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UK-Based (On-Site, Hybrid or Remote) We work with a range of UK employers actively hiring across these roles s We're ...

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Selected role

AI/ML Engineers

Concept AI Ltd London, ENG, GB

$69k Senior Full-time

UK-Based (On-Site, Hybrid or Remote)

We work with a range of UK employers actively hiring across these roles

About the Roles

We're looking for experienced AI and Machine Learning Engineers at all levels—from AI Engineer and ML Engineer through to Senior, Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes.

You'll work across the full ML lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do.

Key Responsibilities

Partner with product, data and engineering stakeholders to frame problems suitable for machine learning
Build, train, evaluate and tune models across classical ML, deep learning and generative AI as appropriate
Productionise models—APIs, batch pipelines, real-time inference, model registries
Design and operate ML pipelines covering ingestion, feature engineering, training, evaluation and deployment
Build robust evaluation harnesses—offline metrics, online experiments, guardrails and monitoring
Apply LLMs and generative AI techniques where they're the right tool—RAG, fine-tuning, prompt engineering, agentic patterns
Monitor models in production for drift, degradation, bias and safety concerns
Partner with data engineering peers to build the feature and training data infrastructure ML needs
(For Senior/Lead) Set ML architecture, mentor engineers and scientists, lead applied research initiatives

What You'll Bring

Technical Expertise:

Strong Python skills with the ML stack: NumPy, pandas, scikit-learn
Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX)
Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics
Production ML experience—deploying, serving and monitoring models at scale
LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows)
MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent)
Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering / SQL
Familiarity with experimentation, A/B testing and online evaluation is a plus

Engineering & Soft Skills:

Strong software engineering discipline—models are products, not notebooks
Rigour in evaluation, validation and reproducibility
Scepticism about model behaviour, failure modes and limits
Excellent communication—able to explain a model's behaviour to engineering, product and exec audiences
Comfortable with ambiguity and iterative problem framing
Curiosity about the underlying domain and the user problem the model is serving

Domain Flexibility:

Roles span NLP, computer vision, recommender systems, forecasting, applied generative AI, fraud, personalisation, search and decisioning
Background in any of these is welcomed; appetite to learn an adjacent domain valued just as much

Experience Level:

Minimum 2+ years for AI / ML Engineer, 5+ for Senior, 8+ for Lead / Principal / Applied Scientist
Background in machine learning engineering, applied science, data science with engineering focus, or research engineering
Examples of models, pipelines or ML systems you've taken from idea to production

What We Offer

Opportunity to work on applied AI where models genuinely change product behaviour and business outcomes
Exposure to modern ML platforms, generative AI tooling and production MLOps practice
Roles at the level you're ready for—we're hiring across the IC ML spectrum
A collaborative environment where engineering rigour and modelling depth are both valued
Clear scope to develop specialist depth (LLMs, vision, MLOps, applied research) or stay broad across ML problems
Flexible working arrangements (on-site, hybrid or remote) and supportive team culture

Job Type: Full-time

Pay: £55,000.00-£150,000.00 per year

Benefits:

Flexitime
Work from home

Work Location: Hybrid remote in London W1T

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