AI/ML Platform Engineer
$90,300 - 189,600
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Posted yesterday
SENIORITY
Lead
SALARY
$90,300 - 189,600
About the role
- Architect a greenfield implementation of LLM-enabled technologies to support agentic workflows
- Deploy, operate, and monitor open-weight LLMs hosted on local Kubernetes clusters
- Design, build, and maintain RAG pipelines to enable use of document investigation, chunking, embedding, retrieval, and reranking with existing models and services
- Develop and maintain Model Context Protocol (MCP) servers and their interconnections to existing services
- Coach teams on best practice MCP designs and usage
- Support software automated testing environments
- Collaborate with development to implement CI/CD pipelines
- Instrument tracing and evaluation tools to measure, compare, and iteratively improve existing product cycles
- Provide requirements for network infrastructure to improve model serving performance and accessibility
- Support software development environments and change management systems
- In-depth Information Technology understanding
- Excellent communication skills, both oral and written
- Software development familiarity with Python, SQL, and Java
- Experience writing data pipelines with Airflow, Spark, Apache Iceberg, or DBTExperience managing AI/ML infrastructure through Kubernetes, Kserve, vLLM, LangFuse, Elasticsearch, and Terraform
- Supported Gitlab CI/CD pipelines
- Understanding of RAG, MCP servers, QLoRA, and artifact repositories such as Nexus
- Conceptual understanding of data warehousing and data pipelines from open and proprietary sources
- Ability to work under limited supervision and adapt to change
- Strong organizational and teamwork skills
- Must have good work ethics and show diligence in work performed.
- Must take initiative and ownership of requirements and tasks
- Knowledge of IT system processes involving requirements definition, analysis, design, implementation, networks, security and life-cycle support
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
