Forward-Deployed ML Engineer: Industrial AI at Scale

Applied Computing; United Kingdom; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Applied Computing is hiring a Forward Deployed ML Engineer to operationalise Orbital’s AI in live industrial environments across cloud, on-premise, and hybrid setups. You will deploy, configure, and tune production AI systems, ensuring reliable inference and practical value in customer workflows.

You’ll work with data scientists and engineers to adapt models to customer data, manage RAG pipelines, and integrate multi-agent systems through robust pipelines and APIs.

Qualifications

• MSc in Computer Science, ML, DS, or equivalent practical experience.
• Strong proficiency in Python and PyTorch.
• Solid software engineering background; distributed systems.
• Experience building Dockerised microservices, with Kubernetes/EKS.
• LLM API integrations (OpenAI, Claude, Gemini).
• Familiarity with message brokers (Kafka, RabbitMQ).
• Comfort in hybrid cloud/on-prem deployments (AWS, Databricks).
• Exposure to time-series or industrial data is a plus.
• Domain experience in oil & gas or energy is a plus.
• Ability to work in forward-deployed settings with customers.
• Comfortable in customer-facing technical roles.
• Strong troubleshooting in production AI systems.

Responsibilities

• Deploy Orbital’s AI/ML services into customer environments.
• Configure inference pipelines across cloud, on-prem, and hybrid infrastructure.
• Package and deploy ML services via Docker/Kubernetes.
• Ensure inference services are reliable, scalable, and production-ready.
• Deploy and tune time-series forecasting and anomaly detection models.
• Adapt models to customer-specific industrial processes.
• Configure thresholds, alerting logic, and detection sensitivity.
• Validate model outputs against engineering expectations.
• Deploy multi-agent AI systems for customer workflows.
• Set up LLM provider integrations and prompt/workflow tuning.
• Deploy RAG pipelines and ingest customer documentation.
• Configure SQL and visualization agents for customer data.
• Generate SHAP explanations and interpretability reports.
• Deploy AI systems into restricted industrial networks.
• Monitor and troubleshoot production deployments.

Skills

Python

Deep learning

Distributed systems

Customer-facing

Troubleshooting

Education

MSc in Computer Science / ML / DS or equivalent

Tools

Docker

Kubernetes / EKS

OpenAI / Claude / Gemini

Kafka / RabbitMQ

REST APIs / FastAPI

Job description

Applied Computing is hiring a Forward Deployed ML Engineer to operationalise Orbital’s AI in live industrial environments across cloud, on-premise, and hybrid setups. You will deploy, configure, and tune production AI systems, ensuring reliable inference and practical value in customer workflows.

You’ll work with data scientists and engineers to adapt models to customer data, manage RAG pipelines, and integrate multi-agent systems through robust pipelines and APIs.