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About This Role
As the recognized global standard for project\-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values\-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one\-of\-a\-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com
Business Summary
The Deltek Global Cloud team focuses on the delivery of first\-class services and solutions for our customers. We are an innovative and dynamic team that is passionate about transforming the Deltek cloud services that power our customers' project success. Our diverse, global team works cross\-functionally to make an impact on the business. If you want to work in a transformational environment, where education and training are encouraged, consider Deltek as the next step in your career!
Position Responsibilities
The Associate Cloud AI Engineer will be a key contributor within the Cloud Architecture team, supporting the design, development, and integration of AI\-powered solutions across the Cloud, Engineering, and Product organizations. This role is central to our strategic initiative to embed Agentic AI capabilities into cloud operations, enabling intelligent automation, self\-healing infrastructure, and next\-generation cloud services. The ideal candidate combines strong software development skills with a systems\-thinking mindset and a foundational understanding of cloud platforms and operations
Key Responsibilities* Assist in designing, developing, and deploying AI/ML solutions that integrate with cloud infrastructure and services, with a focus on Agentic AI frameworks.
- Collaborate with cross\-functional teams across Cloud Architecture, Engineering, and Product to identify automation opportunities and implement AI\-driven workflows.
- Contribute to building and maintaining AI agents that can autonomously monitor, diagnose, and remediate cloud infrastructure issues.
- Develop and optimize APIs, microservices, and data pipelines that power AI capabilities within cloud environments.
- Support the evaluation and integration of foundational AI models (LLMs, multi\-agent systems) into existing cloud platforms and toolchains.
- Participate in architectural reviews and provide input on AI solution design patterns, scalability, and reliability.
- Write clean, well\-documented, and testable code following software engineering best practices.
- Stay current with emerging trends in Agentic AI, cloud\-native technologies, and DevOps/SRE practices.
- Contribute to internal knowledge sharing, documentation, and proof\-of\-concept demonstrations.
Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field.
- US Citizenship is required for this position.
- 1–3 years of professional experience in software development, cloud engineering, or AI/ML engineering.
- Proficiency in one or more programming languages: Python, Go, Java, or TypeScript.
- Foundational knowledge of cloud platforms (AWS, Azure, or OCI) including compute, networking, storage, and managed AI/ML services.
- Understanding of AI/ML concepts including LLMs, prompt engineering, retrieval\-augmented generation (RAG), and agent\-based architectures.
- Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
- Strong analytical and problem\-solving skills with a systems\-thinking approach.
- Excellent communication and collaboration skills; ability to work in cross\-functional, geographically distributed teams.
Career Interests
Engineering
Compensation Info
The U.S. salary range for this position is $53,000\.00\-$93,250\.00\. This range is subject to change as Deltek takes a number of factors into consideration when determining individual base pay, such as location, job\-related knowledge, skills and experience. Certain roles are eligible for additional rewards, including incentive compensation and equity.
Benefits and perks listed here may vary depending on the nature of employment with Deltek. Employees have access to healthcare benefits, a 401(k) plan and company match, paid vacation time and holidays, well\-living programs, short\-term and long\-term disability coverage, basic life insurance and tuition reimbursement.
Position Type
FT
Travel Requirements
10%
Compliance Requirements
Certain roles may have additional privacy, security and compliance requirements to the extent they support Costpoint GCCM or similar product offerings.
EEO Statement
*Deltek, Inc. is an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status.*
E\-Verify Statement
Deltek, Inc., utilizes the E\-Verify program with every potential new hire. This makes it possible for us to make certain that every employee who works for Deltek is eligible to work in the United States. To learn more about E\-Verify you can call 1\-800\-255\-7688 or visit their website by clicking the logo below. E\-Verify® is a registered trademark of the United States Department of Homeland Security.
Applicant Privacy Notice
*Deltek is committed to the protection and promotion of your privacy. In connection with your application for employment with us at Deltek, it is necessary for us to collect, store and use information about you (“Personal Data”) to administer and evaluate your application. We are the “controller” of the Personal Data you provide us and will process any such Personal Data in accordance with applicable law and the statements contained in this* Employment Candidate Privacy Notice*. Additionally, we have not sold and do not sell Personal Data you provide to us through the job application process.*
Job Expires
02\-Jun\-2027
Salary Context
This $53K-$93K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $181K across 1996 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 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Deltek, 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 $178,940 based on 11,900 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $97,380. This role's midpoint ($73K) sits 59% below the category median. Disclosed range: $53K to $93K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Deltek AI Hiring
Deltek has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $93K - $93K.
Remote Work Context
Remote AI roles pay a median of $169,035 across 1,817 positions. About 16% 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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