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About This Role
Inovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data\-driven solutions. And the momentum is building.
Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare's greatest needs. Through our mission\-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve.
\*\*\*\* Must be local to Atlanta, Nashville, Chicago or Boston
Overview: The Marketing Campaign Manager applies strategic and imaginative thinking to contribute to the development and delivery of marketing programs and campaigns across all business units. Working in close collaboration with Product Marketing and other key stakeholders, the Marketing Campaign Manager will leverage their knowledge of an array of digital and traditional marketing methods to design and deliver campaigns to achieve the desired outcomes and corporate marketing OKRs and KPIs.
Duties and Responsibilities:
- Work in close partnership and collaboration with business unit leadership, product marketing and other stakeholders, to design, develop, and deliver integrated, impactful, and results\-driven marketing campaigns and programs.
- Be responsible for developing and implementing marketing strategies that meet the goals of the organization.
- Conduct research of target markets, analysis of consumer behavior and trends, and identify opportunities for growth.
- Effectively plan and coordinate multiple campaign elements to ensure on\-time and on\-budget delivery, by leveraging sound resource management, and effective collaboration with other team members.
- Monitor and manage the budgets for assigned marketing campaigns, ensuring all campaigns stays within the allocated budget while still achieving the desired results.
- Effectively organize and manage complex projects, priorities, and multiple tasks simultaneously while working collaboratively across various groups, including Product Marketing, Content Hub, Corporate Comms, Social and other related functions.
- Think creatively to develop innovative ideas to attract and retain customers.
- Monitor the progress of all assigned campaigns, making adjustments as needed.
- Analyze campaign data to evaluate its effectiveness and identify areas for improvement.
- Conduct competitive analysis with regards to demand gen programs such as SEO, PPC, and other marketing platforms.
- Compile and provide regular reports to stakeholders, including senior management and the marketing team. These reports may include campaign performance metrics, budget updates, and other relevant information.
- Understand, monitor and report on campaign KPIs and other performance metrics that measure achievement of business unit goals.
- Effectively analyze data, interpret marketing trends, and make informed decisions based on the analysis.
- Demonstrate adaptability to changing market conditions, adjusting strategies as needed, and staying up to date with the latest marketing trends and technologies.
- Maintain compliance with Inovalon's policies, procedures and mission statement;
- Adhere to all confidentiality and HIPAA requirements as outlined within Inovalon's Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the undertaking of the position;
- Fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success of the Company; and
- Uphold responsibilities relative to the separation of duties for applicable processes and procedures within your job function.
Job Requirements:
- 2\+ years of experience in building and administration of marketing campaigns or programs;
- Experience marketing technology platforms, tools, products or services, preferably in a B2B environment;
- Intermediate to expert level knowledge of and practical experience using marketing tools such as: Marketo, LinkedIn advertising, Google Ads DemandBase, TechTarget or other like software/marketing platforms
- Minimum intermediate to advanced skills in MS PowerPoint, MS Excel and MS Word;
- Excellent oral and written communication skills;
- High energy, enthusiasm, and initiative;
- Demonstrated effective time and self\-management skills and the agility to work in a dynamic environment.
Education:
- Bachelor's degree in Marketing, Communications, or an equivalent combination of education and related work experience.
Physical Demands and Work Environment:
- Sedentary work (i.e., sitting for long periods of time);
- Exerting up to 10 pounds of force occasionally and/or negligible amount of force;
- Frequently or constantly to lift, carry push, pull or otherwise move objects and repetitive motions;
- Subject to inside environmental conditions; and
- Travel for this position will be up to 5% domestically.
*This position is not eligible for immigration sponsorship (e.g. H\-1B, TN, or E\-3\). Applicants must be authorized to work in the United States as a condition of employment. (This is only applicable for US\-based positions)*
*If you don't meet every qualification listed but are excited about our mission and the work described, we encourage you to apply. Inovalon is most interested in finding the best candidate for the job,* *and you may be just the right person for this or other roles.*
*By embracing* *inclusion,* *we enhance our work environment and drive business success. Inovalon strives to* *provide equal opportunities* *to* *the communities where we operate and to our clients and everyone whom we serve. We endeavor to create a culture of inclusion in which our associates feel empowered to bring their full, authentic selves to work and pursue their professional goals in an equitable setting. We understand that by fostering this type of culture, and welcoming different perspectives, we generate innovation and growth.*
*Inovalon is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or* *veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirement.*
*To review the legal requirements, including all labor law posters, please visit this* *link*
*To review the California Consumer Privacy Statement: Disclosures for California Residents, please visit this* *link*
Salary Context
This $60K-$85K range is below 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 Inovalon, 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 ($72K) sits 57% below the category median. Disclosed range: $60K to $85K.
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.
Inovalon AI Hiring
Inovalon has 3 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Atlanta, GA, US, Tampa, FL, US, Remote, US. Compensation range: $85K - $150K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 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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