3,405 Lead Ml Engineer jobs in the United Kingdom

• Lead the design, development, and implementation of AI/ML models and systems.
• Mentor and manage a team of AI/ML engineers.
• Define and drive the technical roadmap for AI/ML initiatives.
• Oversee the end-to-end ML lifecycle, including data pipelines, model training, and deployment.
• Identify and evaluate new AI/ML technologies and methodologies.
• Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
• Ensure the scalability, reliability, and performance of AI/ML systems in production.
• Conduct research and experimentation to advance AI/ML capabilities.
• Establish and enforce best practices for MLOps and model governance.
• Communicate technical findings and strategic recommendations to leadership.

• Master's or PhD in Computer Science, Machine Learning, AI, or a related quantitative field.
• Significant experience in leading AI/ML engineering teams and projects.
• Deep understanding of various ML algorithms (e.g., supervised, unsupervised, deep learning).
• Proficiency in programming languages such as Python, R, or Java.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong knowledge of MLOps principles and tools.
• Experience with cloud platforms (AWS, Azure, GCP) and big data technologies.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong leadership, communication, and interpersonal abilities.

• Lead the design, development, and implementation of advanced AI and Machine Learning models.
• Architect scalable and robust ML systems for various applications, including predictive modeling, natural language processing, and computer vision.
• Collaborate with data scientists to translate research findings into production-ready code.
• Oversee the end-to-end ML lifecycle, from data preprocessing and feature engineering to model training, evaluation, and deployment.
• Mentor and guide a team of AI/ML engineers, fostering a culture of technical excellence and continuous learning.
• Stay at the forefront of AI/ML research and identify opportunities to leverage new technologies and methodologies.
• Develop and maintain MLOps practices for efficient model deployment, monitoring, and retraining.
• Optimize model performance for accuracy, scalability, and efficiency.
• Work closely with software engineering teams to integrate AI/ML models into existing products and platforms.
• Contribute to technical strategy and roadmap development for AI initiatives.
• Present complex technical concepts to both technical and non-technical stakeholders.
• Ensure the responsible and ethical development and deployment of AI systems.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Extensive experience in developing and deploying machine learning models in production.
• Proficiency in programming languages such as Python, with expertise in libraries like TensorFlow, PyTorch, scikit-learn.
• Strong understanding of algorithms, data structures, and software engineering principles.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Proven experience leading technical teams and projects.
• Excellent problem-solving skills and the ability to tackle complex technical challenges.
• Strong communication and interpersonal skills, with the ability to collaborate effectively across teams.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Published research in top-tier AI/ML conferences or journals is highly regarded.

• Lead the design, development, and deployment of machine learning models and AI solutions.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Develop and implement scalable ML pipelines and MLOps practices.
• Optimise model performance, efficiency, and accuracy.
• Mentor and guide junior ML engineers and data scientists.
• Research and evaluate new AI technologies, algorithms, and tools.
• Contribute to the overall AI strategy and technical roadmap.
• Ensure the robust and reliable operation of AI systems in production.
• Document thoroughly all AI models, processes, and deployments.

• Master's or PhD in Computer Science, Machine Learning, AI, or a related field.
• 7+ years of experience in machine learning engineering or a similar role.
• Proven experience in leading ML projects and mentoring teams.
• Strong programming skills in Python and experience with ML libraries (TensorFlow, PyTorch, scikit-learn).
• Expertise in building and deploying ML models in production environments.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Experience with containerisation technologies (Docker, Kubernetes).
• Excellent problem-solving, analytical, and communication skills.
• Demonstrated ability to work effectively in a remote, collaborative environment.

Job Title: Contract Deep Learning Engineer

Location: London (Hybrid or On-site)

Contract Type: 6–12 months (with potential extension)

About the Role:

We are seeking a highly skilled Deep Learning Engineer to join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis.

Key Responsibilities:

• Design and implement deep learning models using frameworks such as PyTorch or TensorFlow.
• Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies.
• Optimize model performance and scalability for production environments.
• Conduct experiments, evaluate model performance, and iterate based on results.
• Maintain clear documentation and contribute to knowledge sharing across the team.
• Stay up-to-date with the latest research and techniques in deep learning.

Required Skills & Experience:

• Proven experience in developing and deploying deep learning models in production.
• Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras).
• Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.).
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow).
• Strong problem-solving skills and ability to work independently in a fast-paced environment.

Preferred Qualifications:

• MSc or PhD in Computer Science, Machine Learning, or related field.
• Experience with large-scale datasets and distributed training.
• Knowledge of model interpretability and responsible AI practices.

Benefits:

• Flexible working arrangements (hybrid or remote options available).
• Opportunity to work on cutting-edge AI projects.
• Collaborative and innovative team environment.

Job Title: Contract Deep Learning Engineer

Location: London (Hybrid or On-site)

Contract Type: 6–12 months (with potential extension)

About the Role:

We are seeking a highly skilled Deep Learning Engineer to join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis.

Key Responsibilities:

• Design and implement deep learning models using frameworks such as PyTorch or TensorFlow.
• Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies.
• Optimize model performance and scalability for production environments.
• Conduct experiments, evaluate model performance, and iterate based on results.
• Maintain clear documentation and contribute to knowledge sharing across the team.
• Stay up-to-date with the latest research and techniques in deep learning.

Required Skills & Experience:

• Proven experience in developing and deploying deep learning models in production.
• Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras).
• Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.).
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow).
• Strong problem-solving skills and ability to work independently in a fast-paced environment.

Preferred Qualifications:

• MSc or PhD in Computer Science, Machine Learning, or related field.
• Experience with large-scale datasets and distributed training.
• Knowledge of model interpretability and responsible AI practices.

Benefits:

• Flexible working arrangements (hybrid or remote options available).
• Opportunity to work on cutting-edge AI projects.
• Collaborative and innovative team environment.

• Leading the design, development, and implementation of advanced AI and machine learning solutions.
• Building, training, and optimizing deep learning models for various applications, including natural language processing, computer vision, and predictive analytics.
• Developing and maintaining robust ML pipelines for data preprocessing, model training, evaluation, and deployment.
• Collaborating with product managers and stakeholders to define AI strategy and roadmap.
• Mentoring and guiding a team of AI and ML engineers, fostering a culture of innovation and technical excellence.
• Researching and evaluating emerging AI technologies and techniques to identify new opportunities.
• Ensuring the scalability, performance, and reliability of AI systems in production.
• Developing and implementing best practices for MLOps, including model versioning, monitoring, and continuous integration/deployment.
• Communicating complex technical concepts to both technical and non-technical audiences.
• Contributing to the company's intellectual property through publications and patents.