Senior Machine Learning Engineer
At a glance
Senior Machine Learning Engineering role at webAI. Austin · full-time · no salary stated · we estimate $181,150–$247,500 across the United States.
webAI has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Turn research models into reliable, scalable systems that run across cloud, edge and mobile hardware
- Build agent workflows that coordinate multi-step reasoning, tool use and decisions in production
- Use LoRA, PEFT and on-device inference to develop and tune models with the listed ML frameworks
- Reduce model cost with quantization, pruning, distillation and hardware-specific acceleration
- Create RAG pipelines with vector database retrieval, and optimize multimodal systems for constrained, distributed settings
What you bring
- You hold an active U.S. security clearance
- You bring at least four years in applied AI, ML engineering or production AI systems
- You are deeply skilled in PyTorch, TensorFlow or Hugging Face Transformers
- You have deployed models across cloud, edge and mobile hardware, and can optimize them through compression techniques
Who this fits
This senior engineering role suits someone who can move models into production and keep them dependable across restricted or disconnected environments. The position is full-time with webAI and supports public sector work.
From the employer
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 multi disciplinary teams.
Strong understanding of GPU computing, CUDA, and performance profiling.
We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following:
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:
We strive to provide competitive benefits to all employees. The benefits listed in this posting generally apply to U.S.-based employees. For employees hired outside the United States, benefits may vary based on local law, country-specific requirements, and the employment platform or entity through which the employee is hired.
Competitive salary and performance-based incentives
Comprehensive health, dental, and vision benefits package
Including a high-deductible HSA option with company contribution
401k match (US-based only)
Flexible PTO Policy
Parental leave for eligible employees
Continuing education support
Basic, company-paid life insurance
Supplemental life insurance
Company-paid short and long term disability
Free parking for in-office employees
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.