At a Glance
- Tasks: Join our ML team to develop and optimise cutting-edge LLM solutions for customers.
- Company: Databricks is a leading data and AI company trusted by over 10,000 organisations globally.
- Benefits: Enjoy a collaborative culture, remote work options, and opportunities for professional growth.
- Why this job: Fuel your curiosity in ML while making a real impact with innovative technologies.
- Qualifications: Experience in data science, machine learning tools, and cloud platforms like AWS or Azure required.
- Other info: Present at industry conferences and mentor fellow ML enthusiasts within the company.
The predicted salary is between 28800 - 48000 Β£ per year.
The Machine Learning (ML) Practice team is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation Build, scale, and optimize customer data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains Advise data teams on various data science such as architecture, tooling, and best practices Present at conferences such as Data+AI Summit Provide technical mentorship to the larger ML SME community in Databricks Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI ~ Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch ~ Experience building production-grade machine learning deployments on AWS, Azure, or GCP ~ Passion for collaboration, life-long learning, and driving business value through ML ~[Databricks is the data and AI company. More than 10,000 organizations worldwide β including Comcast, CondΓ© Nast, Grammarly, and over 50% of the Fortune 500 β rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. To learn more, follow Databricks on Twitter ,LinkedIn and Facebook . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. If access to export-controlled technology or source code is required for performance of job duties, it is within Employer\’s discretion whether to apply for a U.
Data Scientist/Machine Learning Engineer employer: Databricks
Contact Detail:
Databricks Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Data Scientist/Machine Learning Engineer
β¨Tip Number 1
Familiarise yourself with the latest trends in Large Language Models (LLMs) and MLOps. Engage with online communities, attend webinars, or follow industry leaders on social media to stay updated. This knowledge will not only help you in interviews but also demonstrate your passion for the field.
β¨Tip Number 2
Network with professionals already working in data science and machine learning roles. Attend relevant conferences, such as the Data+AI Summit, where you can meet potential colleagues and learn more about the company culture at Databricks. Building these connections can provide valuable insights and possibly lead to referrals.
β¨Tip Number 3
Showcase your hands-on experience with tools like TensorFlow, PyTorch, and cloud platforms such as AWS, Azure, or GCP. Consider contributing to open-source projects or creating your own projects that highlight your skills in building production-grade ML applications. This practical experience can set you apart from other candidates.
β¨Tip Number 4
Prepare to discuss your approach to collaboration and mentorship in your previous roles. Since the position involves advising data teams and providing technical mentorship, having examples ready will illustrate your ability to work well with others and contribute to a positive team environment.
We think you need these skills to ace Data Scientist/Machine Learning Engineer
Some tips for your application π«‘
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Data Scientist/Machine Learning Engineer position. Familiarise yourself with the specific skills mentioned in the job description, such as experience with LLMs, MLOps, and relevant tools like HuggingFace and TensorFlow.
Tailor Your CV: Customise your CV to highlight your relevant experience in data science and machine learning. Emphasise your hands-on industry experience, particularly with building production-grade ML deployments and any projects involving generative AI applications.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for collaboration and lifelong learning in the field of machine learning. Mention specific examples of how you've driven business value through ML in previous roles, and express your enthusiasm for working with customers and cross-functional teams.
Showcase Your Projects: If applicable, include links to your GitHub or portfolio where you have showcased relevant projects. Highlight any work related to LLM solutions, data science workloads, or MLOps practices to demonstrate your practical skills and knowledge in the field.
How to prepare for a job interview at Databricks
β¨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with machine learning tools like pandas, scikit-learn, and TensorFlow/PyTorch. Highlight specific projects where you've built or optimised ML pipelines, especially those involving LLMs.
β¨Demonstrate Customer Engagement
Since the role involves working closely with customers, share examples of how you've successfully collaborated with clients in the past. Discuss any professional services engagements you've been part of and how you addressed customer needs.
β¨Stay Updated on Industry Trends
Familiarise yourself with the latest trends in LLMs and MLOps. Be ready to discuss recent advancements or case studies that excite you, as this shows your passion for continuous learning and innovation in the field.
β¨Prepare for Technical Presentations
Given the expectation to present at conferences, practice explaining complex concepts clearly and concisely. Consider preparing a mini-presentation on a relevant topic to demonstrate your communication skills and technical expertise.