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- Tasks: Lead the design and implementation of AI solutions, managing the entire model lifecycle.
- Company: Join a specialist data consultancy focused on impactful AI-driven systems.
- Benefits: Enjoy a collaborative culture with opportunities for continuous learning and development.
- Why this job: Shape the future of AI while working with cutting-edge technology and diverse teams.
- Qualifications: Deep expertise in MLOps tools and strong communication skills are essential.
- Other info: This role requires UK work rights; no visa sponsorship available.
The predicted salary is between 43200 - 72000 £ per year.
A specialist data consultancy is seeking a Machine Learning Specialist / Lead - a technically outstanding individual who thrives on collaboration and delivering meaningful impact. You’ll be passionate about building and scaling intelligent AI solutions, working closely with clients, stakeholders, and cross-functional teams to bring them to life.
This role is pivotal in shaping how the consultancy designs, deploys, and scales AI-driven systems. You’ll take ownership across the entire model lifecycle — from infrastructure and pipeline development to deployment, optimisation, and monitoring. You'll also play a key role in operationalising generative AI solutions, including large language models (LLMs), ensuring they are secure, scalable, and cost-effective.
Role Responsibilities:- Design, implement, and manage scalable and secure infrastructure to support AI/ML workloads
- Build and maintain robust pipelines for model training, validation, deployment, and monitoring
- Act as a trusted technical advisor, understanding client challenges and designing tailored MLOps solutions
- Collaborate with internal teams and clients to translate business needs into practical, scalable AI solutions
- Optimise the performance and reliability of models running in production environments
- Develop and maintain strong client relationships through effective communication and delivery excellence
- Lead technical discovery sessions to identify requirements and key pain points
- Mentor and guide cross-functional teams of ML engineers, data scientists, and consultants, fostering innovation and best practices
- Contribute to thought leadership by participating in industry events and producing content on emerging trends
- Stay ahead of developments in MLOps, DevOps, and AI infrastructure, bringing fresh insights into our work
- Identify skills gaps and support continuous learning through targeted training and development initiatives
- Deep technical expertise in deploying, monitoring, and managing AI/ML solutions in production environments
- Excellent communicator, comfortable working directly with clients and multidisciplinary teams
- Hands-on experience with MLOps tools such as MLflow, DVC, Kubeflow, Docker/Kubernetes, and GitOps practices
- Strong working knowledge of Azure and Databricks services
- Proficient with observability and monitoring tools (e.g. Prometheus, Grafana, Datadog)
- Curious and commercially minded — focused on delivering scalable, valuable solutions
- Familiarity with additional cloud platforms such as AWS or GCP is a plus
- Demonstrated leadership skills, with experience mentoring others and leading delivery efforts
If you’re passionate about data and AI, and ready to take a leading role in a UK-based consultancy at the cutting edge of the industry, we’d love to hear from you.
Applicants must have the right to work in the UK and not require sponsorship now or in the future. Visa sponsorship is not available.
Manager of Machine Learning employer: Alvarium Talent
Contact Detail:
Alvarium Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Manager of Machine Learning
✨Tip Number 1
Network with professionals in the AI and machine learning field. Attend industry events, webinars, or meetups to connect with potential colleagues and clients. Building relationships can often lead to job opportunities that aren't advertised.
✨Tip Number 2
Showcase your expertise by contributing to open-source projects or writing articles on platforms like LinkedIn. This not only demonstrates your knowledge but also positions you as a thought leader in the MLOps community, making you more attractive to employers.
✨Tip Number 3
Prepare for technical interviews by practising common machine learning scenarios and case studies. Be ready to discuss your previous projects in detail, focusing on the challenges faced and how you overcame them, as this will highlight your problem-solving skills.
✨Tip Number 4
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as MLflow, Docker, and Azure. Having hands-on experience or even completing relevant online courses can give you an edge over other candidates.
We think you need these skills to ace Manager of Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML solutions, MLOps tools, and any relevant projects. Use specific examples that demonstrate your technical expertise and leadership skills.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data. Discuss how your background aligns with the role's responsibilities and how you can contribute to the consultancy's goals. Be sure to mention your experience in collaborating with clients and cross-functional teams.
Showcase Relevant Projects: If applicable, include a portfolio or links to projects that showcase your work in deploying and managing AI/ML solutions. Highlight any experience with tools like MLflow, Docker, or Azure, as well as your ability to optimise model performance.
Prepare for Technical Questions: Anticipate technical questions related to MLOps, AI infrastructure, and your problem-solving approach. Be ready to discuss your experience in detail, including challenges faced and how you overcame them.
How to prepare for a job interview at Alvarium Talent
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with MLOps tools like MLflow, DVC, and Kubernetes. Highlight specific projects where you've successfully deployed and managed AI/ML solutions in production environments.
✨Demonstrate Your Communication Skills
Since the role involves working closely with clients and cross-functional teams, practice articulating complex technical concepts in a way that is easy for non-technical stakeholders to understand. Use examples from past experiences to illustrate your points.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Think of scenarios where you had to optimise model performance or address client challenges, and be ready to explain your thought process and the outcomes.
✨Emphasise Your Leadership Experience
As a potential leader in the consultancy, be ready to discuss your mentoring experiences and how you've guided teams in adopting best practices. Share examples of how you've fostered innovation and collaboration in previous roles.
