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- Tasks: Lead the design and deployment 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 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 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.
Machine Learning Specialist employer: Alvarium Talent
Contact Detail:
Alvarium Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Specialist
✨Tip Number 1
Familiarise yourself with the latest MLOps tools mentioned in the job description, such as MLflow and Kubeflow. Being able to discuss your hands-on experience with these tools during interviews will demonstrate your technical expertise and readiness for the role.
✨Tip Number 2
Showcase your ability to communicate complex technical concepts clearly. Since this role involves working closely with clients and cross-functional teams, practice explaining your past projects in a way that highlights your collaborative skills and client-focused approach.
✨Tip Number 3
Stay updated on the latest trends in AI and MLOps by attending industry events or webinars. This not only enhances your knowledge but also provides you with talking points that can impress interviewers and show your commitment to continuous learning.
✨Tip Number 4
Prepare examples of how you've optimised AI/ML solutions in production environments. Be ready to discuss specific challenges you faced and how you overcame them, as this will highlight your problem-solving skills and practical experience relevant to the role.
We think you need these skills to ace Machine Learning Specialist
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 with scalable AI solutions, model deployment, and monitoring. This will provide tangible evidence of your capabilities and impact.
Prepare for Technical Questions: Anticipate technical questions related to MLOps, AI infrastructure, and your experience with tools like Azure, Databricks, and Docker/Kubernetes. Be ready to discuss your problem-solving approach and how you've optimised models in production.
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've 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 way that is easy for non-technical stakeholders to understand. This will show your ability to bridge the gap between technology and business needs.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and ability to design tailored MLOps solutions. Think of examples where you've identified client challenges and how you approached them, focusing on the impact of your solutions.
✨Exhibit Leadership and Mentorship Experience
Be ready to discuss your experience in mentoring others and leading delivery efforts. Share specific instances where you've guided cross-functional teams, fostering innovation and best practices in AI/ML projects.
