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About This Role
Machine Learning / Full Stack Engineer – US Defense AI Program
Location: Remote (USA) – Occasional Travel to San Diego, CA
Employment Type: Full\-Time
Compensation: Up to $180,000 Base Salary (No Benefits)
Security Requirement: U.S. Citizenship Required \| Active Secret Clearance Preferred (or Ability to Obtain)
About the Opportunity
Bristol\-AI is a leading technology company focused on transforming U.S. Navy maintenance and logistics operations through Artificial Intelligence, predictive analytics, forecasting, and advanced software platforms.
We are seeking a highly skilled Machine Learning / Full Stack Engineer to develop next\-generation forecasting, optimization, simulation, and AI\-powered decision\-support systems that improve fleet readiness and maintenance execution for critical U.S. Navy programs.
This is an exciting opportunity to work on cutting\-edge Defense AI initiatives supporting long\-term Department of Defense modernization programs.
Key Responsibilities
- Develop forecasting, optimization, simulation, and predictive maintenance models using Python and modern machine learning frameworks.
- Build production\-ready AI solutions utilizing PyTorch, TensorFlow, Scikit\-Learn, NumPy, and Pandas.
- Design and implement workload forecasting, schedule\-risk analysis, workload leveling, and uncertainty modeling solutions.
- Develop Monte Carlo simulations, critical\-path analysis tools, and resource optimization workflows.
- Integrate vector databases, embeddings, semantic search, and Retrieval\-Augmented Generation (RAG) capabilities.
- Build and maintain backend services using FastAPI, PostgreSQL, Pydantic, and modern API architectures.
- Collaborate with Full Stack Engineers to deliver React/TypeScript\-based dashboards and analytics platforms.
- Develop AI\-assisted workflows using CopilotKit, Pydantic AI, MCP integrations, AG\-UI, and agentic frameworks.
- Create automated testing, validation, monitoring, and deployment pipelines.
- Support containerized deployments using Docker and Kubernetes, including secure and air\-gapped environments.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Mathematics, Operations Research, or a related field.
- U.S. Citizen (mandatory).
- Active Secret Security Clearance preferred or ability to obtain one.
- Strong proficiency in Python 3, NumPy, Pandas, and machine learning development.
- Hands\-on experience with PyTorch, TensorFlow, or Scikit\-Learn.
- Experience building production software beyond research notebooks.
- Experience with FastAPI, PostgreSQL, Pydantic, APIs, and backend development.
- Ability to translate complex operational requirements into practical AI and forecasting solutions.
Preferred Qualifications
- Prior Department of Defense (DoD), Navy, Federal Government, or Military project experience.
- Veterans strongly encouraged to apply.
- Experience with predictive maintenance, logistics, fleet operations, or maintenance planning systems.
- Knowledge of Monte Carlo simulation, operations research, optimization, and scheduling algorithms.
- Experience with PostgreSQL, pgvector, vector databases, embeddings, and RAG architectures.
- Familiarity with React, TypeScript, dashboards, and data visualization tools.
- Experience with Docker, Kubernetes, Helm, and secure deployment environments.
- Experience with observability, model monitoring, experiment tracking, and production AI systems.
Why Join Us?
- Work on mission\-critical AI solutions supporting U.S. Navy modernization efforts.
- Contribute to large\-scale predictive maintenance and logistics management initiatives.
- Collaborate with experienced AI, software engineering, and defense technology professionals.
- Opportunity to help shape a rapidly growing Defense AI business.
Application Requirements
To be considered, applicants must:
- Be a U.S. Citizen.
- Hold an Active Secret Security Clearance or be eligible to obtain one.
- Have experience in Machine Learning, Data Science, AI Engineering, or Full Stack Development.
- Be available for occasional travel to the San Diego, CA area when required.
Priority Consideration: Veterans, candidates with prior DoD/Military experience, and candidates with active security clearances.
Pay: $150,000\.00 \- $180,000\.00 per year
Benefits:
- Flexible schedule
Application Question(s):
- Are you a U.S. Citizen? (Required)
- Do you currently hold an Active Secret Security Clearance?(Required)
- Have you worked on Department of Defense (DoD) or Military projects? (Required)
- How many years of professional Machine Learning experience do you have?
- How many years of Python development experience do you have?
- Have you deployed machine learning models into production environments?
- Are you willing to travel occasionally to the San Diego, CA area if required?
- What is your current salary? (Annually in USD)
- What is your expected salary? (Annually in USD)
- What is your notice period? (in days)
Work Location: Remote
Salary Context
This $150K-$180K range is below the median for AI Software Engineer roles in our dataset (median: $190K across 251 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,133 AI roles we're tracking, AI Software Engineer positions make up 8% of the market. At KT2i Inc, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 863 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($165K) sits 29% below the category median. Disclosed range: $150K to $180K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
KT2i Inc AI Hiring
KT2i Inc has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US. Compensation range: $180K - $180K.
Remote Work Context
Remote AI roles pay a median of $173,300 across 2,012 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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