Machine Learning Engineer Databricks in City of Edinburgh
Showing 24 Machine Learning Engineer Databricks jobs in City of Edinburgh
I’m on the lookout for an experienced engineer who can truly bridge the gap between Data Engineering and Data Science. This role is all about leveraging Databricks and Python to design, build, and scale data models that drive genuine business impact.
You’ll be joining a scaling B2B tech company based in Edinburgh city centre - a team tackling complex systems that are ready for serious upgrades and innovation.
The role
- Design, build, and maintain scalable data pipelines within Databricks.
- Deploy, monitor, and support machine learning models in production.
- Take a hands‑on approach to data science, analytics, and ML solutions.
- Continuously optimise data workflows for performance, reliability, and scalability.
What you’ll need
- Proven hands‑on experience with Databricks, Python, PySpark, and SQL.
- Machine learning experience in a cloud environment (AWS, Azure, or GCP).
- Strong understanding of ML libraries such as scikit‑learn, TensorFlow, or MLflow.
- Solid background in data modelling, ELT/ETL processes, and analytics best practices.
If you’re ready to make an impact in a growing tech company and bring your expertise to the table - GET IN TOUCH today!
Equal Opportunity
Bright Purple is an equal opportunities employer: we are proud to work with clients who share our values of diversity and inclusion in our industry.
Lead Machine Learning Engineer – Remote
Our client is a pioneering force in the field of Artificial Intelligence and is seeking an exceptional Lead Machine Learning Engineer to join their fully remote, world‑class team. This is an unparalleled opportunity to architect, develop, and deploy advanced machine learning models that drive innovation across a spectrum of groundbreaking products and services. You will lead a team of talented engineers, pushing the boundaries of AI and shaping the future of intelligent systems.
Key Responsibilities
- Lead the design, development, training, and deployment of state‑of‑the‑art machine learning models and algorithms.
- Architect robust and scalable ML systems for production environments.
- Collaborate with data scientists, researchers, and software engineers to translate business requirements into effective ML solutions.
- Optimize ML models for performance, efficiency, and accuracy.
- Stay at the cutting edge of ML research and development, identifying and implementing new techniques and technologies.
- Mentor and guide junior ML engineers, fostering a culture of technical excellence and continuous learning.
- Oversee the entire ML lifecycle, from data preprocessing and feature engineering to model evaluation and monitoring.
- Ensure the responsible and ethical development and deployment of AI systems.
- Contribute to the strategic direction of the company's AI initiatives.
- Communicate complex technical concepts effectively to both technical and non‑technical stakeholders.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
- Minimum of 7 years of progressive experience in machine learning engineering, with at least 2 years in a leadership or team lead role.
- Proven track record of successfully developing and deploying ML models in production settings.
- Deep expertise in various ML algorithms (e.g., deep learning, reinforcement learning, NLP, computer vision).
- Proficiency in programming languages such as Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit‑learn).
- Strong software engineering skills, including experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Excellent analytical, problem‑solving, and critical‑thinking abilities.
- Exceptional leadership, communication, and interpersonal skills.
- Ability to thrive in a fast‑paced, innovative, and remote work environment.
- A strong portfolio of ML projects or contributions to open‑source ML initiatives is highly desirable.
This fully remote position offers the flexibility to work from anywhere, providing the perfect environment to innovate and lead in the rapidly evolving field of AI. If you are a visionary ML leader ready to make a significant impact, we encourage you to apply.
Principal Machine Learning Engineer – Remote
We are seeking an exceptional Principal Machine Learning Engineer to join a pioneering technology firm that operates on a fully remote basis. Your core focus will be designing, developing, and deploying cutting‑edge machine learning models and systems that solve complex real‑world problems.
Responsibilities
- Lead the design and implementation of scalable machine learning pipelines and infrastructure.
- Develop, train, and evaluate advanced machine learning models for various applications.
- Collaborate closely with data scientists, software engineers, and product managers to translate business needs into technical solutions.
- Mentor and guide junior machine learning engineers, fostering a culture of technical excellence.
- Conduct rigorous research into new ML techniques and technologies, evaluating their potential impact.
- Optimize model performance, efficiency, and deployment strategies.
- Ensure the robustness, scalability, and maintainability of ML systems.
- Contribute to the strategic planning and roadmap for AI and machine learning initiatives.
- Champion best practices in MLOps, including continuous integration, deployment, and monitoring.
- Present complex technical findings and recommendations to both technical and non‑technical audiences.
Qualifications
- Master’s or Ph.D. in Computer Science or related quantitative field.
- Extensive experience (7+ years) in machine learning engineering, with a proven track record of delivering impactful ML solutions.
- Expertise in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit‑learn).
- Strong understanding of various ML algorithms, including deep learning, NLP, and reinforcement learning.
- Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
- Proficiency in MLOps principles and tools for model deployment and management.
- Excellent analytical, problem‑solving, and algorithmic thinking skills.
- Exceptional communication and collaboration skills.
- Experience leading technical projects and mentoring engineers.
Senior Machine Learning Engineer – Generative AI
Our client, a leader in cutting‑edge AI development, is seeking a highly skilled Senior Machine Learning Engineer specializing in Generative AI. This hybrid role combines in‑office collaboration with the flexibility of remote work and is based out of Edinburgh, Scotland.
Key Responsibilities
- Design, develop, and implement state‑of‑the‑art generative AI models (LLMs, GANs, VAEs, diffusion models).
- Build and maintain scalable machine learning pipelines for training, evaluation, and deployment.
- Fine‑tune pre‑trained models for specific downstream tasks and applications.
- Conduct rigorous experimentation and analysis to evaluate model performance and identify areas for improvement.
- Collaborate with researchers to implement and test novel AI architectures and algorithms.
- Optimize models for efficiency, latency, and deployment on various platforms.
- Write clean, well‑documented, and production‑ready code.
- Stay abreast of the latest research and advancements in generative AI and deep learning.
- Mentor junior ML engineers and contribute to team knowledge sharing.
- Participate in code reviews and contribute to best practices in ML engineering.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5–7 years of hands‑on experience in machine learning engineering, focusing on deep learning and generative models.
- Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and Keras.
- Experience with popular generative AI frameworks and tools.
- Strong understanding of model architectures, training methodologies, and evaluation metrics for generative models.
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices.
- Excellent problem‑solving skills and ability to work with large datasets.
- Strong communication and collaboration skills.
- Experience working in a hybrid environment is essential.
Staff Machine Learning Infrastructure Engineer – Redwood City
Location: Redwood City, CA
Hybrid: 2 days onsite per week
Salary: $150‑250K
Required Qualifications
- Bachelor’s degree or higher in Computer Science or a related field.
- At least 7 years of professional experience in the software industry, with a minimum of 2 years in a tech lead role.
- Proven experience with high‑performance computing environments and distributed systems.
- Demonstrated ability to scale ML training systems and optimize resource utilization.
- Hands‑on experience with job scheduling systems and managing cloud GPU environments (GCP, AWS, etc.).
- Deep understanding of distributed computing concepts, including race conditions, memory optimization, and parallel processing.
- Hands‑on experience in ML model tuning for performance.
- Experience with common ML training and inference tools including PyTorch, TensorRT, Triton, Accelerate, etc.
- Strong analytical and problem‑solving skills with the ability to troubleshoot complex system issues.
- Excellent communication skills to collaborate effectively with cross‑functional teams.
Preferred Qualifications
- Experience with container orchestration tools (e.g., Kubernetes) and infrastructure‑as‑code frameworks.
Graduate Software Engineer – AI & Machine Learning (Internship) – Edinburgh
Our client is offering an exceptional internship opportunity for aspiring Graduate Software Engineers based in Edinburgh, Scotland, UK. This role is hybrid and provides valuable experience in the full software development lifecycle.
Responsibilities
- Assist in the development and implementation of AI and machine learning algorithms.
- Write clean, efficient, and well‑documented code in Python or other relevant languages.
- Participate in data collection, cleaning, and preprocessing for model training.
- Collaborate with senior engineers on model development, testing, and validation.
- Contribute to the design and architecture of AI‑powered software solutions.
- Research and evaluate new AI technologies and methodologies.
- Assist in the deployment and integration of machine learning models into existing systems.
- Participate in code reviews and team discussions.
- Document technical specifications and project progress.
Qualifications
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.
- Strong programming skills in Python, Java, or C++.
- Foundational knowledge of machine learning concepts, algorithms, and libraries (e.g., TensorFlow, PyTorch, scikit‑learn).
- Understanding of data structures and algorithms.
- Excellent analytical and problem‑solving abilities.
- Strong communication and teamwork skills.
- Eagerness to learn and adapt to new technologies.
- Ability to work effectively in a hybrid remote and in‑office environment.
Lead Data Scientist – Edinburgh
Our client, a prestigious financial institution in Edinburgh, is seeking a highly skilled and experienced Lead Data Scientist to spearhead advanced analytics initiatives. This role is hybrid, combining office and remote work.
Key Responsibilities
- Leading the design, development, and deployment of advanced machine learning models.
- Mentoring and managing a team of data scientists, fostering their professional growth.
- Identifying and exploring new data sources and analytical opportunities.
- Collaborating with cross‑functional teams to deliver data‑driven solutions.
- Communicating complex technical findings to diverse audiences.
- Ensuring the quality, scalability, and robustness of data science solutions.
- Staying current with the latest research and techniques in AI and machine learning.
- Contributing to the development of the company's data strategy and roadmap.
- Developing and maintaining production‑level machine learning pipelines.
- Driving best practices in data science, coding, and experimentation.
Qualifications
- Master’s or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics).
- Proven experience as a Data Scientist, with a significant focus on machine learning.
- Demonstrated experience in leading data science projects or teams.
- Expertise in Python or R, and SQL.
- Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning).
- Experience with big data technologies (e.g., Spark, Hadoop).
- Familiarity with cloud computing platforms (AWS, Azure, GCP).
- Excellent problem‑solving, analytical, and communication skills.
Equal Opportunity Statement
Our client is an equal opportunities employer and promotes diversity and inclusion in the workplace. We encourage applications from all qualified individuals.
