Senior ML Engineer (LLM, data pipelines)

Описание вакансии

#llm #python #remote

Senior ML Engineer (LLM, data pipelines – advanced level – MUST)

Salary is up to 7500 USD gross (up to 8000 usd gross for candidates with Tech Lead|Team Lead experience)

REMOTE, full-time, b2b contract, location of the candidate and legal entity, bank account of the candidate – outside of Russia, Belarus and Turkey (candidates with Russian and Belorussian citizenship are not allowed here)

https://truelogic.ai/

What we’re building. TrueLogic is an applied AI lab building semantic AI that can actually think with you — grounded in formal knowledge representations and sound reasoning. Our mission is to create trusted agents that reason over deep, structured knowledge: texts, commentaries, arguments, and traditions. We start where the

bar is highest — dense scholarly corpora in Judaism and philosophy — because agents that behave responsibly and intelligently there raise the standard everywhere: scientific research, corporate environments, any setting where an LLM agent needs a real context layer to understand its environment and take the right actions.

We’re looking for an AI Engineer to build the LLM layer of our platform: multi-agent workflows, hybrid retrieval over knowledge graphs and vector indexes, inference integration, and evaluation. You’ll sit between research and platform — taking agent architectures from prototype to production and making them measurably reliable.

Your role

Build and productionize multi-agent workflows on Anthropic/OpenAI APIs: orchestration, tool use, structured outputs, guardrails.

Design hybrid retrieval architectures that combine knowledge graphs, vector search, and ranking into a single coherent context layer.

Build evaluation harnesses and observability for agent behavior — quality, latency, cost — and use them to drive iteration.

Integrate LLM inference, retrieval, and reasoning services into production backends.

Work with researchers and domain experts to turn neuro-symbolic prototypes into robust product features.

What you’ll need

5+ years of commercial software engineering ML experience, including production systems in Python.

Hands-on experience building LLM systems beyond demos: agents and tool use, RAG, or evaluation pipelines. (3+ years)

Real workflow experience with the OpenAI/Anthropic APIs

Solid engineering fundamentals: API design, services, testing, deployment.

Structured knowledge representations: ontologies, knowledge graphs, SPARQL, or graph databases (e.g.,Neo4j).

Vector databases and hybrid retrieval architectures.

B2 English

Nice to have

Kubernetes and cloud-native deployment.

Model serving (e.g., vLLM), fine-tuning, or evaluation frameworks.

Go and/or Scala.