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About This Role
About Lyra Health
Lyra Health is the leading provider of mental health solutions for employers supporting more than 20 million people globally. The company has delivered 13 million sessions of mental health care, published more than 20 peer\-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness and cost efficiency. Extensive peer\-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life\-changing mental health care through Lyra Empower, the only fully integrated, AI\-powered platform combining the highest\-quality care and technology solutions.
About the Role:
We're looking for a Campaign Manager to execute integrated demand generation programs that drive qualified pipeline across our enterprise and mid\-market segments. You'll sit on the Growth Marketing team, working closely with your manager to shape campaign strategy — then owning execution end\-to\-end across inbound and ABX motions.
This is a role for someone who is energized by building and running programs, is naturally analytical, and takes pride in clean execution and measurable results. You'll partner cross\-functionally with Sales, BDRs, Product Marketing, and Content teams, and you'll be expected to track and report on the performance of everything you run.
This is a backfill for an established seat with active programs. You'll have a strong foundation to build on and the opportunity to make it your own.
Location: US; Remote
### Responsibilities
- Campaign Planning \& Execution:
+ Build and run multi\-channel demand generation campaigns spanning email, paid media, content syndication, webinars, and direct mail
+ Manage the campaign calendar: brief, build, launch, optimize, and report on programs from start to finish
+ Activate campaigns around key moments including Mental Health Awareness Month, our annual State of Workforce Mental Health report, and major industry events
- ABX Support:
+ Execute account\-based campaign plays in coordination with the ABX Manager, using 6sense intent signals to personalize outreach for key segments
+ Build account\-level campaign sequences in Marketo and align with Sales and BDRs on follow\-up timing and handoffs
- Performance Tracking \& Reporting:
+ Track campaign performance in Salesforce — MQL/MQA volume, pipeline sourced, pipeline influenced
+ Maintain campaign dashboards and contribute to weekly, monthly, and QBR reporting with clear, accurate data
+ Conduct post\-campaign analysis and bring forward actionable recommendations to improve results over time
- Cross\-Functional Collaboration:
+ Work with Product Marketing to ensure campaign messaging aligns with positioning and resonates with CHRO, CPO, and Benefits \& Total Rewards audiences
+ Partner with Field Marketing and Events to build campaign activations around events that convert engagement into pipeline
+ Serve as the campaign point of contact for Sales and BDR teams, keeping them informed on active programs and incorporating their feedback on lead quality
- Content \& Asset Coordination:
+ Brief, project\-manage, and QA campaign assets: landing pages, email sequences, paid ad copy, and nurture tracks
+ Help repurpose event and research content into ongoing demand generation programs
### Qualifications
- BA/BS degree or equivalent
- 5\+ years of B2B marketing experience with meaningful exposure to demand generation or campaign execution — you can point to programs you ran and results you drove
- Hands\-on experience with Marketo and Salesforce — you're comfortable building programs and pulling performance data without heavy ops support
- Familiarity with 6sense or Demandbase for intent\-based targeting and account prioritization
- Creative instinct with a performance mindset — you can brief and pressure\-test campaign assets (emails, ads, landing pages) for both message clarity and visual impact, and you know the difference between creative that looks good and creative that converts. Bonus if you can write a compelling subject line or headlines yourself.
- Solid analytical skills — you track what you launch, know what the numbers mean, and can clearly communicate performance to your team and stakeholders
- Strong project management habits — you can manage multiple campaigns at once, hit deadlines, and keep cross\-functional partners aligned
- Clear written communication — you can translate a product message into email copy or ad creative that actually speaks to a buyer
### Preferred Qualifications
- Experience marketing to HR, Benefits, or People Operations audiences
- Familiarity with the employee benefits or HR tech landscape
- Experience in a B2B SaaS or health tech environment
- Exposure to ABX or account\-based campaign tactics
As a full\-time Campaign Manager, Growth Marketing, you will be employed by Lyra Health, Inc. The anticipated annual base salary range for this full\-time position is $106,000 to $146,000\. The base range is determined by role and level, and placement within the range will depend on a number of job\-related factors, including but not limited to your skills, qualifications, experience and location. This role may also be eligible for discretionary bonuses.
Annual salary is only one part of an employee’s total compensation package at Lyra. We also offer generous benefits that include:
- Comprehensive healthcare coverage (including medical, dental, vision, FSA/HSA, life and disability insurances)
- Lyra for Lyrians; coaching and therapy services
- Equity in the company through discretionary restricted stock units
- Competitive time off with pay policies including vacation, sick days, and company holidays
- Paid parental leave
- 401K retirement benefits
- Monthly tech allowance
- We like to spread joy throughout the year with well\-being perks and activities, surprise swag, regular community celebration…and more!
We can’t wait to meet you.
"We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.
By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra. We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR. Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives. If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form. This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice."
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, summarizing interviews, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $106K-$146K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Lyra Health, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($126K) sits 25% below the category median. Disclosed range: $106K to $146K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Lyra Health AI Hiring
Lyra Health has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $146K - $146K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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