AI/ML Engineer II

People who do well here tend to approach problems similarly.

• They are comfortable operating without full clarity .
• They pay attention to what actually happens, not just what was intended.
• They are willing to be wrong, adjust quickly, and improve based on real feedback.
• They take responsibility for outcomes, not just implementation.

This is not a good fit for someone who needs tightly defined problems or prefers distance from how their work is used.

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.

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.

We offer competitive, performance-aligned compensation tied to technical depth, clearance level, and mission impact.

• 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

• 401(k) plan (no current employer match, but under consideration)
• 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.

• Design and implement end-to-end ML workflows supporting semantic search, classification, entity resolution, and retrieval.
• Build production-ready AI services with strong attention to reliability, testability, and maintainability.
• Develop and tune embedding pipelines, retrieval systems, and retrieval-augmented generation (RAG) components.
• Collaborate with data engineering and backend teams to integrate ML capabilities into scalable systems.
• Implement evaluation workflows tied to measurable mission performance (accuracy, latency, robustness).
• Support deployment, monitoring, and versioning of ML models as part of a disciplined MLOps lifecycle.
• Participate in architecture discussions and propose solutions aligned to platform constraints and mission needs.

• B.S. or M.S. in Computer Science, Engineering, or related technical field.
• 3–6 years of experience building applied ML systems or NLP workflows.
• Strong Python development skills with ability to write production-quality services.
• Experience training, tuning, evaluating, and deploying ML models.
• Familiarity with modern ML/NLP libraries (Transformers, spaCy, scikit-learn, PyTorch).
• Exposure to cloud environments and containerized deployment patterns.
• Strong communication skills and ability to collaborate across teams.

• Experience with embeddings, vector search, RAG, and semantic retrieval systems.
• Familiarity with MLflow, DVC, Kubeflow, SageMaker, or similar tooling.
• Experience with graph-based retrieval, agentic systems, or tool-use architectures.
• Experience supporting defense, intelligence, ISR, or mission environments.