ML Systems Engineer: From Research to Production

Sentient Labs; United Kingdom; On-site; GBP 90,000 - 120,000; Full time

Job summary

Sentient Labs is seeking an Applied ML Engineer to build end-to-end systems at the intersection of ML research and production software in the United Kingdom. You will translate research results into reliable, user-facing products and scale evaluation infrastructure across models and APIs.

You will work across model evaluation, inference infrastructure, and product interfaces, turning experiments into measurable, usable features with robust tooling and documentation.

Qualifications

• Strong Python engineering skills with PyTorch and Hugging Face Transformers.
• Deep knowledge of ML evaluation: datasets, baselines, metrics, calibration, and reproducibility.
• Ability to read ML papers and implement methods from first principles.
• Experience building production software: APIs, async jobs, databases, logging, testing, deployment.
• Experience with open-weight models and LLM inference systems.
• Ability to work across backend/frontend; React/TypeScript exposure.
• Strong technical judgment on evaluating experimental evidence.
• High agency and ownership.
• Adaptable to fast-paced startup with cross-functional work.

Responsibilities

• Reproduce and evaluate research methods using open-weight and API-accessible models.
• Design evaluation datasets, probes, scoring methods, baselines, calibration tests, and experiment harnesses.
• Work directly with model weights, logits, hidden states, activations, model APIs, and inference infrastructure when required.
• Build and extend our evaluation infrastructure, including runners, judges, persistence, experiment orchestration, and reporting.
• Turn research workflows into product experiences, including experiment configuration, runs, traces, comparisons, reports, and review workflows.
• Investigate how verification methods behave under model modification, including fine-tuning, merging, quantization, distillation, safety removal, and deliberate evasion.
• Design controlled experiments that separate meaningful signals from artifacts or confounders.
• Write clear technical reports that distinguish measured evidence, interpretation, and hypotheses.
• Ship production-quality systems with APIs, background jobs, observability, testing, and documentation.

Skills

Python

PyTorch

Transformers

ML Evaluation

Production Software

Experimentation

API Development

Tools

DSPy

LiteLLM

Temporal

Ray

vLLM

PgVector

Job description

Sentient Labs is seeking an Applied ML Engineer to build end-to-end systems at the intersection of ML research and production software in the United Kingdom. You will translate research results into reliable, user-facing products and scale evaluation infrastructure across models and APIs.

You will work across model evaluation, inference infrastructure, and product interfaces, turning experiments into measurable, usable features with robust tooling and documentation.