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What You Will Do
The Space Remote Sensing and Data Science Group (ISR-6) is seeking a Deputy Group Leader (DGL) to join our collaborative and dynamic team! As the DGL you will help manage the technical work and administrative operations of the group.
The Space Remote Sensing and Data Science Group (ISR-6) is an innovative, vibrant group in the Intelligence & Space Research (ISR) Division. ISR Division has been designing, building, and operating innovative ground, air, and spaced-based measurement and detection systems for over 60 years to provide solutions for some of the most challenging scientific and national security problems facing the nation and the world. The ISR-6 Group, with nearly 40 scientists & engineers, postdocs, and students, develops and deploys sophisticated and customized detection systems and analysis tools to address needs in our key mission areas of nuclear non-proliferation, space domain awareness, atmospheric science, planetary science and exploration, and multi-source intelligence. To develop and deploy these tailored solutions, we leverage our core capabilities in spectral, spatial, and temporal sensing (acoustic, optical, infrared, RF, and x-rays); source phenomenology modeling, interpretation, and propagation; data analysis, algorithm development and machine learning; and detector and system design, development, and deployment (ground, airborne and space-based platforms). Our data analysis capabilities include, but are not limited to, time-frequency analysis, anomaly detection, extraction of faint signals from cluttered backgrounds, machine learning, ptychography and tomography. Our systems are tested in laboratory and operationally relevant (field and testbed) scenarios and range from low TRL (proof of principle systems) to high TRL (deployed).
The ISR-6 Deputy Group Leader (DGL) will work closely with the ISR-6 Group Leader (GL), providing scientific, technical, and operational leadership along with management oversight for Space Remote Sensing and Data Science staff members. The ideal Deputy Group Leader will be highly organized, self-motivated, and adaptable, with the ability to proactively address tactical needs as they arise across areas ranging from facilities management to dynamic staffing needs. A learning mindset is essential, along with strong problem-solving skills, the ability to anticipate and remove obstacles, and the emotional intelligence to lead critical conversations with empathy, clarity, and professionalism. The Deputy Group Leader will devote approximately 50% of their time to group management and leadership responsibilities, while continuing to perform technical work in a half-time capacity, providing balance between growth in management and contributing directly to project deliverables.
The Deputy Group Leader will partner with the Group Leader to lead and manage technical work and administrative operations of the Space Remote Sensing and Data Science Group. Duties include but are not limited to the following:
- Work with the ISR Division Leadership Team, program offices, project leaders, and key stakeholders to provide oversight, support, and coordination of work to ensure delivery of quality products and services on time and within budget.
- Mentor, coach, and build effective leaders and performers, with particular emphasis on individual staff career development. This includes identifying growth opportunities and ensuring recognition of individuals and teams, performance and salary management, development of staffing plans, and onboarding of new staff.
- Marshal resources and investments for development and sustainment of the group's technical capabilities, facilities, and computational infrastructure.
- Manage workforce and group administration, including group financial oversight, specialized facility sustainment and modernization, and development and optimization of processes to enable all staff to achieve mission objectives safely and securely.
What You Need
Minimum Job Requirements:
Leadership and Management
- Demonstrated ability to model collaborative leadership to develop and sustain a creative, entrepreneurial R&D work environment in which innovation and continuous learning are essential for solving some of the most difficult challenges in science, engineering, and national security.
- Experience and skill in conflict management and resolution.
- Experience in or aptitude for working in a large, complex institution with many systems, policies and processes.
Collaboration and Communication
- Demonstrated record of developing collaborations, promoting teamwork, building consensus, and motivating others through common goals and objectives.
- Excellent written and verbal communication skills, to communicate effectively with staff, upper-level management, sponsors, and stakeholders. Demonstrated ability to convey complex concepts or difficult decisions.
- Strong organizational skills, sound technical judgment, and the ability to evaluate tradeoffs. Ability to influence and support project execution or organizational direction.
- Strong active listening skills.
Workforce Development
- Demonstrated ability to foster a positive and inclusive work environment that encourages continuous learning, expands technical and leadership capabilities, recognizes contributions, and supports the career development and long-term success of technical and support staff.
- Demonstrated experience and skill at developing relationships with individuals and acting as an effective mentor and coach for them.
Safety and Security
- Record of effective management of safety, environment, and health risks and processes.
- Experience with effective protection of sensitive information, and responsible execution of national security missions.
- Technical Knowledge
- Demonstrated technical knowledge of and accomplishments in one or more areas relevant to ISR-6's key mission areas such as remote sensing, space systems, space domain awareness, advanced analytics, AI/ML, data science, source phenomenology, or related disciplines.
Security Clearance
Ability and desire to obtain Q clearance, which generally requires U.S. citizenship.
Education/Experience:
Position requires a bachelor's degree from an accredited institution and 5 years related experience; or an equivalent combination of education and experience directly related to the occupation. Degree in a STEM field preferred.
Desired Qualifications:
- Prior record of project leadership, proposal development, marketing of capabilities, and growth of customer relationships.
- Prior experience supervising and leading multidisciplinary teams of individuals with diverse backgrounds.
- Familiarity with the administration of operational and administrative policies and procedures at LANL and/or demonstrated experience navigating complex institutional policies and processes of a large research and development enterprise.
- Working knowledge of DOE/NNSA, DoD, and other government agencies, particularly in programs dealing with ground and/or space-based detection missions.
- Working knowledge of Human Performance Improvement (HPI) and/or Safe Conduct of Research (SCoR) principles, or equivalent techniques.
- Active Q/SCI clearance/access
Notes to Applicants: For full consideration, applicants must submit a comprehensive cover letter that addresses the key requirements of the position.
Physical Requirements:
- Physical movement between buildings located primarily within a half-mile radius, which may include movement across uneven and/or inclined ground.
- Physical movement within large interior facility spaces and corridors, which may require travel up and down stairs.
- Direct interaction with hardware, equipment, and instruments in office and laboratory environments.
Work Environment:
Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Position commitment: Regular appointment employees are required to serve a period of continuous service in their current position in order to be eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the time required, they may only apply for Laboratory jobs with the documented approval of their Division Leader. The position commitment for this position is 1 year.
Note to Applicants:
Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China-including the special administrative regions of Hong Kong and Macau-as well as citizens of the Islamic Republic of Iran, the Democratic People's Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents ("green card" holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory.
Where You Will Work
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:
- PPO or High Deductible medical insurance with the same large nationwide network
- Dental and vision insurance
- Free basic life and disability insurance
- Paid childbirth and parental leave
- Award-winning 401(k) (6% matching plus 3.5% annually)
- Learning opportunities and tuition assistance
- Flexible schedules and time off (PTO and holidays)
- Onsite gyms and wellness programs
- Extensive relocation packages (outside a 50 mile radius)
Additional Details
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.
Clearance: Q (Position will be cleared to this level). Selected applicants will be subject to a background investigation conducted by or on behalf of the Federal Government, and must meet eligibility requirements* for access to classified matter. This position requires a Q clearance. and obtaining such clearance requires US Citizenship except in extremely rare circumstances. Dependent upon the position, additional authorization to access classified information may be required, which may or may not be available to dual citizens. Receipt of a Q clearance and additional access authorization ultimately is a decision of the Federal Government and not of Triad.
*Eligibility requirements: To obtain a clearance, an individual must be at least 18 years of age; U.S. citizenship is required except in very limited circumstances. See DOE Order 472.2 for additional information.
New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.
Regular position: Term status Laboratory employees applying for regular-status positions are converted to regular status.
Internal Applicants: Regular appointment employees who have served the required period of continuous service in their current position are eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the required period of continuous service, they may only apply for Laboratory jobs with the documented approval of their Division Leader. Please refer to Policy P701 for applicant eligibility requirements.
Incentive Compensation Program: Position is eligible to participate in the Triad Incentive Compensation Program. You must be in an eligible position for a minimum of 3 months, before July 1st and remain in an eligible position as of the end of the fiscal year, September 30th. The annual distribution is prorated based on the number of months in the eligible position.
Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to [email protected] or call (505)-664-6947. Apply
Salary Context
This $153K-$266K range is above the median for AI/ML Engineer roles in our dataset (median: $176K across 1540 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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Los Alamos National Laboratory, 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. Disclosed range: $153K to $266K.
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.
Los Alamos National Laboratory AI Hiring
Los Alamos National Laboratory has 5 open AI roles right now. They're hiring across AI/ML Engineer. Based in Los Alamos, NM, US. Compensation range: $158K - $266K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% 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 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
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