Salary) We’re working with a major UK government initiative that’s shaping the future of how citizens interact with public services. The programme focuses on harnessing the latest AI technologies to deliver simpler, faster, and more efficient digital experiences across departments. We’re looking for an experienced Cloud & DevOps Engineer to join the AI Customer Experience team - a multidisciplinary … group driving innovation in Generative AI, conversational interfaces, and automation. You’ll design, build, and manage the infrastructure that powers large-scale AI services and agentic workflows across government systems. Key Responsibilities Design and provision secure, scalable cloud infrastructure (AWS, Azure, or GCP) using Python-based Infrastructure as Code (Terraform or Pulumi). Build and optimise CI/CD pipelines … to automate the deployment of AI applications and models (MLOps/LLMOps). Containerise workloads using Docker and manage deployments through Kubernetes (KubeRay, Kubeflow, MLRun, or similar). Provision and manage the infrastructure required to run AI workloads, including vector databases and hyperscaler AI services. Develop automation scripts in Python to streamline operations and reduce manual tasks. Implement comprehensive monitoring More ❯
Salary) We’re working with a major UK government initiative that’s shaping the future of how citizens interact with public services. The programme focuses on harnessing the latest AI technologies to deliver simpler, faster, and more efficient digital experiences across departments. We’re looking for an experienced Cloud & DevOps Engineer to join the AI Customer Experience team - a multidisciplinary … group driving innovation in Generative AI, conversational interfaces, and automation. You’ll design, build, and manage the infrastructure that powers large-scale AI services and agentic workflows across government systems. Key Responsibilities Design and provision secure, scalable cloud infrastructure (AWS, Azure, or GCP) using Python-based Infrastructure as Code (Terraform or Pulumi). Build and optimise CI/CD pipelines … to automate the deployment of AI applications and models (MLOps/LLMOps). Containerise workloads using Docker and manage deployments through Kubernetes (KubeRay, Kubeflow, MLRun, or similar). Provision and manage the infrastructure required to run AI workloads, including vector databases and hyperscaler AI services. Develop automation scripts in Python to streamline operations and reduce manual tasks. Implement comprehensive monitoring More ❯
london (city of london), south east england, united kingdom
Amber Labs
Salary) We’re working with a major UK government initiative that’s shaping the future of how citizens interact with public services. The programme focuses on harnessing the latest AI technologies to deliver simpler, faster, and more efficient digital experiences across departments. We’re looking for an experienced Cloud & DevOps Engineer to join the AI Customer Experience team - a multidisciplinary … group driving innovation in Generative AI, conversational interfaces, and automation. You’ll design, build, and manage the infrastructure that powers large-scale AI services and agentic workflows across government systems. Key Responsibilities Design and provision secure, scalable cloud infrastructure (AWS, Azure, or GCP) using Python-based Infrastructure as Code (Terraform or Pulumi). Build and optimise CI/CD pipelines … to automate the deployment of AI applications and models (MLOps/LLMOps). Containerise workloads using Docker and manage deployments through Kubernetes (KubeRay, Kubeflow, MLRun, or similar). Provision and manage the infrastructure required to run AI workloads, including vector databases and hyperscaler AI services. Develop automation scripts in Python to streamline operations and reduce manual tasks. Implement comprehensive monitoring More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Lorien
or Edinburgh preferred)?? Duration: 6-12 months? Day Rate: Competitive via Umbrella A leading global bank is seeking a skilled Data Engineer to join its next-generation data and AI transformation programme. This contract role offers the chance to work on high-impact initiatives, including powering intelligent chatbots and AI-driven analytics across the organisation. Key Responsibilities: Design, build, and … maintain scalable ETL data pipelines to support AI, chatbot, and analytics use cases. Collaborate with data scientists, ML engineers, and product teams to deliver clean, reliable data for model training and real-time inference. Enable chatbot platforms by integrating structured and unstructured data sources for conversational AI applications. Develop and maintain Tableau dashboards to support data storytelling and operational insights. … Airflow, Informatica, or similar. Advanced SQL skills and experience with large-scale relational and cloud-based databases. Hands-on experience with Tableau for data visualisation and dashboarding. Exposure to AI/ML environments , including data preparation for chatbot training and deployment. Familiarity with chatbot frameworks is a plus Experience with cloud platforms (AWS, GCP, or Azure) and modern data architectures More ❯
Senior Python Engineer | London We’re partnering with a high-growth AI startup that’s building intelligent automation systems designed to simplify complex, real-world operations. Their platform is already redefining how data, workflow, and human decision-making come together — and they’re scaling fast. If you’re excited by the idea of joining an elite engineering team tackling deep … technical problems in AI, automation, and scalable software systems, this could be the role for you. The Role: As a Senior Python Engineer , you’ll take ownership of backend design and development, helping to shape the architecture behind cutting-edge AI-driven platforms. You’ll work closely with AI and product teams to bring intelligent features into production — solving high … impact problems with clean, scalable code. Responsibilities: Architect, design, and build robust backend systems and APIs using Python. Collaborate with AI and data teams to integrate models into production environments. Optimise and scale distributed systems and data pipelines for performance and reliability. Contribute to overall technical strategy, code reviews, and system architecture discussions. Work cross-functionally with design and product More ❯
Senior Python Engineer | London We’re partnering with a high-growth AI startup that’s building intelligent automation systems designed to simplify complex, real-world operations. Their platform is already redefining how data, workflow, and human decision-making come together — and they’re scaling fast. If you’re excited by the idea of joining an elite engineering team tackling deep … technical problems in AI, automation, and scalable software systems, this could be the role for you. The Role: As a Senior Python Engineer , you’ll take ownership of backend design and development, helping to shape the architecture behind cutting-edge AI-driven platforms. You’ll work closely with AI and product teams to bring intelligent features into production — solving high … impact problems with clean, scalable code. Responsibilities: Architect, design, and build robust backend systems and APIs using Python. Collaborate with AI and data teams to integrate models into production environments. Optimise and scale distributed systems and data pipelines for performance and reliability. Contribute to overall technical strategy, code reviews, and system architecture discussions. Work cross-functionally with design and product More ❯
Senior Python Engineer London We're partnering with a high-growth AI startup that's building intelligent automation systems designed to simplify complex, real-world operations. Their platform is already redefining how data, workflow, and human decision-making come together - and they're scaling fast. If you're excited by the idea of joining an elite engineering team tackling deep … technical problems in AI, automation, and scalable software systems, this could be the role for you. The Role: As a Senior Python Engineer , you'll take ownership of backend design and development, helping to shape the architecture behind cutting-edge AI-driven platforms. You'll work closely with AI and product teams to bring intelligent features into production - solving high … impact problems with clean, scalable code. Responsibilities: Architect, design, and build robust backend systems and APIs using Python. Collaborate with AI and data teams to integrate models into production environments. Optimise and scale distributed systems and data pipelines for performance and reliability. Contribute to overall technical strategy, code reviews, and system architecture discussions. Work cross-functionally with design and product More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Senior Python Engineer | London We’re partnering with a high-growth AI startup that’s building intelligent automation systems designed to simplify complex, real-world operations. Their platform is already redefining how data, workflow, and human decision-making come together — and they’re scaling fast. If you’re excited by the idea of joining an elite engineering team tackling deep … technical problems in AI, automation, and scalable software systems, this could be the role for you. The Role: As a Senior Python Engineer , you’ll take ownership of backend design and development, helping to shape the architecture behind cutting-edge AI-driven platforms. You’ll work closely with AI and product teams to bring intelligent features into production — solving high … impact problems with clean, scalable code. Responsibilities: Architect, design, and build robust backend systems and APIs using Python. Collaborate with AI and data teams to integrate models into production environments. Optimise and scale distributed systems and data pipelines for performance and reliability. Contribute to overall technical strategy, code reviews, and system architecture discussions. Work cross-functionally with design and product More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Senior Python Engineer | London We’re partnering with a high-growth AI startup that’s building intelligent automation systems designed to simplify complex, real-world operations. Their platform is already redefining how data, workflow, and human decision-making come together — and they’re scaling fast. If you’re excited by the idea of joining an elite engineering team tackling deep … technical problems in AI, automation, and scalable software systems, this could be the role for you. The Role: As a Senior Python Engineer , you’ll take ownership of backend design and development, helping to shape the architecture behind cutting-edge AI-driven platforms. You’ll work closely with AI and product teams to bring intelligent features into production — solving high … impact problems with clean, scalable code. Responsibilities: Architect, design, and build robust backend systems and APIs using Python. Collaborate with AI and data teams to integrate models into production environments. Optimise and scale distributed systems and data pipelines for performance and reliability. Contribute to overall technical strategy, code reviews, and system architecture discussions. Work cross-functionally with design and product More ❯
london (city of london), south east england, united kingdom
Experis UK
Senior Python Engineer | London We’re partnering with a high-growth AI startup that’s building intelligent automation systems designed to simplify complex, real-world operations. Their platform is already redefining how data, workflow, and human decision-making come together — and they’re scaling fast. If you’re excited by the idea of joining an elite engineering team tackling deep … technical problems in AI, automation, and scalable software systems, this could be the role for you. The Role: As a Senior Python Engineer , you’ll take ownership of backend design and development, helping to shape the architecture behind cutting-edge AI-driven platforms. You’ll work closely with AI and product teams to bring intelligent features into production — solving high … impact problems with clean, scalable code. Responsibilities: Architect, design, and build robust backend systems and APIs using Python. Collaborate with AI and data teams to integrate models into production environments. Optimise and scale distributed systems and data pipelines for performance and reliability. Contribute to overall technical strategy, code reviews, and system architecture discussions. Work cross-functionally with design and product More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
london (city of london), south east england, united kingdom
E-Solutions
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
london (city of london), south east england, united kingdom
Photon
Science Architect will assess the maturity and effectiveness of data science practices across teams, focusing on how data science is structured, executed, and governed within the organization. Unlike the AI Architect, who evaluates individual AI capability, and the Data & AI Architect, who focuses on technical systems and platform maturity, this role centers on evaluating analytical workflows, modeling standards, experimentation culture … used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform, and practice assessments into a unified capability map. • Gap Identification: Identify gaps in model governance, documentation, and model-to-business … data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to More ❯
Software Engineer Term: 6 Months Pay: £888 per day Inside IR35 Location: Kings Cross London Hybrid Our client see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer … side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI, as well as extensive safety and robustness evaluations. We’re looking for a highly skilled machine learning engineer to help us make this vision a reality. Competitive candidates will have a track record of writing … and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills, ideal candidates will demonstrate a keen interest in ethical and safety aspects of using AI in More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Undisclosed
Software Engineer Term: 6 Months Pay: £888 per day Inside IR35 Location: Kings Cross London Hybrid Our client see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer … side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI, as well as extensive safety and robustness evaluations. We’re looking for a highly skilled machine learning engineer to help us make this vision a reality. Competitive candidates will have a track record of writing … and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills, ideal candidates will demonstrate a keen interest in ethical and safety aspects of using AI in More ❯
City Of London, England, United Kingdom Hybrid / WFH Options
Undisclosed
Software Engineer Term: 6 Months Pay: £888 per day Inside IR35 Location: Kings Cross London Hybrid Our client see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer … side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI, as well as extensive safety and robustness evaluations. We’re looking for a highly skilled machine learning engineer to help us make this vision a reality. Competitive candidates will have a track record of writing … and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills, ideal candidates will demonstrate a keen interest in ethical and safety aspects of using AI in More ❯
