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For Companies At a Glance
- 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: Be at the forefront of AI innovation, shaping solutions that make a real difference.
- Qualifications: Deep expertise in MLOps tools and strong communication skills are essential.
- Other info: This role requires UK work eligibility; 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 design, deploy, and scale 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
Skills and experience required:
- 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.
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 Medium or LinkedIn. This not only demonstrates your knowledge but also helps you stand out as a thought leader in the MLOps community.
✨Tip Number 3
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as MLflow, Docker, and Azure. Having hands-on experience with these tools will give you an edge during interviews and discussions.
✨Tip Number 4
Prepare for technical discovery sessions by researching common client challenges in AI/ML. Being able to discuss tailored solutions confidently will demonstrate your ability to act as a trusted advisor and enhance your candidacy.
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 keywords from the job description to demonstrate that you meet the specific requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data, and explain how your skills align with the role. Mention specific experiences where you've successfully implemented AI solutions or led teams.
Showcase Technical Skills: Include a section in your application that details your technical expertise, particularly with tools like MLflow, Docker, and Azure. Provide examples of how you've used these tools in past projects.
Highlight Leadership Experience: Since the role involves mentoring and leading teams, be sure to include any leadership roles you've held. Discuss how you've guided teams in previous positions and the impact of your mentorship.
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 Kubeflow. Highlight specific projects where you successfully deployed and managed AI/ML solutions in production environments.
✨Demonstrate Effective Communication Skills
Since the role involves working closely with clients and multidisciplinary teams, practice articulating complex technical concepts in a clear and concise manner. Prepare examples of how you've effectively communicated with stakeholders in past projects.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Think of scenarios where you've had to optimise model performance or address client challenges, and be ready to explain your thought process and the outcomes.
✨Emphasise Leadership and Mentorship Experience
The consultancy values leadership skills, so be ready to discuss your experience mentoring others and leading delivery efforts. Share specific instances where you fostered innovation and best practices within your team.
