1,376 to 1,400 of 4,245 Machine Learning Jobs in England

the Role We are seeking an experienced Senior Security Consultant (AI Specialist) to lead the design, strategy, and implementation of secure architectures for AI and machine learning (ML) systems. This senior-level role sits at the intersection of cybersecurity and advanced technology, shaping enterprise security frameworks and ensuring responsible and compliant use of AI across large-scale environments. … You’ll play a strategic role in defining AI/ML security standards, performing risk assessments, and ensuring compliance with key regulations such as GDPR and the EU AI Act. As a thought leader in this space, you’ll influence enterprise-wide security architecture decisions and help guide innovation responsibly and securely. Key Responsibilities Define and deliver enterprise-level AI …/ML security strategies, policies, and standards. Architect secure AI/ML models, platforms, and pipelines, embedding security throughout the lifecycle. Lead AI risk assessments and develop mitigation frameworks for complex and emerging threats. Oversee AI security testing, adversarial validation, and ongoing risk monitoring. Ensure AI compliance with data privacy and regulatory frameworks (GDPR, EU AI Act, ISO 27001). More ❯

the Role We are seeking an experienced Senior Security Consultant (AI Specialist) to lead the design, strategy, and implementation of secure architectures for AI and machine learning (ML) systems. This senior-level role sits at the intersection of cybersecurity and advanced technology, shaping enterprise security frameworks and ensuring responsible and compliant use of AI across large-scale environments. … You’ll play a strategic role in defining AI/ML security standards, performing risk assessments, and ensuring compliance with key regulations such as GDPR and the EU AI Act. As a thought leader in this space, you’ll influence enterprise-wide security architecture decisions and help guide innovation responsibly and securely. Key Responsibilities Define and deliver enterprise-level AI …/ML security strategies, policies, and standards. Architect secure AI/ML models, platforms, and pipelines, embedding security throughout the lifecycle. Lead AI risk assessments and develop mitigation frameworks for complex and emerging threats. Oversee AI security testing, adversarial validation, and ongoing risk monitoring. Ensure AI compliance with data privacy and regulatory frameworks (GDPR, EU AI Act, ISO 27001). More ❯

the Role We are seeking an experienced Senior Security Consultant (AI Specialist) to lead the design, strategy, and implementation of secure architectures for AI and machine learning (ML) systems. This senior-level role sits at the intersection of cybersecurity and advanced technology, shaping enterprise security frameworks and ensuring responsible and compliant use of AI across large-scale environments. … You'll play a strategic role in defining AI/ML security standards, performing risk assessments, and ensuring compliance with key regulations such as GDPR and the EU AI Act. As a thought leader in this space, you'll influence enterprise-wide security architecture decisions and help guide innovation responsibly and securely. Key Responsibilities Define and deliver enterprise-level AI …/ML security strategies, policies, and standards. Architect secure AI/ML models, platforms, and pipelines, embedding security throughout the lifecycle. Lead AI risk assessments and develop mitigation frameworks for complex and emerging threats. Oversee AI security testing, adversarial validation, and ongoing risk monitoring. Ensure AI compliance with data privacy and regulatory frameworks (GDPR, EU AI Act, ISO 27001). More ❯

the Role We are seeking an experienced Senior Security Consultant (AI Specialist) to lead the design, strategy, and implementation of secure architectures for AI and machine learning (ML) systems. This senior-level role sits at the intersection of cybersecurity and advanced technology, shaping enterprise security frameworks and ensuring responsible and compliant use of AI across large-scale environments. … You’ll play a strategic role in defining AI/ML security standards, performing risk assessments, and ensuring compliance with key regulations such as GDPR and the EU AI Act. As a thought leader in this space, you’ll influence enterprise-wide security architecture decisions and help guide innovation responsibly and securely. Key Responsibilities Define and deliver enterprise-level AI …/ML security strategies, policies, and standards. Architect secure AI/ML models, platforms, and pipelines, embedding security throughout the lifecycle. Lead AI risk assessments and develop mitigation frameworks for complex and emerging threats. Oversee AI security testing, adversarial validation, and ongoing risk monitoring. Ensure AI compliance with data privacy and regulatory frameworks (GDPR, EU AI Act, ISO 27001). More ❯

the Role We are seeking an experienced Senior Security Consultant (AI Specialist) to lead the design, strategy, and implementation of secure architectures for AI and machine learning (ML) systems. This senior-level role sits at the intersection of cybersecurity and advanced technology, shaping enterprise security frameworks and ensuring responsible and compliant use of AI across large-scale environments. … You’ll play a strategic role in defining AI/ML security standards, performing risk assessments, and ensuring compliance with key regulations such as GDPR and the EU AI Act. As a thought leader in this space, you’ll influence enterprise-wide security architecture decisions and help guide innovation responsibly and securely. Key Responsibilities Define and deliver enterprise-level AI …/ML security strategies, policies, and standards. Architect secure AI/ML models, platforms, and pipelines, embedding security throughout the lifecycle. Lead AI risk assessments and develop mitigation frameworks for complex and emerging threats. Oversee AI security testing, adversarial validation, and ongoing risk monitoring. Ensure AI compliance with data privacy and regulatory frameworks (GDPR, EU AI Act, ISO 27001). More ❯

the Role We are seeking an experienced Senior Security Consultant (AI Specialist) to lead the design, strategy, and implementation of secure architectures for AI and machine learning (ML) systems. This senior-level role sits at the intersection of cybersecurity and advanced technology, shaping enterprise security frameworks and ensuring responsible and compliant use of AI across large-scale environments. … You’ll play a strategic role in defining AI/ML security standards, performing risk assessments, and ensuring compliance with key regulations such as GDPR and the EU AI Act. As a thought leader in this space, you’ll influence enterprise-wide security architecture decisions and help guide innovation responsibly and securely. Key Responsibilities Define and deliver enterprise-level AI …/ML security strategies, policies, and standards. Architect secure AI/ML models, platforms, and pipelines, embedding security throughout the lifecycle. Lead AI risk assessments and develop mitigation frameworks for complex and emerging threats. Oversee AI security testing, adversarial validation, and ongoing risk monitoring. Ensure AI compliance with data privacy and regulatory frameworks (GDPR, EU AI Act, ISO 27001). More ❯

will work collaboratively with other Data Scientists, Software Engineers, Product and Engagement Managers on projects specific to our Japanese customers. You will not only lead the development of sophisticated ML models but also shape the future of our AI capabilities. You will have the opportunity to mentor junior team members, influence strategic decisions, and directly impact our customers' experiences. If … learning algorithms Support with customer PoVs and onboarding Understand business problems and product requirements and help translate these into technical solutions Execute and deliver full AI/ML solutions from sourcing training data, design and implementing state-of-the-art machine learning models, testing, benchmark and product-driven research for model performance improvement, to shipping stable … into production Strong understanding of software development fundamentals, in particular deploying models to production and how to set up pipelines. Can demonstrate a track record of delivering AI/ML solutions as an individual contributor Demonstrate expertise in deep learning for computer vision, natural language processing, reinforcement learning etc Displays in depth knowledge in machine learning More ❯

building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations. Duties Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake … secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. Abilty to Design, Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leverage Databricks ML and Azure ML to develop predictive models and drive business insights. Design, Monitor and optimize data pipelines and … including Azure Data Lake Storage, Databricks, and Azure Data Factory. Excellent problem-solving and analytical skills and strong communication and teamwork skills. Passion for data and a thirst for learning and is either already a Databricks champion or working towards it Relevant Architecture certifications from Mircosft and Databricks More ❯

systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.This role will report to a Research Manager in the AI Lab. Responsibilities Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices. Explore new data sources … and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/ML, such as: Computer Science, Mathematics, Statistics, Physics, Linguistics, Mechanical Engineering, or related disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, and deploying production-ready … techniques, etc.) Familiarity with PyTorch, PyTorch Lightning, or similar frameworks Strong coding abilities in Python Strong Software development skills and familiarity with GPUs, MLOps, Git, High-performance large-scale ML systems and platforms. Experience with Transformers, LLMs, NLP, Multi-modal Deep Learning, and VLMs/MLLMs Publication track record in machine learning conferences and/or journals More ❯

Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

Manager to lead personalization efforts within their CRM ecosystem. You'll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle-from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

Manager to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product … embeddings and other advanced features to improve relevance and performance. Collaborate with CRM and regional marketing teams to align with campaign goals and customer segmentation strategies Own the full ML lifecycle—from model design to deployment and monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED … learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

An exciting opportunity for an experienced Senior Security Consultant with deep expertise in AI and Machine Learning (ML) Security Architecture. This role focuses on shaping and delivering secure, ethical, and compliant AI/ML strategies for a leading global technology organisation. On Offer Up to £115,000 base salary £4,000 car allowance 15% bonus Comprehensive benefits package … Career growth in a world-class technology environment Key Responsibilities Define and implement AI/ML security strategies, policies, and architectures. Design secure AI/ML models, systems, and data pipelines. Conduct AI risk assessments and develop mitigation strategies. Ensure data security, privacy, and compliance with GDPR, ISO 27001, and the EU AI Act. Lead AI/ML security testing … audits, and adversarial assessments. Skills & Experience Extensive experience in cybersecurity, including AI/ML security architecture. Strong knowledge of AI/ML models, algorithms, and adversarial mitigation. Familiarity with frameworks: NIST, ISO 27001, TOGAF, SABSA. Certifications: CISSP or CISM. Experience with cloud security (Azure, AWS, or GCP). Excellent communication and stakeholder management skills. Eligible for UK Security Clearance (SC More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯