3 months ago

Senior Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Senior ML Engineer to design, deploy, and productionize AI systems for public sector environments, spanning cloud to edge devices. Focused on multi-modal AI, RAG pipelines, adaptive ML via LoRA/PEFT, and optimized on constrained hardware with PyTorch, TensorFlow, and Hugging Face Transformers. Responsible for turning research prototypes into scalable production solutions with robust, secure performance across diverse connectivity scenarios.

Location: Austin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key 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.

Pay and Benefits

Perks:Health InsuranceDentalVision401kWellness StipendContinuing EducationParkingParental LeaveLife Insurance

Key Requirements

•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
•Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone)

Experience:4+ yearsPublic sectorAiMachine learningEdge computing

Skills:Problem solvingCommunicationTeam collaboration

Languages:English

Tech Stack:PyTorchTensorFlowHugging Face TransformersLoRAPEFTRAGChromaDBFAISSMilvusPineconeCUDA

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Security Clearance:Active US Security clearance

Company Brief

WebAI

Provides an AI platform to build, deploy, and manage web-based AI applications, offering tools for natural language, vision, and web automation so businesses and developers can integrate intelligent features into websites and products.

Industry: AI & Machine Learning

Website

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WebAI

3 months ago

Senior Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: Austin

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key 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.

Pay and Benefits

Perks:Health InsuranceDentalVision401kWellness StipendContinuing EducationParkingParental LeaveLife Insurance

Key Requirements

•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
•Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone)

Experience:4+ yearsPublic sectorAiMachine learningEdge computing

Skills:Problem solvingCommunicationTeam collaboration

Languages:English

Tech Stack:PyTorchTensorFlowHugging Face TransformersLoRAPEFTRAGChromaDBFAISSMilvusPineconeCUDA

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Security Clearance:Active US Security clearance

Company Brief

WebAI

Industry: AI & Machine Learning

Website