Interested in this AI/ML Engineer role at Transamerica?
Apply Now →Skills & Technologies
About This Role
Job Family
IT \- GeneralAbout Us
At Transamerica, hard work, innovative thinking, and personal accountability are qualities we honor and reward. We understand the potential of leveraging the talents of a diverse workforce. We embrace an environment where employees enjoy a balance between their careers, families, communities, and personal interests.
Ultimately, we appreciate the uniqueness of a company where talented professionals work collaboratively in a positive environment — one focused on helping people look forward and plan for the best life possible while providing tools and solutions that make it easier to get there.
Who We Are
We believe everyone deserves to live their best life. More than a century ago, we were among the first financial services companies in America to serve everyday people from all walks of life.
Today, we’re part of an international holding company, with millions of customers and thousands of employees worldwide. Our insurance, retirement, and investment solutions help people make the most of what’s important to them.
We’re empowered by a vast agent network covering North America, with diversity to match. Together with our nonprofit research institute and foundation, we tune in, step up, and are a force for good — for our customers and the communities where we live, work, and play. United in our purpose, we help people create the financial freedom to live life on their terms.
What We Do
Transamerica is organized into three distinct businesses. These include 1\) World Financial Group, including Transamerica Financial Advisors, 2\) Protection Solutions and Savings \& Investments, comprised of life insurance, annuities, employee benefits, retirement plans, and Transamerica Investment Solutions, and 3\) Financial Assets, which includes legacy blocks of long term care, universal life, and variable and fixed annuities. These are supported by Transamerica Corporate, which includes Finance, People and Places, General Counsel, Risk, Internal Audit, Strategy and Development, and Corporate Affairs, which covers Communications, Brand, and Government and Policy Affairs.
Transamerica employs nearly 7,000 people. It’s part of Aegon, an integrated, diversified, international financial services group serving approximately 23\.9 million customers worldwide.\* For more information, visit transamerica.com.
Job Description Summary
Aegon’s Core AI Team is driving AI\-driven transformation across our global business. Building on recent successes – including the launch of a vendor\-agnostic enterprise LLM gateway (AWS Launchpad), we are now investing in next\-generation Gen AI and Agentic AI capabilities. This role will help evolve the organizations AI platform and operational services, develop and mature AI operations and customer support processes, drive and support AI Platform adoption, and provide AI expertise to accelerate developer onboarding and enablement.Job Description
Responsibilities
- Assist in monitoring and maintaining AI platform services and applications.
- Support troubleshooting efforts for basic platform, service, or integration issues under guidance from more experienced team members.
- Help maintain and update documentation, user guides, onboarding materials, and internal knowledge content.
- Contribute to testing, debugging, validation, and basic operational support for AI platform features and updates.
- Assist with CI/CD pipeline tasks, deployment support activities, and automation efforts as assigned.
- Collaborate with team members to support platform onboarding and developer enablement activities.
- Learn and apply AI engineering, cloud, support, and DevOps best practices in day\-to\-day work.
- Track basic operational issues and help document resolutions and support procedures.
- Provide responsive support for routine developer questions and escalate complex issues appropriately.
- Participate in team learning, knowledge sharing, and continuous improvement efforts.
Qualifications
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline; equivalent internship or academic p project experience may also be considered
- Minimal to 2 years of relevant experience, including internships, co\-ops, research, or academic projects
- Basic knowledge of Python or another modern programming language
- Foundational understanding of cloud concepts, preferably AWS
- Exposure to AI/ML or Generative AI concepts through coursework, personal projects, research, or internships
- Basic understanding of software development lifecycle concepts, version control, and testing practices
- Strong analytical thinking, curiosity, and eagerness to learn new technologies and tools
- Good written and verbal communication skills and ability to work effectively in a team environment
Preferred Qualifications
- Internship or academic experience with AI, machine learning, software engineering, or platform support
- Exposure to Git, APIs, microservices, or automation tools
- Interest in cloud engineering, AI platforms, or developer enablement
Working Conditions
- This is a hybrid position requiring three days in office per week in Denver, CO.
- Some work outside of normal business hours may be required due to global nature of business
- Moderate travel (10\-25%)
- Travel for internal meetings as needed
Compensation
The Salary for this position generally ranges between $76,000\-97,000 annually. *Please note that the salary range is a good faith estimate for this position and actual starting pay is determined by several factors including* qualifications, experience, geography, work location designation (in\-office, hybrid, remote) and operational needs. Salary may vary above and below the stated amounts, as permitted by applicable law.
Additionally, this position is typically eligible for an Annual Bonus based on the Company Bonus Plan/Individual Performance and is at the Company’s discretion.
Applicants must possess legal authorization to work for our company in the U.S. without the need for immigration, sponsorship or otherwise serving as an employer of record for immigration employment purposes.
At this time, this role is not eligible for immigration\-related employment authorization sponsorship.
This is a hybrid position requiring three days in office per week in one of our hub location, Denver. Relocation assistance will not be provided for this position.
What We Offer
For eligible employees, we offer a comprehensive benefits package designed to support both the personal and financial well\-being of our employees.
Compensation Benefits
- Competitive Pay
- Bonus for Eligible Employees
Benefits Package
- Pension Plan
- 401k Match
- Employee Stock Purchase Plan
- Tuition Reimbursement
- Disability Insurance
- Medical Insurance
- Dental Insurance
- Vision Insurance
- Employee Discounts
- Career Training \& Development Opportunities
Health and Work/Life Balance Benefits
- Paid Time Off starting at 160 hours annually for employees in their first year of service.
- Ten (10\) paid holidays per year (typically mirroring the New York Stock Exchange (NYSE) holidays).
- Be Well Company holistic wellness program, which includes Wellness Coaching and Reward Dollars
- Parental Leave – fifteen (15\) days of paid parental leave per calendar year to eligible employees with at least one year of service at the time of birth, placement of an adopted child, or placement of a foster care child.
- Adoption Assistance
- Employee Assistance Program
- Back\-Up Care Program
- PTO for Volunteer Hours
- Employee Matching Gifts Program
- Employee Resource Groups
- Inclusion and Diversity Programs
- Employee Recognition Program
- Referral Bonus Programs
Inclusion \& Diversity
We believe our commitment to diversity and inclusion creates a work environment filled with exceptional individuals. We’re thrilled to have been recognized for our efforts through the Human Rights Campaign Corporate Equality Index, Dave Thomas Adoption Friendly Advocate, and several Seramount lists, including the Inclusion Index, 100 Best Companies for Working Parents, Best Companies for Dads, and Top 75 Companies for Executive Women.
To foster a culture of inclusivity throughout our workforce, workplace, and marketplace, Transamerica offers a wide range of diversity and inclusion programs. This includes our company\-sponsored, employee\-driven Employee Resource Groups (ERGs), which are formed around a shared interest or a common characteristic of diversity. ERGs are open to all employees. They provide a supportive environment to help us better appreciate our similarities and differences and understand how they benefit us all.
Giving Back
We believe our responsibilities extend beyond our corporate walls. That's why we created the Aegon Transamerica Foundation in 1994\. Through a mix of financial grants and the volunteer efforts of our employees, the foundation supports nonprofit organizations focused on the things that matter most to our people in the communities where we live and work.
Transamerica’s Parent Company
Aegon acquired the Transamerica business in 1999\. Since its start in 1844, Aegon has grown into an international company serving more than 23\.9 million people across the globe.\* It offers investment, protection, and retirement solutions, always with a clear purpose: Helping people live their best lives. As a leading global investor and employer, the company seeks to have a positive impact by addressing critical environmental and societal issues, with a focus on climate change and inclusion and diversity.
- As of December 31, 2023
Salary Context
This $76K-$97K range is in the lower quartile 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 Transamerica, 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. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($86K) sits 52% below the category median. Disclosed range: $76K to $97K.
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.
Transamerica AI Hiring
Transamerica has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Denver, CO, US. Compensation range: $97K - $97K.
Location Context
AI roles in Denver pay a median of $184,000 across 159 tracked positions. That's 8% below the national 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.