Junior AI/ML Engineer

Torch.AI•Leawood, KS

1d•Hybrid

About The Position

The Work: Join a Mission That Matters Torch.AI is building the AI Control Layer for the United States Government. Not another dashboard. Not another workflow app. Not another black-box model glued to a PowerPoint. The AI Control Layer is foundational data and intelligence infrastructure that makes sense of messy, adversarial, multi-domain data at machine speed. Commanders, analysts, and operators can act with clarity when it matters most. Our platform—ORCUS (data movement), NEXUS (deep semantic vectorization), and HALO (graph-native reasoning)—is accredited, deployed, and operating today across enterprise clouds and tactical edge environments. We support multi-INT fusion, predictive movement analysis, targeting workflows, anomaly detection, and decision support for cross-domain operations including ISR, information advantage, joint effects, and force protection. We are seeking candidates who want to build systems that operate under real constraints: degraded visibility, adversarial mis/disinformation, intermittent connectivity, low-SWaP hardware, and seconds-to-decision timelines. This is operational AI. It ships. It runs. It gets used. If you’re driven to strengthen U.S. defense readiness and protect national interests, Torch.AI offers meaningful impact at national scale. What Makes Torch.AI Different We believe the government must own its data, its decision environment, and its reasoning infrastructure. Our AI Control Layer increases the value of existing systems of record rather than replacing them. We measure performance by accuracy, latency, and efficiency, not slideware benchmarks. We are craftsmen. We build with intention. We ship with discipline. You’ll collaborate with engineers, data experts, veterans, and mission practitioners. You’ll own meaningful work, move quickly, and see your systems deployed in production, often within weeks. We are fast-paced, entrepreneurial, and mission-driven. Every day is a new puzzle. The Type of Candidates Who Thrive Torch.AI is not for everyone. People who succeed here: Are builders, not curators. They ship and iterate. Are comfortable with messy data, unclear requirements, and real mission constraints without always having the luxury of clear specs. Respect operators and prioritize utility over elegance. Care about explainability and determinism because real decisions demand auditability. Move quickly but understand security boundaries and accreditation realities. Measure success by operational impact, not model novelty. If you need perfect conditions and months of runway, this may not be the right place. If you want to see your work used in production and feel the weight of that responsibility, we should talk. Security Clearance Some roles require an active Secret, Top Secret, or Top Secret/SCI clearance. Where required, candidates must be eligible to obtain and maintain the appropriate clearance level. U.S. citizenship is required for all positions. Torch.AI does not sponsor employment visas. If you do not currently hold a clearance but are eligible, sponsorship may be available depending on role and mission requirements. Work Location Most roles are based at our headquarters in Leawood, KS. Some hybrid/remote positions across the Arlington, VA, Washington, DC, and Maryland (DMV) region are available. Limited travel (<10%) may be required for some roles. Compensation, Benefits, Incentives We offer competitive, performance-aligned compensation tied to technical depth, clearance level, and mission impact. Total Rewards Include: Competitive base salary Quarterly performance bonuses Equity participation within the first 12 months Unlimited PTO + 11 paid company holidays Professional development in a high-growth, mission-driven environment Weekly in-office catering at HQ Benefits: 401(k) plan (no current employer match) PPO, HSA, and TRICARE Supplement medical options Above-market HSA contributions HSA, FSA, and Dependent Care FSA options Dental and vision plans above national averages Employer-paid life insurance (1× salary) Employer-paid Short-Term and Long-Term Disability Voluntary Accident, Critical Illness, and Hospital Indemnity coverage Up to $300/month in tax-advantaged commuter benefits Torch.AI is an Equal Opportunity / Affirmative Action Employer committed to building a team that reflects the mission we serve. If you want to build AI systems that move from ingestion to actionable insight, and know exactly why they produced the answer they did, we should talk.

Requirements

B.S. in Computer Science, Engineering, Mathematics, or related technical field.
1–3 years of experience in software engineering or applied ML (internships included).
Strong Python fundamentals and ability to write clean, testable code.
Familiarity with at least one ML/NLP library (e.g., scikit-learn, spaCy, PyTorch, TensorFlow, Transformers).
Foundational understanding of ML workflows: data preprocessing, training loops, validation, and evaluation metrics.
Basic understanding of APIs, containerization, or cloud environments is preferred but not required.
Ability to work in ambiguous problem spaces and iterate quickly with guidance.
Strong communication skills and willingness to collaborate across engineering disciplines.

Nice To Haves

Exposure to LLMs, embeddings, semantic search, or retrieval pipelines.
Familiarity with vector databases or graph-based data systems.
Experience working with constrained environments (edge devices, low-SWaP hardware).
Understanding of real-time or latency-sensitive ML systems.
Exposure to defense, ISR, or mission-oriented problem domains.
Experience integrating ML outputs into operational workflows.

Responsibilities

Implement and evaluate machine learning components under senior guidance, focusing on operational performance rather than academic novelty.
Support data preparation, labeling, preprocessing, and feature engineering across structured and unstructured datasets.
Contribute to retrieval, embedding, or LLM-enabled pipelines with mentorship.
Assist in building prototype and production-ready AI services using frameworks such as PyTorch, scikit-learn, or modern NLP toolkits.
Execute experiments for NLP/NLU workflows including classification, entity extraction, semantic search, and retrieval.
Support model evaluation using measurable metrics aligned with latency, accuracy, and mission constraints.
Learn foundational deployment patterns including containerization, API exposure, monitoring, and model lifecycle practices.
Participate in code reviews, sprint planning, documentation, and disciplined software development practices.