Senior Machine Learning Engineer

International SOS; Greater London; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Hybrid working: 3 days in the office

Private pension

Job summary

International SOS in London (Chiswick) is seeking an experienced Senior Machine Learning Engineer to join our Product team. You will build production-grade AI capabilities across generative and agentic paradigms— from retrieval-augmented knowledge assistants and context-aware responses to multi-step agent workflows.

The role combines ML and software engineering to deliver grounded, governed, and scalable solutions that move from Lab prototype to Factory production.

Qualifications

• 6+ years in AI/ML engineering or applied machine learning.
• Strong Python skills with ML libraries and LLM frameworks.
• Experience with cloud AI services and vector stores.
• Proficiency in SQL and data warehouses/lakes.
• Familiarity with MLOps/LLMOps, Kubernetes, CI/CD.
• Understanding of prompt engineering and guardrails.
• Git version control and software engineering fundamentals.

Responsibilities

• Design ML, generative, and agentic AI solutions (RAG pipelines, prompts, tool-calling agents).
• Build grounded retrieval over enterprise knowledge with source citations.
• Integrate models via the model gateway with guardrails and PII redaction.
• Develop and maintain agent orchestration, memory, and escalation paths.
• Data preprocessing, feature engineering, and prompt design on enterprise datasets.
• Deploy solutions through MLOps/LLMOps with monitoring and SLAs.
• Optimize models and prompts for accuracy, latency, and cost.
• Run experiments, track metrics, and iterate for quality.
• Collaborate with AIOps and Security to integrate into CI/CD and prod monitoring.
• Support responsible-AI practices, model cards, and version control.

Skills

Python

ML engineering

LLM frameworks

RAG

Prompt engineering

CI/CD

Kubernetes

Git

Data preprocessing

SQL

Tools

LangChain

LangGraph

AWS Bedrock

SageMaker

Azure

GCP

Vector stores

Embeddings

Job description

About the role

We are looking for an experienced Senior Machine Learning Engineer to join our Product team, in Chiswick, West London,

You will be responsible for building production‑grade AI capabilities across the platform’s generative and agentic paradigms – from retrieval‑augmented knowledge assistants and context‑aware responses to multi‑step agent workflows. The role combines strong machine learning and software engineering skills to deliver grounded, governed, and scalable solutions that move from Lab prototype to Factory production.

Key responsibilities

• Design and implement ML, generative, and agentic AI solutions — RAG pipelines, prompt workflows, tool‑calling agents, and predictive models
• Build grounded retrieval over enterprise knowledge with source citation and tenant isolation
• Integrate models via the model gateway, applying guardrails, PII redaction, and content safety on every request
• Develop and maintain agent orchestration, memory, and human‑in‑the‑loop escalation paths
• Perform data preprocessing, feature engineering, prompt design, and evaluation using enterprise datasets
• Deploy solutions through MLOps/LLMOps pipelines with monitoring, evaluations, and SLAs
• Optimise models and prompts for accuracy, latency, cost, and groundedness
• Run experiments, track metrics against golden sets, and iterate to improve quality
• Collaborate with AIOps and Security to integrate solutions into CI/CD and production monitoring
• Support responsible‑AI practices, model cards, and version control for every release

About you

• 6+ years in AI/ML engineering or applied machine learning
• Strong Python skills with scikit‑learn, TensorFlow, PyTorch, or XGBoost, plus experience with LLM frameworks (LangChain/LangGraph) and RAG
• Experience with cloud AI services (AWS Bedrock/SageMaker, Azure, or GCP) and vector stores
• Proficiency in SQL and working with data warehouses/lakes and embeddings
• Familiarity with MLOps/LLMOps, containerisation (Kubernetes), and CI/CD
• Understanding of prompt engineering, evaluation harnesses, and guardrails
• Strong grasp of ML theory, software engineering practices, and version control (Git)

Benefits

• Competitive salary and incentive scheme
• Warm, supportive, and open company culture
• An opportunity to thrive in a global environment
• Hybrid working: 3 days in the office
• Birthday holiday and option to purchase additional annual leave
• Comprehensive Benefits Package: Private Pension, Private Medical Insurance, Life Assurance and more