Machine Learning Engineer
Build and ship locally hosted language-model capabilities for a cybersecurity product, owning training data, fine-tuning, evaluation, security, and constrained-hardware inference. The role requires strong Python, LLM serving and grounding experience, with Rust and cybersecurity knowledge valued.
About the job
Responsibilities
- Own the model track end to end, including training data, fine-tuning runs, evaluation, and release.
- Build and maintain trusted evaluation gates for model changes.
- Build training-data pipelines with grounding so models state only what they have read.
- Define agent instructions, tool contracts, and recovery behavior.
- Harden models against prompt injection, misuse, internal-information disclosure, and unsafe guidance.
- Serve models on constrained customer hardware, balancing quantization, inference runtimes, memory, latency, and quality.
- Ship models into a production Rust service in collaboration with engineering, Product Management, and QA.
Requirements
- Bachelor's degree in a technical field or equivalent practical experience.
- Experience fine-tuning open-weight large language models with LoRA, QLoRA, or similar methods.
- Strong Python skills, including training-data pipeline development.
- Experience with retrieval-backed generation, hallucination control, and source-traceable model output.
- Experience with LLM serving and inference, including vLLM or Ollama, quantization, and constrained-hardware trade-offs.
- Familiarity with tool calling and agent-based LLM applications.
- Ability to design and run evaluations for non-deterministic systems.
- Working knowledge of SQL.
- Strong verbal and written English communication skills.
- Self-motivated, adaptable, and comfortable owning a workstream in a fast-paced, team-oriented environment.
Nice to Have
- Rust literacy, including reading and modifying existing service code.
- Experience with agent frameworks such as ADK-style frameworks.
- Awareness of LLM security risks, including prompt injection, data leakage, and misuse.
- Experience deploying compact models on-premises, offline, or in resource-constrained environments.
- Experience with LLM evaluation tooling, including LLM-as-judge systems, regression suites, and human-review loops.
- Cybersecurity knowledge or experience building security-product components.
Skills
Python, LLMs, Lora, Qlora, SQL, vLLM, Ollama, Quantization, Retrieval-Augmented Generation, Tool Calling, Agent Frameworks, Rust, Prompt Injection, Llm Evaluation, Cybersecurity
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