AI/ML Engineer

AI/ML Engineer

Posted 1 day ago by N Consulting Global

Negotiable
Undetermined
Hybrid
Edinburgh, Scotland, United Kingdom

Summary: The AI/ML Engineer role in Edinburgh focuses on designing, developing, and implementing AI/ML models and solutions for real-world applications. The position requires collaboration with data engineers and stakeholders to optimize datasets and translate business problems into AI-driven solutions. Candidates should have extensive experience in machine learning pipelines and cloud platforms. The role emphasizes the importance of ethical AI practices and staying current with emerging technologies in the field.

Key Responsibilities:

  • Design, develop, and implement AI/ML models, algorithms, and solutions for real-world problems.
  • Collaborate with data engineers to prepare, clean, and optimize large-scale datasets for AI applications.
  • Build and deploy machine learning pipelines (training, validation, deployment, monitoring, and retraining).
  • Optimize models for scalability, performance, and cost efficiency in production environments.
  • Apply NLP, computer vision, deep learning, or reinforcement learning techniques where applicable.
  • Work with cloud platforms (AWS, Azure, GCP, or Snowflake) to deploy AI solutions at scale.
  • Collaborate with stakeholders to translate business problems into AI-driven solutions.
  • Implement AI observability, governance, fairness, and ethical AI practices.
  • Stay up-to-date with emerging AI/ML research, tools, and technologies.

Key Skills:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
  • Strong programming skills in Python, Java, or C++ with hands-on experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras).
  • Solid understanding of ML algorithms, neural networks, transformers, and statistical methods.
  • Experience with data processing frameworks (Pandas, Spark, SQL, Kafka).
  • Knowledge of cloud AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI).
  • Strong problem-solving and analytical skills with the ability to translate complex problems into implementable AI solutions.
  • Experience in model monitoring, A/B testing, and continuous improvement.

Salary (Rate): undetermined

City: Edinburgh

Country: United Kingdom

Working Arrangements: hybrid

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Role : AI/ML Engineer

Location : Edinburgh

Work Mode: Hybrid

Contract Role

Experience : 8+ Years

Job Description

Key Responsibilities

  • Design, develop, and implement AI/ML models, algorithms, and solutions for real-world problems.
  • Collaborate with data engineers to prepare, clean, and optimize large-scale datasets for AI applications.
  • Build and deploy machine learning pipelines (training, validation, deployment, monitoring, and retraining).
  • Optimize models for scalability, performance, and cost efficiency in production environments.
  • Apply NLP, computer vision, deep learning, or reinforcement learning techniques where applicable.
  • Work with cloud platforms (AWS, Azure, GCP, or Snowflake) to deploy AI solutions at scale.
  • Collaborate with stakeholders to translate business problems into AI-driven solutions.
  • Implement AI observability, governance, fairness, and ethical AI practices.
  • Stay up-to-date with emerging AI/ML research, tools, and technologies.

Required Skills & Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
  • Strong programming skills in Python, Java, or C++ with hands-on experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras).
  • Solid understanding of ML algorithms, neural networks, transformers, and statistical methods.
  • Experience with data processing frameworks (Pandas, Spark, SQL, Kafka).
  • Knowledge of cloud AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI).
  • Strong problem-solving and analytical skills with the ability to translate complex problems into implementable AI solutions.
  • Experience in model monitoring, A/B testing, and continuous improvement.