Interested in this AI/ML Engineer role at iCatalyst?
Apply Now →Skills & Technologies
About This Role
Job ID: 2026\_07\_AIE
Role/Title: Artificial Intelligence (AI) Engineer
Priority: High – Immediate Hire
Hybrid Opportunity \- Must be local to the DC/VA/MD area and available to work onsite when needed.
####
#### Clearance Requirement: Public Trust Clearance \-*Due to federal clearance requirements for this position, only U.S. citizens or Permanent Residents are eligible.* *Candidates with visa sponsorship —now or in the future—are not eligible for this clearance.*
About iCatalyst
-------------------
iCatalyst, Inc. is a next\-generation technology company specializing in Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning (ML), and Robotic Process Automation (RPA).
Since 2007, we have partnered with federal and commercial clients to deliver innovative, mission\-driven solutions that enhance operational efficiency, digital transformation, and business outcomes.
Our solutions are built on a foundation of agility, security, and scalability, guided by our CMMI ML 3 Services and Software Development framework and backed by globally recognized certifications in ISO 9001:2015 (Quality Management) and ISO/IEC 27001:2022 (Information Security).
#### Core Capabilities
We specialize in AI\-Driven Digital Transformation, Cloud and Infrastructure Modernization, Data Engineering and Advanced Analytics, Enterprise IT Modernization and Mission\-Focused Program and Change Management.
#### Why Join iCatalyst?
At iCatalyst, our people are at the center of everything we do.
- Award\-winning culture of innovation and a friendly workplace
- Work on cutting\-edge AI and digital transformation projects
- Be part of a mission\-driven team
- Grow your career in a stable, certified, high\-performing organization
- Comprehensive benefits and wellness packages, 401K with company match, competitive pay
Role Overview
-----------------
We are seeking a AI Engineer to join our growing team in support of our federal program.
This is an exciting opportunity to work on cutting\-edge technologies and contribute to impactful, mission\-critical initiatives.
Key Responsibilities
------------------------
- Serve as the senior developer for the design, development, enhancement, and sustainment of a cloud\-based, browser\-accessible Geographic Information System (GIS) platform supporting aeronautical information, airspace restrictions, and air traffic analysis.
- Architect, develop, and optimize enterprise\-scale applications using Angular, TypeScript, and JavaScript, ensuring high performance, scalability, maintainability, and security.
- Design, develop, and manage complex UI/UX, work with geospatial data models and services using PostgreSQL and PostGIS, including spatial indexing, geoprocessing, and advanced spatial analytics.
- Develop sophisticated application UI/UX capabilities including geospatial visualization, mapping services, spatial analysis, and real\-time data processing.
- Integrate and consolidate data from multiple authoritative sources into a unified operational platform while ensuring data accuracy, consistency, and integrity.
- Lead the modernization of system architecture and software components using industry best practices, emerging technologies, and cloud\-native design patterns.
- Identify, evaluate, and implement Artificial Intelligence (AI) and Machine Learning (ML) capabilities to enhance geospatial analytics, predictive modeling, anomaly detection, decision support, and operational efficiency.
- Design and implement AI/ML pipelines that leverage geospatial, airspace, and air traffic datasets to generate actionable insights and automate analytical workflows.
- Optimize application, database, and geospatial processing performance to support very large\-scale datasets, complex spatial queries, and mission\-critical operational requirements.
- Provide technical leadership and hands\-on expertise for system architecture, code quality, DevSecOps practices, troubleshooting, and complex problem resolution.
- Collaborate with government stakeholders, domain experts, and engineering teams to translate mission requirements into scalable technical solutions.
- Ensure solutions comply with federal security, data governance, accessibility, and operational standards while maintaining high system availability and reliability.
- Special projects such as corporate proposals, technical write ups, etc., as needed.
- Provide support and expertise in assigned domain.
- Collaborating with cross\-functional teams to deliver solutions.
- Ensure adherence to security, compliance, and quality standards.
- Support continuous improvement and innovation initiatives.
Required Skills
-------------------
- Expertise in PostgreSQL, PostGIS, Angular, TypeScript, JavaScript, enterprise GIS technologies and related technologies.
- Experience using enterprise security tools (e.g. SolarWinds, Splunk etc.).
- Knowledge of frameworks such as NIST 800\-53, FISMA, and FedRAMP.
- Experience using tools e.g. JIRA, Confluence, and Visio.
- Strong planning and organizing skills and are a team player.
- Ability to prioritize and work effectively towards deadlines.
- Attention to detail and accuracy.
- Ability to work independently and as part of a team; ability to take initiative with minimal direction and to solve problems.
- Ability to interact with a variety of individuals in a courteous and professional manner.
- Strong communication skills and the ability to collaborate with multiple teams.
- Strong analytical and problem\-solving abilities.
Experience \& Qualifications
--------------------------------
- 10\+ years of relevant experience.
- Demonstrated expert\-level proficiency in PostgreSQL, PostGIS, Angular, TypeScript, JavaScript, and enterprise GIS technologies.
- Proven experience developing and deploying advanced AI/ML\-enabled geospatial solutions in complex, data\-intensive environments.
- Extensive knowledge of geospatial data management, spatial analytics, aeronautical information systems, and airspace or transportation domain applications.
- Proven ability to work in fast\-paced, client\-focused environments.
- Experience supporting federal programs preferred
- Preferred Certifications:
+ Certifications such as AI, ML, AWS/Microsoft Certified Solutions Architect.
Education
-------------
- Position requires BS/BA degree in a STEM discipline from an accredited university with 10 years of experience OR a MS/MA degree in STEM discipline with 8 years of experience.
Work Location and Schedule
------------------------------
- McLean, VA (Hybrid/Remote)
- Monday – Friday 8AM – 5:30PM EST
- Work schedules and arrangements may be adjusted based on client and program needs
Employment Type
-------------------
- Full\-Time, Salaried (Exempt)
Customer / Contract
-----------------------
- Federal Agency
Compensation
----------------
- The likely salary range or Hourly rate for this position is $130K\-$165K.
Salary range reflects our commitment to pay equity and transparency. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, certifications, labor qualifications, geographic location and contractual requirements and could fall outside of this range.
Clearance Requirements
--------------------------
- U.S. Citizenship or Permanent Residence required
- Ability to successfully pass a federal background check
- Employment is subject to verification of eligibility to work in the United States
As part of the hiring process, we will ask you to complete a background verification process that may leverage artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.
Travel
----------
- Minimal or no travel anticipated
Total Rewards and Benefits
------------------------------
We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.
Our benefits package for eligible employees includes a variety of medical plan options, some with Health Savings Accounts, a dental plan option, a vision plan, and a 401(k)\-plan offering the ability to contribute both pre\- and post\-tax dollars up to the IRS annual limits and receive a company match.
To encourage work/life balance, iCatalyst offers employees a variety of paid time off plans, including vacation, sick, 11 Federal holidays, military, bereavement and jury duty leave. To ensure our employees are able to protect their income, other offerings such as short and long\-term disability benefits, life, accidental death and dismemberment, insurance are provided or available.
In addition, we offer our full\-time employees the following benefits subject to eligibility and iCatalyst policies.
- Phone and internet Reimbursement for eligible employees
- Transportation Support (Uber rides to \& from HQ to select locations)
- Training \& Education Assistance (per eligibility)
- Annual Wellness Benefit
- Social and Community giveback
Additional Information
--------------------------
- This position is contingent upon contract award and/or client approval, where applicable
- iCatalyst, Inc. is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, or other protected characteristics
- Candidates will be required to adhere to client\-specific compliance requirements and sign NDAs
- iCatalyst reserves the right to modify job responsibilities, duties, or requirements as business needs evolve
Next Step
-------------
Explore a career at iCatalyst and you’ll find endless opportunities to grow alongside colleagues who share your ambition to deliver your best work. Apply today to be part of a team shaping the future of technology and innovation.
For more information, please visit:
iCatalyst Careers Page
iCatalyst Website
\#hc254854
Salary Context
This $130K-$165K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At iCatalyst, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($147K) sits 33% below the category median. Disclosed range: $130K to $165K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
iCatalyst AI Hiring
iCatalyst has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in McLean, VA, US. Compensation range: $130K - $165K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.