Job Detail

Senior ML Engineer (Databricks)

Data Science and AI Full–time
ID: #10841
Posted: 2026-03-09
Salary

Description

Who we are: Kubrick is a next-generation technology consultancy, designed to accelerate delivery and build amazing teams. We deliver services across data, AI, and cloud and we’re building the next generation of tech leaders. Since 2017, we have established a market leading position supporting our clients build their data and technology teams and deliver enduring solutions. The Role: We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our growing community specialising in Databricks. The successful applicant will have a strong background in training models to support a range of problem domains and be well versed in delivering and maintaining models in a production environment through applying MLOps best practice. The role will require familiarity with the relevant capabilities of Databricks and at least one of the major cloud service providers (AWS, Azure, or GCP). Advanced proficiency in Python and SQL is essential and an academic background ground in a related discipline is preferred. As a Senior ML Engineer in our Kubrick Advanced team, you will play a key role in delivering high quality AI/ML and data engineering projects to our clients, with Databricks serving as the primary platform for solution development. You will work closely with Databricks’ professional services teams and client stakeholders to design and implement Lakehouse aligned architectures, leveraging Delta Lake, Unity Catalog, MLflow, and Databricks Model Serving as part of robust end to end solutions. Alongside hands on development, you will frequently take on leadership responsibilities within Kubrick delivery squads, providing technical guidance, enforcing best practices, and ensuring solutions are scalable, secure, and aligned with Databricks standards throughout the project lifecycle. You will also contribute to the ongoing growth and capability development of Kubrick, in strengthening our Databricks delivery proposition. This will include supporting the development of internal accelerators, championing best practice use of the Lakehouse Platform, and assuming line management or technical leadership responsibilities within the team. Key Responsibilities: • Lead technical delivery within Kubrick’s squads deployed on client project engagements, ensuring our solutions follow Databricks Lakehouse best practices and that Kubrick is recognised for the quality, scalability, and robustness of the technical solutions we provide • Work with Kubrick & client staff of other disciplines to understand and assess requirements, design Lakehouse aligned architectures, and inform delivery planning that leverages Databricks capabilities such as Delta Lake, Unity Catalog, MLflow, and Databricks Workflows • Seek, build, and maintain effective client relationships contributing to Kubrick’s commercial priorities while strengthening our collaborative partnership model, particularly in data & AI engagements delivered on Databricks • Line managing developers within the team, supporting their technical development with a focus on Databricks engineering best practices, certified learning paths, and production grade ML delivery standards • Promote a culture of engineering excellence within KA through curiosity, collaboration, and contributions to our internal Databricks knowledge base, accelerators, and delivery playbooks • Actively participate in continuous learning and upskilling, including pursuing Kubrick funded Databricks certifications and engaging in self directed or group learning to ensure your technical capabilities remain modern and industry relevant Required Skills & Experience • Experience in Machine Learning and/or Data Science, including building, deploying, and operating production grade ML model, ideally within a Lakehouse architecture • Hands-on practical experience training, finetuning, and deploying ML models on Databricks, including use of ML flow for tracking and model registry, Model Serving, and Delta Lake as the underlying data layer. Holding a Databricks ML Engineer certification is highly desirable • Strong ability to “pick the right tool for the job,” selecting appropriate modelling approaches, frameworks, and Databricks native capabilities to address a given problem statement. • Awareness of the cost implications of training, finetuning, testing, and serving ML models on Databricks, including cluster configuration, autoscaling, and job orchestration. • Deep AI/ML subject matter expertise, combined with the communication skills needed to explain technical concepts clearly and influence both technical and business stakeholders. • Demonstrable experience in delivery leadership and/or line management, including mentoring junior technical personnel—ideally within a Databrick centric engineering environment. Development opportunities: Kubrick provides all team members with a collaborative and supported environment to progress through a structured career. This career structure provides for increased commercial exposure, technical development, and management and leadership training. You will build your commercial acumen and better understand the impact of project decisions. You will strengthen your ability to adapt your communication styles and messaging to suit different situations. You will gain greater credibility and grow as a leader, understanding how to prioritise team responsibilities and coach team members to deliver great outcomes. As part of this community, you will have the following development benefits and opportunities: • 20 dedicated development days. Four of these will be quarterly collective training days and the remainder will be informed by your own professional development plan. • Support for Professional accreditations in our partner technologies, e.g. Databricks, Azure, AWS etc. • Close collaboration opportunities with principal consultants and senior members of the business. We are proud supporters of Women in Data®. Connect, engage and belong to the largest free female data community in the UK – visit: www.womenindata.co.uk to join our community. Stay connected! Follow us on LinkedIn for updates on career opportunities and more.

Hard Skills 11
Skill Source Confidence
Python llm_hard
100%
SQL llm_hard
100%
Fine-tuning Models llm_hard
100%
Model Deployment llm_hard
100%
MLOps llm_hard
100%
Azure ML llm_hard
80%
Google Cloud AI llm_hard
80%
Model Optimization llm_hard
80%
Data Pipelines llm_hard
80%
Data Infrastructure llm_hard
80%
AWS (SageMaker, EC2, S3) llm_hard
80%
Soft Skills 18
Skill Source Confidence
Cross-Functional Communication llm_soft
100%
Explaining Complex Ideas Clearly llm_soft
100%
Stakeholder Communication llm_soft
100%
Skill Development llm_soft
100%
Self-Improvement llm_soft
100%
Digital Literacy llm_soft
100%
Tech Savviness llm_soft
100%
Leadership llm_soft
100%
People Management llm_soft
100%
Team Leadership llm_soft
100%
Mentoring llm_soft
100%
Collaboration llm_soft
100%
Building Professional Relationships llm_soft
100%
Continuous Learning llm_soft
100%
Technical Writing llm_soft
80%
Documentation llm_soft
80%
Coaching llm_soft
80%
Openness to Feedback llm_soft
80%
Apply Options
Publisher Direct Link
Data - Jobs - Women In Data® No Apply
Indeed No Apply
Glassdoor No Apply
Built In Yes Apply
IT Job Board No Apply
BeBee GB No Apply
SimplyHired No Apply
JobzMall Yes Apply
Data - Jobs - Women In Data® No Apply
API Logs for this Job
Query Country Status Response ms Created
machine learning engineer in London, UK gb duplicate 9358 2026-03-28 10:08
Senior ML Engineer (Databricks) extracted 10064 2026-03-22 02:43
Senior ML Engineer (Databricks) classified 460 2026-03-21 21:05
junior ML engineer in United Kingdom gb processed 22049 2026-03-21 17:00
Raw JSON
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