra Brands is seeking a Data Principal to lead the strategy and delivery of data, analytics, automation, and AI capabilities across critical business areas. In this role, you will partner closely with senior business and technology leaders to translate strategic priorities into scalable solutions that improve decision\-making, operational performance, and innovation.
Reporting to the VP, Information Technology, you will own a portfolio of data, automation, and AI initiatives, including strategy, roadmap, prioritization, and value realization. You will play a highly visible role in advancing enterprise data capabilities by connecting business needs with modern platforms and driving solutions that deliver measurable outcomes.
This role is ideal for a leader who can combine business partnership, portfolio ownership, and technical direction to turn enterprise data strategy into practical, high\-impact execution at scale.
What You Will Do
- Define and lead the data, analytics, automation, and AI strategy for assigned business areas, aligned to enterprise priorities and measurable outcomes
- Partner with senior business and functional leaders to shape priorities, align investments, and ensure solutions support business needs
- Own and lead a portfolio of initiatives, including roadmap development, investment prioritization, and value realization
- Deliver measurable business impact by connecting data, analytics, and automation to core business processes and decisions
- Identify and address data and process gaps that limit speed, visibility, or effectiveness
- Balance speed, scalability, and long\-term sustainability to maximize value delivery
- Lead end\-to\-end delivery of data products, automation solutions, and AI capabilities
- Establish clear ownership and accountability across product lifecycle, prioritization, and outcomes
- Oversee roadmap execution, cross\-team dependencies, and alignment with enterprise initiatives
- Provide technical leadership across data engineering, analytics, and AI enablement
- Establish standards for data quality, governance, security, and responsible AI
- Build and lead a high\-performing team of data, engineering, and solution professionals
- Foster a culture of accountability, collaboration, and continuous improvement
- Communicate progress, risks, and outcomes to senior business and technology leadership
- Manage external vendors and ensure compliance with governance and regulatory requirements
What You Will Bring
- Bachelor’s degree in computer science, information systems, engineering, or a related field; advanced degree preferred
- 12\+ years of experience in data, analytics, automation, or related technology domains
- 5\+ years of experience leading teams and delivering enterprise\-scale initiatives
- Proven track record of driving data, analytics, or AI solutions in complex, matrixed organizations
- Strong business acumen across functions such as Sales, Supply Chain, R\&D, or Operations
- Experience translating business needs into technology solutions and delivering measurable outcomes
- Hands\-on experience with modern cloud data platforms such as Snowflake, Databricks, or similar technologies
- Familiarity with enterprise systems such as SAP and related platforms
- Strong understanding of data governance, data quality, security, and responsible AI practices
- Experience managing budgets, vendors, and large\-scale portfolios
- Strong communication skills, with the ability to clearly articulate technical concepts, tradeoffs, and business value
- Demonstrated ability to lead teams, build relationships, and drive results through collaboration and influence
Compensation
Pay Range:$135,000\-$200,000*The annual salary listed above is the expected offering for this position. An employee’s actual annual salary will be based on but not limited to: location, relevant experience/level and skillset, while balancing internal Conagra employees’ equity. Conagra Brands will comply with applicable law regarding minimum salaries for exempt employees.*
Our Benefits
We care about your total well\-being and will support you with the following, subject to your location and role:
- Health: Comprehensive healthcare plans, wellness incentive program, mental wellbeing support and fitness reimbursement
- Wealth: Great pay, bonus incentive opportunity, matching 401(k) and stock purchase plan
- Growth: Career development opportunities, employee resource groups, on\-demand learning and tuition reimbursement
- Balance: Paid\-time off, parental leave, flexible work\-schedules (subject to your location and role) and volunteer opportunities
Our Company
At Conagra Brands, we have a rich heritage of making great food. We aspire to have the most impactful, energized and inclusive culture in food. As a member of our 18,000\+ person team across 40\+ locations, you are empowered to reach your potential, make an impact and own your career. We're in the business of building champions – within our people and our iconic brands like Birds Eye®, Slim Jim® and Reddi\-Wip®.
Our focus on innovation extends beyond making great food, it also reflects our commitment to embracing new solutions that positively impact our team, the communities we serve and the health of our planet. Foodies Welcome.
Conagra Brands is an equal opportunity employer and considers qualified applicants for employment without regard to sex, race, color, religion, ethnic or national origin, gender, sexual orientation, gender identity or expression, age, pregnancy, leave status, disability, veteran status, genetic information and/or any other characteristic or status protected by national, federal, state or local law. Reasonable accommodation may be made upon request.
Salary Context
This $135K-$200K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1889 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 3,736 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Conagra Brands, 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 $181,357 based on 12,694 positions with disclosed compensation. Director-level AI roles across all categories have a median of $248,100. This role's midpoint ($167K) sits 8% below the category median. Disclosed range: $135K to $200K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,650. 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: $248,100; VP: $250,000.
Conagra Brands AI Hiring
Conagra Brands has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Omaha, NE, US. Compensation range: $200K - $200K.
Location Context
Across all AI roles, 15% (562 positions) offer remote work, while 3,158 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 3,736 open positions tracked in our dataset. By seniority: 109 entry-level, 1,755 mid-level, 1,486 senior, and 386 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (562 positions). The remaining 3,158 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,650. 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 3,736 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,564), Data Scientist (311), AI Software Engineer (277). 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 (109) are outnumbered by mid-level (1,755) and senior (1,486) 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 386 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (562 positions), with 3,158 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 $253,650, 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 (1,942 postings), Aws (1,175 postings), Azure (881 postings), Rag (827 postings), Gcp (718 postings), Prompt Engineering (590 postings), Pytorch (586 postings), Claude (528 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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