Interested in this AI/ML Engineer role at AVEVA?
Apply Now →Skills & Technologies
About This Role
AVEVA is creating software trusted by over 90% of leading industrial companies.
Salary Range:
$73,800.00 - $123,200.00This pay range represents the minimum and maximum compensation that the position offers, and final compensation can vary within the range depending on work location, job experience, skills, and relevant educational attainment and/or training.
Position: Software Developer Graduate (AI Proficient)
Employment type: Full-time
Location:Lake Forest/ San Leandro/ Scottsdale/ Philadelphia
Work Type: Hybrid (3 days a week in office)
Work Authorization: This application is intended for candidates that are eligible for full-time work authorization in the United States upon completing their education.
Please be prepared to answer the following in your application:
- Do you now, or will you in the future, require sponsorship for employment visa status (**e.g. F1, J1, H-1B, CPT, OPT visa status, etc.) to work legally in the United States?
Position Overview:
As a Software Developer Graduate at AVEVA, you step into a full-time, production-grade role from day one — shipping real software for the industrial enterprises that keep the world running. What sets this role apart is how you'll build: leveraging the latest agentic coding tools, from intelligent code generation and AI-assisted debugging to autonomous workflows that accelerate every stage of the development lifecycle. This isn't about occasionally using a tool — it's about engineering with an AI-proficient mindset as a core part of how great software gets made. With AI and cloud at the center of our strategy and a global portfolio of 75+ products, this is where a sharp, self-directed graduate grows into an engineer who doesn't just keep pace with the future of software development, but helps define it.
Key Responsibilities:
- Recognize, articulate, and make technical decisions / trade-offs around multiple dimensions (scaling, reliability, performance, maintenance, etc.) that have an impact on your team
- Design, develop, test, and debug software applications
- Deliver software on-time and constantly work to make accurate estimates and deliver on those estimates
- Provide technical support of products including direct customer support and escalated issues
- Document product behavior and implementation details
- Collaborate with team members on how to approach and prioritize development efforts
- Understand and proactively follow team processes, documentation, best practices, and code style guides
- Give insightful feedback on pull requests, engineering designs, and features
- Expand your working knowledge of your respective technical domain Desired Skills and Knowledge:
- A Bachelor's Degree, Master's Degree Computer Science, Computer Engineering or a related field graduating with a GPA of 3.0 or above
- Software product or application development experience
- Familiarity with agentic engineering tools and coding assistants such as GitHub Copilot, Claude Code, Cursor, or similar development harnesses.
- Introductory understanding of how agents and skills work, including when to apply them effectively in software development workflows.
- A curious, self-directed mindset with the confidence to explore new tools, experiment independently, and learn through hands-on discovery.
- Good experience with developing software in major programming languages such as: C++, C#/.NET, JavaScript, etc.
- Familiarity with software design patterns (objected oriented design), Computer Science fundamentals/principles and methodologies, as well as knowledge of operating system internals
- Sharp debugging and problem-solving skills
- Excellent written and verbal communication skills.
- An eagerness to accept and expand upon skills and knowledge based on feedback
- Someone who seeks advice on how to approach and prioritize development efforts
- A self-motivated person with excellent time management skills USA Benefits include:
Flex work hours, 20 days PTO rising to 25 with service, three paid volunteering days, primary and secondary parental leave, well-being support, medical, dental, vision, and 401K.
It’s possible we’re hiring for this position in multiple countries, in which case the above benefits apply to the primary location. Specific benefits vary by country, but our packages are similarly comprehensive.
Find out more: aveva.com/en/about/careers/benefits/
Hybrid working
We work in a hybrid way at AVEVA. Most roles are based at a local AVEVA office, with an expectation of being on-site 50% of your working hours to support collaboration and connection. Some positions are fully office-based depending on the nature of the work, and certain roles that support specific customers or markets may be remote. The working arrangement for this position will be confirmed during the hiring process.
Hiring process
Interested? Great! Get started by submitting your cover letter and CV through our application portal. AVEVA is committed to recruiting and retaining people with disabilities. Please let us know in advance if you need reasonable support during your application process.
Find out more: aveva.com/en/about/careers/hiring-process
About AVEVA
AVEVA is a global leader in industrial software with more than 6,500 employees in over 40 countries. Our cutting-edge solutions are used by thousands of enterprises to deliver the essentials of life – such as energy, infrastructure, chemicals, and minerals – safely, efficiently, and more sustainably.
We are committed to embedding sustainability and inclusion into our operations, our culture, and our core business strategy. Learn more about how we are progressing against our ambitious 2030 targets: sustainability-report.aveva.com/
Find out more: aveva.com/en/about/careers/
AVEVA requires all successful applicants to undergo and pass a drug screening and comprehensive background check before they start employment. Background checks will be conducted in accordance with local laws and may, subject to those laws, include proof of educational attainment, employment history verification, proof of work authorization, criminal records, identity verification, credit check. Certain positions dealing with sensitive and/or third-party personal data may involve additional background check criteria.
AVEVA is an Equal Opportunity Employer. We are committed to being an exemplary employer with an inclusive culture, developing a workplace environment where all our employees are treated with dignity and respect. We value diversity and the expertise that people from different backgrounds bring to our business. AVEVA provides reasonable accommodation to applicants with disabilities where appropriate. If you need reasonable accommodation for any part of the application and hiring process, please notify your recruiter. Determinations on requests for reasonable accommodation will be made on a case-by-case basis.
Salary Context
This $73K-$123K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At AVEVA, 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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($98K) sits 54% below the category median. Disclosed range: $73K to $123K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
AVEVA AI Hiring
AVEVA has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Lake Forest, CA, US. Compensation range: $123K - $123K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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.