About zaimler

AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it.

zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve.

zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we'd love to talk.

About the Role

This is a staff-level role for a seasoned AI/ML engineer who can operate at the intersection of research and production. You'll serve as the technical bridge between our research and applied engineering teams — translating cutting-edge ideas into robust, scalable systems while setting the strategic direction for how we train, evaluate, and deploy models. Deeply hands-on, but able to zoom out and set the agenda.

We're looking for someone who has been here before. Built the infra, shaped the strategy, and knows what good looks like at every layer of the ML stack.

What You Will be Doing

Bridge research and applied engineering, ensuring ideas move from concept to production with rigor and speed
Own training and evaluation infrastructure, including tuning, modeling pipelines, and evaluation frameworks
Build and evolve feature stores that serve both model development and production workloads
Optimize agentic workflows end-to-end for performance, reliability, and scale
Set technical strategy for how zaimler trains, evaluates, and deploys models as the platform grows
Partner closely with leadership to define the ML roadmap and make key architectural decisions

Prior Experience

PhD preferred; Master's with exceptional experience considered
8–10 years of experience in ML or AI engineering, with meaningful time in platform or lab environments
Track record of building and owning AI/ML infrastructure end-to-end, not just contributing to it
Deep experience with training pipelines, evaluation frameworks, and feature store design
Hands-on experience optimizing agentic or multi-step LLM workflows in production
Has operated as a lead or Head of AI at a startup or within a high-autonomy team
Strong strategic instincts; able to set direction, make tradeoffs, and communicate them clearly

Nice to Have

Experience on both the AI infra and applied research sides of an organization
Familiarity with Knowledge Extraction, NLP, or semantic graph systems
Experience with GPU optimization, vLLM, Ray, or similar serving and training tools
Background working with or alongside research teams (lab, academic, or industry)

We value builders over résumés. If this role excites you but you don't check every box, we still want to hear from you. zaimler is an equal opportunity employer.

About the company

Zaimler builds an enterprise data platform that makes data AI-ready by simplifying and organizing complex datasets for advanced applications. The platform ingests and structures data, automates taxonomy creation and knowledge-graph representations, and enables scalable preparation for machine learning and business intelligence. Led by veterans from LinkedIn, Meta, and Visa, Zaimler targets large-scale enterprises with an emphasis on AI readiness and scalable data infrastructure, backed by venture funding and early design partnerships. Its goal is to become the standard platform that lets large organizations unlock the value of their data through AI-ready infrastructure and scalable AI applications.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

Get referred to zaimler

See people who can refer or advise you

Simplify's Take

What believers are saying

Zaimler says it runs inside regulated enterprises and supports GDPR, HIPAA, and 23 NYCRR 500.
PremierAlts lists $35 million raised and a $107 million valuation in February 2026.
Hiring across San Mateo, New York, Texas, and Bangalore signals active commercialization.

What critics are saying

Context-layer software faces direct competition from Snowflake, Databricks, and hyperscalers adding native features.
Enterprise deployments demand deep integrations and governance, dragging sales cycles beyond 2026.
If regulated customers delay adoption, Zaimler becomes a feature, not a standalone company.

What makes zaimler unique

Sofus Macskassy and Biswajit Das bring LinkedIn, Meta, Visa, and Truera data-platform pedigree.
Zaimler auto-infers enterprise ontologies and serves query-time context inside customer VPCs.
It unifies SAP, Salesforce, and Snowflake data without migration or zero-copy export.

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Benefits

Health Insurance

Flexible PTO

Company Equity

zaimler

Staff Applied Machine Learning Engineer

About the job