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About This Role
SimSpace serves as an AI Proving Ground where organizations can confidently train, test, and outmaneuver adversaries in any environment. Trusted by allied governments, militaries, enterprises, and research institutions worldwide, SimSpace enables adaptive, AI\-ready defenses that stay ahead of evolving threats. Founded in 2015 by experts from U.S. Cyber Command and MIT Lincoln Laboratory, the platform unifies training, testing, and validation in a realistic, live\-fire simulation—helping teams evaluate security investments, optimize performance, and compress cyber readiness cycles from months to days.
Why join SimSpace? We are an organization that is focused on building our culture and mindfully enhancing our atmosphere every day which is why we have collaborated on an integral value system. Our governing philosophy of being Human Centered is deeply embedded within our value system. We apply this philosophy to every one of our internal team members, external clients, and their customers.
How Do We Work? We believe that people are at the center of everything we do. SimSpace fosters a culture of continuous learning, curiosity, and professional growth. That belief shows up in action: in\-house training, internal and external learning platforms, cyber conferences, industry events, and dedicated time for skill development. Our people are empowered to shape their careers \- and it shows. Year over year, SimSpace consistently outperforms industry benchmarks in internal mobility, promotions, and total rewards growth.
Who Thrives Here? We are a team of innovators, protectors, and problem\-solvers. We believe diversity of thought and experience fuels better solutions, and we’re committed to building teams that reflect the communities we serve. Whether you’re remote or office\-based, you’ll collaborate with talented colleagues across departments and time zones, united by the mission to create a safer digital world.
We invite you to apply today!
We are looking for a Senior AI\-Centric Threat Hunter
We are looking for a highly motivated Cybersecurity Professional to support mentorship and assessment of global security teams in basic to advanced cybersecurity skill areas. The ideal candidate has a strong technical background, is enthusiastic, is good at problem solving, has a strong desire to learn, prefers to be hands\-on technically, and constantly strives for excellence.
The Senior AI\-Centric Threat Hunter will be part of a team developing methodologies of incorporating AI agents into cybersecurity workflows, designing experiments to help develop/test AI agents and models, delivering instructional content to customers, and facilitating a variety of Blue Team exercises for SimSpace and our customers. When facilitating exercises, you will be responsible for teaching security concepts, demonstrating practical/hands\-on use of open source and commercial security tools; referencing both well established and cutting edge techniques that Cybersecurity Incident Response Teams might use to effectively defend their networks from advanced cyber threats.
What will you be doing as a Senior AI\-Centric Threat Hunter at SimSpace?
- Lead an internal initiative to research and integrate candidate agentic capabilities into test environments
- Serve as a consultant to customers looking to integrate agentic capabilities into their cybersecurity enterprise in how to identify, integrate and test capabilities prior to deployment
- Keep up with industry evolution around AI and cybersecurity operations reviewing publications and standards
- Bring world class mentorship of advanced threat hunting tactics and strategy for our global clients and international organizations.
- Utilize years of Blue Teaming experience to establish parsing rules, dashboards, and tuning of numerous enterprise security tools in our cyber range platform to exceed client goals and objectives.
- Work with our range operations team to develop toolsets and scenarios within a cybersecurity range to model real\-world threat defense scenarios.
- Utilize foresight and awareness of overall business priorities when dealing with competing requirements and needs from across the organization in order to build consensus and drive results.
- Takes initiative in day\-to\-day tasks, leads projects, and mentors other team members.
- Navigate and work effectively across a complex, geographically dispersed organization.
- Support assessment of customer security teams and customer events ( this means the role will require national and international travel estimated up to 25\-30%).
What are the qualifications to apply? To be successful as a Senior AI\-Centric Threat Hunter on SimSpace’s Evaluation Team, you need to have:
- Demonstrated proficiency in AI/ML engineering, including practical application and experimentation with AI agents, LLM APIs.
- Possess a deep understanding of AI agents, specializing in the orchestration of agent decision loops, tool access frameworks, and memory systems optimized for threat hunting and proactive security operations.
- Architecting RAG Systems: Hands\-on experience designing and deploying Retrieval\-Augmented Generation (RAG) pipelines to ground LLMs in internal threat intelligence, historical incident data, and enterprise security policies while eliminating hallucinations.
- Advanced proficiency in Python and standard data science/AI libraries, alongside strong scripting skills for data manipulation (Pandas, Numpy).
- Familiarity with open\-source AI ecosystems (Hugging Face) and frameworks for running local, privacy\-safe LLMs (Ollama, vLLM).
- 6\+ years of experience in a technical role in the areas of Security Operations, Incident Response, Detection Engineering, Offensive Security/Red Team, or Cyber Threat Intelligence.
- Experience analyzing host, network, and application telemetry for indicators of attack across the stages of the cyber kill chain.
- Direct experience working with very large datasets and log analysis tools including but not limited to: Splunk, Elastic, Python, Pandas, SQL, Hadoop, Hue.
- Ability to apply Cyber Threat Intelligence through enrichment, correlation, and attribution.
- Experience with setup and/or troubleshooting of security stacks.
- Familiarity with offensive security strategies and assessment methodology.
- Experience explaining threat hunt objectives to mixed technical and non\-technical audiences and ability to communicate associated risk by distilling complex content into digestible information.
- Hands\-on technical experience and ability to demonstrate hunting for indicators of compromise in numerous enterprise scale EDR and SIEM tools to include Splunk, Elastic, Crowdstrike, and many other major vendors.
- Previous experience performing digital forensics or indecent response on major security incidents.
- Demonstrated self\-starter with a constant desire to help others improve and build the team.
*We’re proud to offer a competitive and comprehensive package designed to support your well\-being, growth, and success:*
- Compensation. Base salary range: $135,000 \- $200,000 reflecting our confidence in your expertise and impact, with the opportunity for bonuses tied to individual and company performance.
- Health \& Wellness. Comprehensive medical, dental, and vision benefits, plus savings plans—coverage starts on day one!
- Mental Health Support. Access to company\-paid counseling, coaching, and resources for you and your family through Spring Health.
- Financial Well\-Being. Plan for your future with a 401(k)\-retirement savings plan featuring a company match.
- Flexible Time Off. Take the time you need with unlimited vacation and dedicated health \& wellness days. SimSpace provides flexible solutions to meet the diverse work\-life needs of team members.
- Parental Leave. Paid leave plans to support you and your loved ones during life’s most important moments.
- Ownership Opportunities. Equity stock options at hire, with annual performance\-based grants—become an invested stakeholder in our shared success.
- Referral Rewards. Earn $1,500–$3,500 for every qualified hire through our employee referral program.
- Peloton Interactive Wellness Program. Full\- and partial\- subsidized membership plans and equipment discounts to help you reach your personalized fitness goals.
- Continuous Learning. Access a LinkedIn Learning membership to prioritize your personal and professional development.
- Social Connections. Monthly reimbursements for meaningful connections with teammates through our SocialSpace Community.
- Extra Perks. Legal plan coverage, pet insurance, wellness reimbursements, and more to simplify life’s details.
SimSpace is an Equal Opportunity Employer:
*In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire.*
*SimSpace is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. We are committed to providing an inclusive and welcoming environment for all members of our staff, clients, volunteers, subcontractors, vendors, and clients.*
*Research shows that women and people from underrepresented groups only apply to jobs if they meet all of the qualifications. However, no one ever meets 100% of the qualifications. SimSpace encourages you to break that statistic and to apply. We look forward to your application!*
*We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact* *[email protected]**.*
*SimSpace does not accept unsolicited resumes from employment agencies.*
*Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range.*
Compensation Range: $135K \- $200K
Salary Context
This $135K-$200K range is below the median for AI/ML Engineer roles in our dataset (median: $181K across 1996 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 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At SimSpace Corporation, 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 $178,940 based on 11,900 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($167K) sits 6% below the category median. Disclosed range: $135K to $200K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
SimSpace Corporation AI Hiring
SimSpace Corporation has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in US. Compensation range: $200K - $200K.
Location Context
AI roles in Austin pay a median of $218,800 across 493 tracked positions. That's 9% above 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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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