Zendesk

2 days 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: 7 hours agoStatus: Live

Job Summary

Design and architect the high-performance runtime powering AI agents, focusing on durable, fault-tolerant execution, multi-tenant state management, and secure resource isolation. Build enterprise memory infrastructures with strict ACID transaction integrity, drive adoption of the Model Context Protocol (MCP), and establish observability/FinOps telemetry to trace tenant actions and optimize compute cost-per-token. Partner with AI scientists while owning execution environments for safe production operation.

Location: Melbourne, New South Wales

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Architect multi-tenant durable agent runtime with fault-tolerant execution and automated recovery.
•Build convergent, high-throughput enterprise memory functions for agent memory tiers with low-latency retrieval and ACID integrity.
•Ensure strict multi-tenant resource isolation with zero-trust execution validation and database row-level security.
•Develop the integration fabric (MCP) by building secure servers/clients for tool discovery and capability negotiation and enabling agent-to-agent collaboration.
•Implement observability and FinOps telemetry, enforcing rate limits and optimizing compute cost-per-token with tenant-level tracing.

Pay and Benefits

Perks:Remote Work

Key Requirements

•Extensive backend experience building distributed systems (Java, Go, or Python), including event-driven architectures (Kafka) and non-deterministic execution in cloud environments.
•Architect durable, fault-tolerant execution environments with incremental execution and state persistence for long-running workflows.
•Design enterprise memory infrastructure supporting working/episodic/semantic/procedural memory with ultra-low-latency retrieval and strict ACID transactions.
•Implement multi-tenant resource isolation using zero-trust execution validation and database-layer row-level security to prevent cross-tenant leakage.
•Experience with protocol-driven integration and secure tool execution, including MCP-style capability negotiation and sandboxing.

Experience:AI agentsLLMsDistributed systems

Skills:Systems thinkingMentoringReliability focusProtocol awarenessArchitectural depth

Tech Stack:GoJavaPythonKafkaPostgresGRPCGraphQLMCPVector storesDurable executionEvent sourcingACIDRow-level securityZero-trustIn-memory datastores

Company Brief

Zendesk

Provides cloud-based customer service and engagement software, including help desk, ticketing, chat, and CRM tools that enable businesses to manage customer support, self-service, and omnichannel communication at scale.

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Decacorn (USD 10B+)

Funding: Private Equity Backed

Headquarters: San Francisco, United States

Founded: 2007

Glassdoor: 4.0

Website LinkedIn Glassdoor

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Zendesk

2 days 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: 7 hours agoStatus: Live

Job Summary

Location: Melbourne, New South Wales

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Architect multi-tenant durable agent runtime with fault-tolerant execution and automated recovery.
•Build convergent, high-throughput enterprise memory functions for agent memory tiers with low-latency retrieval and ACID integrity.
•Ensure strict multi-tenant resource isolation with zero-trust execution validation and database row-level security.
•Develop the integration fabric (MCP) by building secure servers/clients for tool discovery and capability negotiation and enabling agent-to-agent collaboration.
•Implement observability and FinOps telemetry, enforcing rate limits and optimizing compute cost-per-token with tenant-level tracing.

Pay and Benefits

Perks:Remote Work

Key Requirements

•Extensive backend experience building distributed systems (Java, Go, or Python), including event-driven architectures (Kafka) and non-deterministic execution in cloud environments.
•Architect durable, fault-tolerant execution environments with incremental execution and state persistence for long-running workflows.
•Design enterprise memory infrastructure supporting working/episodic/semantic/procedural memory with ultra-low-latency retrieval and strict ACID transactions.
•Implement multi-tenant resource isolation using zero-trust execution validation and database-layer row-level security to prevent cross-tenant leakage.
•Experience with protocol-driven integration and secure tool execution, including MCP-style capability negotiation and sandboxing.

Experience:AI agentsLLMsDistributed systems

Skills:Systems thinkingMentoringReliability focusProtocol awarenessArchitectural depth

Tech Stack:GoJavaPythonKafkaPostgresGRPCGraphQLMCPVector storesDurable executionEvent sourcingACIDRow-level securityZero-trustIn-memory datastores

Company Brief

Zendesk

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Decacorn (USD 10B+)

Funding: Private Equity Backed

Headquarters: San Francisco, United States

Founded: 2007

Glassdoor: 4.0

Website LinkedIn Glassdoor