Remote AI Engineer

N Consulting Ltd
Colchester, UK
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Airflow Amazon Web Services Artificial Neural Networks Computer Vision Microsoft Azure Continuous Integration Information Engineering Data Transformation Python (Programming Language) Machine Learning Natural Language Processing
+17 more
NoSQL Recommender Systems Tensorflow Standard Sql Reinforcement Learning Google Cloud Feature Engineering Data Ingestion Pytorch Large Language Models Generative AI Data Strategy Scikit Learn Kubernetes HuggingFace Machine Learning Operations Docker

Job description

Design, develop, and deploy end-to-end AI/ML solutions from data ingestion to production.

Build and optimize ML/DL models for NLP, computer vision, recommendation systems, and predictive analytics.

Implement and maintain MLOps pipelines (CI/CD for ML) for scalable deployment and monitoring.

Collaborate with cross-functional teams (data scientists, engineers, product managers) to define AI-driven solutions.

Research and integrate Generative AI (LLMs, diffusion models, transformers) into real-world applications.

Drive data strategy, including data collection, preprocessing, and feature engineering.

Optimize models for performance, scalability, and cost-effectiveness in cloud/on-prem environments.

Mentor junior engineers and contribute to best practices in AI development.

Requirements

Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).

Hands-on experience with NLP (LLMs, transformers, embeddings, vector databases).

Deep understanding of neural networks, reinforcement learning, and generative models.

Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).

Strong knowledge of SQL/NoSQL databases and data engineering practices.

Soft Skills: Excellent problem-solving, communication, and leadership abilities.

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