More jobs:
Machine Learning Engineer
Job in
Raleigh, Wake County, North Carolina, 27608, USA
Listed on 2026-09-07
Listing for:
TEKsystems
Full Time
position Listed on 2026-09-07
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Reliability/ Performance Engineer
Job Description & How to Apply Below
- Masters degree in Computer Science, Machine Learning, Data Science, Engineering, or related discipline.
- 10+ years of software engineering, machine learning engineering, or applied AI experience.
- 3+ years building production AI, LLM, or Generative AI solutions.
- Strong Python development experience.
- Experience developing production-grade Retrieval-Augmented Generation (RAG) systems.
- Experience building or supporting Agentic AI, AI orchestration, or multi-agent workflows.
Description
About the Role
Our client is seeking a Senior Machine Learning Engineer II to help build and scale advanced Agentic AI and Multi-Agent Systems that transform how professionals interact with information.
This role goes beyond traditional machine learning engineering. The ideal candidate will have experience designing intelligent AI systems capable of reasoning, planning, retrieval, tool utilization, workflow orchestration, and autonomous task execution across large-scale knowledge environments. You will work closely with Applied Scientists, ML Engineers, Architects, Product Leaders, and Software Engineers to develop production-grade AI systems that leverage Large Language Models (LLMs), RAG architectures, vector search, agent frameworks, and emerging reasoning technologies.
This position is ideal for engineers who have moved beyond basic prompt engineering and have experience building sophisticated AI applications capable of solving complex, multi-step business problems.
Key Responsibilities
Agentic AI Development
Design, build, and deploy production-scale multi-agent AI systems.
Develop agent workflows capable of planning, reasoning, retrieval, tool utilization, validation, and task execution.
Architect agent ecosystems utilizing specialized agent roles such as:
Planner
Researcher
Critic
Verifier
Writer
Orchestrator
Implement shared memory, state management, context preservation, and agent communication frameworks.
Develop guardrails and validation systems to improve reliability and reduce hallucinations.
Retrieval-Augmented Generation (RAG)
Design and optimize enterprise-scale RAG architectures.
Develop advanced retrieval strategies leveraging:
Vector databases
Semantic search
Knowledge graphs
Metadata filtering
Hybrid retrieval approaches
Improve grounding, citation accuracy, retrieval quality, and relevance.
Optimize chunking strategies, embedding pipelines, and context management.
Machine Learning Engineering
Build scalable AI and machine learning services deployed into production environments.
Develop model evaluation frameworks for both traditional machine learning and LLM-based systems.
Create automated testing pipelines for prompts, retrieval systems, agent workflows, and AI outputs.
Fine-tune, evaluate, and optimize AI systems for performance, latency, quality, and cost.
AI Evaluation & Observability
Define and measure success metrics for agentic AI systems, including:
Task completion rates
Accuracy
Hallucination rates
Retrieval effectiveness
Cost efficiency
User satisfaction
Latency
Implement monitoring, observability, and evaluation frameworks for LLM applications.
Develop processes for continuous improvement and model governance.
Research & Innovation
Evaluate emerging AI technologies and frameworks.
Investigate advances in:
Multi-Agent Systems
Agentic AI
Reasoning Models
LLM Orchestration
Knowledge Retrieval
Autonomous AI Workflows
Contribute to architecture standards and AI platform strategy.
Participate in proof-of-concepts and innovation initiatives.
Required Qualifications
Bachelor's degree in Computer Science, Machine Learning, Data Science, Engineering, or related discipline.
6+ years of software engineering, machine learning engineering, or applied AI experience.
3+ years building production AI, LLM, or Generative AI solutions.
Strong Python development experience.
Experience developing production-grade Retrieval-Augmented Generation (RAG) systems.
Experience building or supporting Agentic AI, AI orchestration, or multi-agent workflows.
Strong understanding of:
Large Language Models (LLMs)
Natural Language Processing (NLP)
Information Retrieval
Semantic Search
Embeddings
Prompt Engineering
Model Evaluation
Experience working with…
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