Sr. Machine Learning Engineer (US Security Clearance)

webAI; Washington (District of Columbia); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health insurance

401(k) match

Wellness stipend

Education support

Parental leave

Free parking

Job summary

webAI is seeking a Senior Machine Learning Engineer to support Public Sector initiatives, building production-ready AI systems for secure and distributed environments. You will transform prototype models into scalable systems operating across hardware from government cloud to edge devices in restricted environments.

Responsibilities include deploying multi-step reasoning workflows, optimizing models with quantization and distillation, and building RAG pipelines with vector databases for

Qualifications

• 4+ years of experience in applied AI/ML engineering or production AI systems.
• Proficiency with PyTorch, TensorFlow, or Hugging Face Transformers.

Responsibilities

• Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning and tool use across production systems.
• Productionize AI models from research prototypes into scalable, deployable systems for real-world applications.
• Engineer adaptive ML systems with on-device inference, LoRA/PEFT, and hardware-aware optimization.

Skills

PyTorch

TensorFlow

Hugging Face Transformers

RAG pipelines

Vector databases

Edge/Distributed AI

Tools

Quadrant

ChromaDB

FAISS

Milvus

Pinecone

Job description

Special Notice: This position is NOT contingent upon awarding of a project or needing a funding source. This is full‑time employment with webAI.

About the Role

We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused on building and optimizing production‑ready AI systems for secure and distributed environments.

You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments.

Responsibilities

• Design, develop, and deploy agentic workflows to orchestrate multi‑step reasoning, tool use, and decision‑making across production systems.
• Productionize AI models from research prototypes into scalable, deployable systems used in real world applications.
• Engineer adaptive ML systems using LoRA, PEFT, and on‑device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine‑tuning, and optimization.
• Implement model optimization techniques such as quantization, pruning, distillation, and hardware‑specific acceleration.
• Build and maintain Retrieval Augmented Generation (RAG) pipelines, including vector database integration for contextual retrieval.
• Work with multi‑modal AI systems across computer vision, audio, and natural language domains.
• Optimize model execution for distributed and resource‑constrained environments, ensuring reliability under variable connectivity conditions.

Qualifications

• Active US Security clearance
• 4+ years of experience in applied AI, ML engineering, or production AI systems.
• Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers.
• Proven experience deploying AI models across cloud, edge, and mobile hardware environments.
• Expertise in model compression and optimization (quantization, pruning, distillation).
• Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone).
• Familiarity with multi‑modal models and synthetic data generation methods.
• Strong algorithmic and problem‑solving skills, especially in distributed or constrained compute environments.

Preferred Skills

• Experience with edge AI, federated learning, or offline inference systems.
• Understanding of AI governance and compliance frameworks relevant to public sector deployments.
• Experience integrating models into large‑scale distributed systems or microservice architectures.
• Excellent communication and technical documentation skills for collaboration across multidisciplinary teams.
• Strong understanding of GPU computing, CUDA, and performance profiling.

Core Values

• Truth – Emphasizing transparency and honesty in every interaction and decision.
• Ownership – Taking full responsibility for one’s actions and decisions, demonstrating commitment to the success of our clients.
• Tenacity – Persisting in the face of challenges and setbacks, continually striving for excellence and improvement.
• Humility – Maintaining a respectful and learning‑oriented mindset, acknowledging the strengths and contributions of others.

Benefits

• Competitive salary
• Comprehensive health, dental, and vision benefits package
• 401(k) match (U.S.-based employees only)
• $200/month Health & Wellness stipend
• Continuing Education support
• $500/year Function Health subscription (U.S.-based employees only)
• Free parking for in‑office employees
• Flexible Time Off (FTO)
• Parental leave for eligible employees
• Supplemental life insurance

webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.