Forward-Deployed ML Engineer for Real-World Energy AI

Applied Computing; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Applied Computing in the United Kingdom is seeking a Forward Deployed ML Engineer to operationalise Orbital’s AI systems in live industrial environments across cloud, on-prem, and hybrid infrastructures. You will deploy, configure, tune, and productionise ML services, integrate RAG pipelines, and ensure reliability, low latency, and high uptime while collaborating directly with customers.

This role emphasizes hands-on deployment over pure research, with close work alongside data engineers and

Qualifications

• MSc in Computer Science, ML, Data Science, or equivalent practical experience.
• Strong proficiency in Python and deep learning frameworks (PyTorch preferred).
• Solid software engineering background; distributed systems design & debugging.
• Experience building and running Dockerised microservices, ideally with Kubernetes/EKS.
• LLM integrations (OpenAI, Claude, Gemini) and REST inference APIs like FastAPI.
• Familiarity with message brokers (Kafka, RabbitMQ, or similar).
• Comfort in hybrid cloud/on-prem deployments (AWS, Databricks, or industrial environments).
• Exposure to time-series or industrial data (historians, IoT, SCADA/DCS logs) is a plus.
• Domain experience in oil and gas or energy is a plus.
• Ability to work in forward-deployed settings, collaborating directly with customers.

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.

Skills

Python

PyTorch

Docker/Kubernetes

LLM APIs

Kafka/RabbitMQ

FastAPI

Hybrid cloud

Time-series data

Oil & gas domain

Customer-facing

Education

MSc in Computer Science / ML / Data Science or related field

Tools

Docker

Kubernetes

OpenAI API

Claude API

Gemini API

Kafka

RabbitMQ

FastAPI

Job description

Applied Computing in the United Kingdom is seeking a Forward Deployed ML Engineer to operationalise Orbital’s AI systems in live industrial environments across cloud, on-prem, and hybrid infrastructures. You will deploy, configure, tune, and productionise ML services, integrate RAG pipelines, and ensure reliability, low latency, and high uptime while collaborating directly with customers.

This role emphasizes hands-on deployment over pure research, with close work alongside data engineers and