Head Of Machine Learning Operation

The Organisation:
The Ellison Institute of Technology (EIT) works to develop and deploy advanced technology in pursuit of solving some of humanity’s most challenging and enduring problems. Guided by world-leading scientists and entrepreneurs, EIT seeks to accelerate innovation by driving scientific and technological advancements across four humane endeavours: health and medical science, food security and sustainable agriculture, climate change and clean energy, and government innovation and the era of artificial intelligence.
EIT Oxford is a new interdisciplinary research and development facility that bridges The Oxford Science Park and Littlemore. Set for completion in 2026, the state-of-the-art facility will have 30,000m² of research laboratories, an oncology and preventative care clinic, plus educational and meeting spaces. The new facility will further EIT’s current partnership with the University of Oxford and become the new home for Ellison Scholars.
Please visit eit.org for more details.
At the Ellison Institute, we believe that an inclusive, collaborative team atmosphere is just as important to our mission as our scientific aims and methods. We strive to build a supportive environment where everyone feels confident taking creative risks toward innovation. We value emotional intelligence and communicating with empathy and respect for others. We foster a team that is curious, has a deep sense of commitment, responsibility, and the resilience needed to achieve excellence.

The AI Capability Team
We are a collaborative team of world class AI scientists, data scientist, data and software engineers and technologists within the Ellison Institute of Technology. We work across of the humane endeavours, supported by world-class and large-scale compute and data platforms.
Our mission is to harness AI to unlock 10x impact in all of the humane endeavours with current state of the art, and to deliver 100x impact in the future through foundational ML research and novel AI approaches.
We unite through deep collaboration three elements: (1) the expertise of EIT’s scientists and our AI impact teams, deep ties with the world class fundamental AI researchers across Oxford University, and (3) the brilliance of the future leaders funded by the Ellison Scholars network. By doing so, we unlock an additionality that is more than the sum of its parts.
We enable AI to be at the heart of how EIT tackles some of humanity's most pressing and enduring challenges. We will do this across health and medical science, food security and sustainable agriculture, climate change and clean energy, and government innovation and era of artificial intelligence.
Our work leverages the world-renowned AI research from Oxford and beyond, but we don't stop there. We take breakthrough AI research and orient them towards ambitious real-world applications, striving to make a tangible difference to society and people's lives. And by understanding the potential of transforming humanity with science and technology, we help to focus Oxford’s cutting edge research on impact that serves humanity.
Join us in our journey as we unlock the potential of AI to create a better future.

The Role:
The Head of Machine Learning Operations (MLOps) is a strategic Leadership role responsible for overseeing the deployment, management and optimosation of Machime Learning Models and Systems. The role requires a deep understanding of ML Operations, infrastructure management and regulatory compliance. The successful candidate will lead a team of engineers and data scientists to ensure the seamless integration of ML Models into production environments driving forward the Institutes research and development goals.

Duties/Responsibilities:

Infrastructure Management:
Lead the Design and Implementation: Oversee the architecture and maintenance of the infrastructure required for ML operations, including cloud services, data storage solutions, and high-performance computing resources.
Optimise Resource Utilisation: Ensure efficient utilisation of computational resources to support the scaling and deployment of ML models.
Integration with Existing Systems: Collaborate with IT and software engineering teams to integrate ML infrastructure with existing systems and workflows.

Model Lifecycle Management:
Model Deployment: Manage the end-to-end lifecycle of ML models from development to deployment, ensuring models are efficiently transitioned to production.

Model Retraining and Updating: Develop strategies for continuous monitoring, retraining, and updating of ML models to maintain optimal performance and accuracy.
Collaboration with Data Scientists: Work closely with data scientists to translate research models into production-ready systems.

Monitoring and Logging:
Implement Monitoring Systems: Establish and maintain robust monitoring systems to track model performance and operational metrics in real-time.

Log Management: Develop comprehensive logging practices to capture model behaviour and data processing activities for audit and troubleshooting purposes.

Anomaly Detection: Implement automated tools for detecting and responding to anomalies in model performance.

Compliance and Security:
Ensure Regulatory Compliance: Lead efforts to ensure that ML operations comply with relevant regulatory standards, including GDPR, HIPAA, and industry-specific guidelines.

Security Protocols: Develop and enforce security protocols to protect sensitive data and ML models from unauthorised access and breaches.

Ethical AI Practices: Promote ethical AI practices and ensure that deployed models adhere to fairness, accountability, and transparency principles.

Mission Alignment and Adaptability
Passion for leveraging ML to address global challenges and a commitment to EIT’s mission.

Ideal Candidate Profile:

• Education: Master’s or PhD in Computer Science, Data Science, or a related field.
• Experience: Minimum of 10 years in ML or data science roles with at least 5 years in a leadership position.
• Technical Skills: Proficiency in cloud platforms, ML frameworks (TensorFlow, PyTorch), and DevOps tools.
• Compliance Knowledge: Strong understanding of regulatory requirements and best practices in data privacy and security.
• A collaborative mindset with excellent communication skills to effectively work with research teams and stakeholders.
• Demonstrates a dedication to EIT’s cultural principles by being collaborative and inclusive while also taking creative risks to drive innovation.
• Values emotional intelligence and communicates with empathy and respect for others.
• Thrives in a team that is curious, feels a strong sense of responsibility, and possesses the grit to achieve excellence.
• Experience of early-stage research that involves significant scientific discovery in AI and/or other scientific domains like health and medicine, physics, biology etc.
• Experience delivering solutions such as predictive models in domains where harnessing sensitive data ethically is core to the impact of the AI.