Interested in this AI/ML Engineer role at BambooHR?
Apply Now →About This Role
Work Mode: Please Note: This is a Utah-based hybrid position which will require some regular in-office days each week. Additionally, employment with BambooHR is contingent on passing both a background and credit check.
AI at BambooHR
At BambooHR, we're all about setting people free to do great work, and we believe AI is a powerful partner in that mission. We're leaning into intelligent tools to streamline our workflows, giving us more time for high-impact innovation. We look for curious, forward-thinking people who are ready to explore how AI can elevate their work and help us reimagine the future of HR.
Essential Job Duties
At BambooHR, we believe doing great work starts with having a great quality of life. That's why we're committed to creating an environment where our employees can thrive both professionally and personally.
As BambooHR continues to grow and innovate, we're expanding our focus on privacy, data protection, and responsible AI practices. We're looking for an Associate Legal Counsel who is passionate about helping organizations navigate evolving regulatory requirements while building practical, scalable programs.
In this role, you'll report to the Associate General Counsel, Privacy, AI, and Digital Governance and partner closely with cross-functional stakeholders to support BambooHR's privacy and AI governance initiatives. You'll help translate legal and regulatory requirements into actionable business practices, contribute to innovative solutions and support the development of policies, processes, and controls that promote trust, transparency, and responsible innovation.
You will:
- Partner with and support the Associate General Counsel, Privacy, AI, and Digital Governance in executing legal, operational, and transactional program activities that advance a regulator-ready privacy and AI governance program.
- Manage annual updates to privacy program documentation, including privacy notices, customer contract addendums, policies, and other templates. ensuring materials remain current, accurate, and audit-ready.
- Manage legal review and escalations for privacy and AI rights requests and support day-to-day adherence to applicable privacy regulations, maintaining organized and defensible records of program activities.
- Work with cross-functional stakeholders throughout BambooHR on a variety of AI, privacy and data protection matters — including incident response, risk assessments, and control gap remediation — with clear escalation to the AGC on matters with significant legal exposure or strategic implications.
- Support privacy program operations related to marketing technologies, website operations, cookie consent management, and data collection practices, balancing business enablement with regulatory defensibility.
- Assist AGC in identifying and addressing privacy and AI-related legal considerations, serving as a practical and solutions-oriented resource that enables BambooHR's AI-first objectives while building the governance guardrails needed to sustain them.
- Support adherence with GDPR, CCPA/CPRA, emerging U.S. state privacy laws, and evolving AI regulatory frameworks, proactively monitoring developments and flagging material changes that warrant AGC attention or program-level updates.
- Assist with conducting privacy and AI impact assessments and assist with risk evaluation and mitigation efforts, exercising sound judgment about when to escalate issues, propose alternatives, or seek direction from the AGC before proceeding.
- Monitor legal and regulatory developments related to privacy, data protection, and artificial intelligence, and provide practical guidance to internal stakeholders.
What You Need to Get the Job Done
- Juris Doctor (J.D.) degree or equivalent legal experience.
- 3–5 years of experience supporting privacy, data protection, AI governance, , cybersecurity or technology-related functions.
- Working knowledge of privacy laws and regulations, including GDPR, CCPA/CPRA, HIPAA, GLBA, and other emerging privacy requirements.
- A strong interest in AI governance, AI risk management, or emerging AI regulatory frameworks.
- Ability to interpret legal and regulatory requirements and translate them into practical business solutions.
- Strong project management and organizational skills with the ability to manage multiple priorities simultaneously.
- Excellent written and verbal communication skills.
- Strong attention to detail and analytical problem-solving abilities.
- Collaborative mindset and ability to work effectively across multiple business functions.
What Will Make Us REALLY Love You
- Experience supporting privacy programs within a SaaS or high-growth technology company.
- Experience conducting privacy impact assessments, AI risk assessments, or vendor reviews.
- Experience managing transactional privacy operations such as policy development, training, incident response, vendor risk management, and appropriate data use.
- Familiarity with AI governance frameworks such as the NIST AI Risk Management Framework, ISO standards, or emerging AI regulations.
- Experience partnering with cross-functional teams, such as Legal, Security, Risk, Security, and Product teams to operationalize regulatory requirements.
- In-house experience supporting privacy, security, or responsible AI initiatives.
- Passion for helping organizations build trustworthy, and responsible technology and governance practices
What You'll Love About Us
- A Great Company Culture that has been recognized by multiple organizations like Inc, and Salt Lake Tribune
- Comprehensive health, life, and disability insurance
- Generous leave policies that include 4 weeks of vacation, 12 company holidays, parental leave, and volunteer time off so you can enjoy quality of life
- 401k plans with up to 6% company match
- $2000 Paid-Paid Vacation bonus
- EAP through Headspace
- Check out all our benefits that benefit you
About Us
At BambooHR, we're building something different: we're building a people intelligence platform that transforms HR and sets people free to do great work! We're a proven market leader driving innovation while building lasting success through thoughtful, sustainable growth. Here, you'll find a place that champions growth: both professional and personal, both individual and collective.
We invest in potential, giving you the space to stretch your capabilities and turn good ideas into reality while providing the safety net of a supportive, values-driven culture. Our approach combines meaningful work with meaningful lives, offering competitive benefits, professional development, and the flexibility to thrive both in and outside the office.
What sets us apart isn't just what we do, but how we do it: with openness, integrity, and a shared commitment to doing the right thing. Join us in creating HR software that makes work better for everyone, while we make work better for you.
BambooHR is committed to the full inclusion of all qualified individuals and will ensure that persons with disabilities are provided reasonable accommodations throughout the hiring process. If you would like to request accommodations, please let your recruiter know.
BambooHR is An Equal Opportunity Employer-M/F/D/V
Because our team members are trusted to handle sensitive information, we require all candidates that receive and accept employment offers to complete a background check before being hired.
For information on California Privacy Policy, click here*.*
Our process utilizes AI as an assistant to efficiently process and analyze candidate data. Recruiters and hiring managers maintain full oversight and accountability, ensuring that all final selection and rejection decisions are human-made and based solely on objective job qualifications. Please see our General Privacy Notice and California Privacy Notice for more details.
See our AI Guidelines for Candidates for details on how BambooHR uses AI in recruiting, how we expect candidates to use AI, and what is not allowed.
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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At BambooHR, 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 $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
BambooHR AI Hiring
BambooHR has 4 open AI roles right now. They're hiring across AI/ML Engineer. Based in Draper, UT, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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.