T
AI Engineer
Teserac, Inc.
3 hours ago
Full-time
On-site
Santa Clara, California, United States
Teserac, Inc. is seeking an AI/ML Engineer to build production AI systems for data center observability and power operations. The role covers the full AI lifecycle, from pipelines and LLM integration to evaluation, orchestration, and ongoing production support.
Key Responsibilities
Design, develop, and maintain AI-powered applications and automation workflows
Integrate and optimize
LLM APIs
for production use cases
Build and refine retrieval and knowledge-augmentation pipelines
Develop evaluation frameworks to benchmark AI system performance
Implement monitoring, tracing, and debugging capabilities for AI systems
Read and synthesize relevant research, bringing ideas forward and debating them with the team
Contribute to AI architecture decisions and production hardening
Stay current with the rapidly evolving AI/ML landscape
What You Will Work On
Multi-agent orchestration and LLM-driven triage workflows
Time-series modeling for anomaly detection, failure prediction, and health forecasting on multivariate telemetry
Retrieval-augmented knowledge systems for operations teams
Data and ML pipelines, including ingestion, ETL, and dataset construction
Fine-tuning and post-training of language models for operational use cases
AI observability, evaluation frameworks, and production performance benchmarking
Required Qualifications
Degree in Computer Science, Machine Learning, Mathematics, or a related field, or equivalent demonstrated experience
Strong proficiency in
Python
Solid software engineering fundamentals, including testing, version control, and CI/CD
Experience working with LLM APIs in applied contexts
Familiarity with agentic system concepts such as tool/function-calling and agent frameworks
Daily use of AI-assisted coding tools (Cursor, Copilot, Claude Code, etc.)
Ability to read ML research papers and translate ideas into practical experiments
Strong analytical thinking and clear communication, including the ability to argue a position and update it when wrong
Technologies Python ,
LLM APIs ,
Cursor ,
Copilot ,
Claude Code ,
LangGraph ,
LangChain ,
MCP ,
PyTorch ,
vLLM ,
GCP (Vertex AI) ,
Niagara ,
BACnet ,
Modbus .
Preferred Experience
Professional AI/ML engineering experience (any level)
Experience building agentic systems using frameworks such as LangGraph or LangChain; MCP a plus
Time-series modeling for forecasting and anomaly or failure prediction on multivariate data
Experience fine-tuning or post-training language models
PyTorch and/or model serving frameworks such as vLLM
Experience building data and ML pipelines, including ingestion and dataset construction
Familiarity with cloud ML platforms, especially GCP (Vertex AI)
LLM evaluation and benchmarking, including harness design and eval loop development
Domain experience with data center or industrial telemetry and BMS/OT protocols (Niagara, BACnet/Modbus)
Background in DevOps, distributed systems, or observability tooling
Benefits
Health Care Plan (Medical, Dental & Vision)
Paid Time Off (Vacation, Sick & Public Holidays)
Free Food & Snacks
Stock Option Plan
401(k)
Location Santa Clara, CA
(onsite)
#J-18808-Ljbffr
Key Responsibilities
Design, develop, and maintain AI-powered applications and automation workflows
Integrate and optimize
LLM APIs
for production use cases
Build and refine retrieval and knowledge-augmentation pipelines
Develop evaluation frameworks to benchmark AI system performance
Implement monitoring, tracing, and debugging capabilities for AI systems
Read and synthesize relevant research, bringing ideas forward and debating them with the team
Contribute to AI architecture decisions and production hardening
Stay current with the rapidly evolving AI/ML landscape
What You Will Work On
Multi-agent orchestration and LLM-driven triage workflows
Time-series modeling for anomaly detection, failure prediction, and health forecasting on multivariate telemetry
Retrieval-augmented knowledge systems for operations teams
Data and ML pipelines, including ingestion, ETL, and dataset construction
Fine-tuning and post-training of language models for operational use cases
AI observability, evaluation frameworks, and production performance benchmarking
Required Qualifications
Degree in Computer Science, Machine Learning, Mathematics, or a related field, or equivalent demonstrated experience
Strong proficiency in
Python
Solid software engineering fundamentals, including testing, version control, and CI/CD
Experience working with LLM APIs in applied contexts
Familiarity with agentic system concepts such as tool/function-calling and agent frameworks
Daily use of AI-assisted coding tools (Cursor, Copilot, Claude Code, etc.)
Ability to read ML research papers and translate ideas into practical experiments
Strong analytical thinking and clear communication, including the ability to argue a position and update it when wrong
Technologies Python ,
LLM APIs ,
Cursor ,
Copilot ,
Claude Code ,
LangGraph ,
LangChain ,
MCP ,
PyTorch ,
vLLM ,
GCP (Vertex AI) ,
Niagara ,
BACnet ,
Modbus .
Preferred Experience
Professional AI/ML engineering experience (any level)
Experience building agentic systems using frameworks such as LangGraph or LangChain; MCP a plus
Time-series modeling for forecasting and anomaly or failure prediction on multivariate data
Experience fine-tuning or post-training language models
PyTorch and/or model serving frameworks such as vLLM
Experience building data and ML pipelines, including ingestion and dataset construction
Familiarity with cloud ML platforms, especially GCP (Vertex AI)
LLM evaluation and benchmarking, including harness design and eval loop development
Domain experience with data center or industrial telemetry and BMS/OT protocols (Niagara, BACnet/Modbus)
Background in DevOps, distributed systems, or observability tooling
Benefits
Health Care Plan (Medical, Dental & Vision)
Paid Time Off (Vacation, Sick & Public Holidays)
Free Food & Snacks
Stock Option Plan
401(k)
Location Santa Clara, CA
(onsite)
#J-18808-Ljbffr