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- Tasks: Develop and optimise LLM solutions while collaborating with cross-functional teams.
- Company: Join Databricks, a leading data and AI company trusted by over 10,000 organisations globally.
- Benefits: Enjoy comprehensive benefits, remote work options, and a commitment to diversity and inclusion.
- Why this job: Fuel your curiosity in ML trends and make a real impact in the tech world.
- Qualifications: Experience in Generative AI, data science tools, and a graduate degree in a quantitative field.
- Other info: Opportunity to present at conferences and mentor within the ML community.
The predicted salary is between 43200 - 72000 £ 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. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. 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.
The impact you will have:
- 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.
- Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap.
What we look for:
- 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.
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
- Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
- Passion for collaboration, life-long learning, and driving business value through ML.
- (Preferred) Experience working with Databricks & Apache Spark to process large-scale distributed datasets.
About Databricks:
Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
Commitment to Diversity and Inclusion:
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards.
Sr. Data Scientist / Machine Learning Engineer - GenAI employer: Databricks
Contact Detail:
Databricks Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. Data Scientist / Machine Learning Engineer - GenAI
✨Tip Number 1
Familiarise yourself with the latest trends in Generative AI and Large Language Models. Follow industry leaders on social media, read relevant research papers, and engage in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the data science and machine learning community. Attend meetups, webinars, or conferences related to ML and AI, such as the Data+AI Summit. Building connections can lead to valuable insights and potential referrals for the position at Databricks.
✨Tip Number 3
Showcase your hands-on experience with tools like HuggingFace, Langchain, and cloud platforms such as AWS, Azure, or GCP. Consider working on personal projects or contributing to open-source initiatives that highlight your skills in building and deploying LLM applications.
✨Tip Number 4
Prepare to discuss your experience in mentoring and communicating technical concepts. Think of examples where you've successfully explained complex ideas to non-technical audiences or guided peers in their projects. This will align well with the collaborative culture at Databricks.
We think you need these skills to ace Sr. Data Scientist / Machine Learning Engineer - GenAI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in building Generative AI applications and working with tools like HuggingFace, Langchain, and OpenAI. Emphasise your hands-on industry data science experience and any production-grade machine learning deployments you've worked on.
Craft a Compelling Cover Letter: In your cover letter, express your passion for collaboration and lifelong learning in the field of machine learning. Mention specific projects or experiences that demonstrate your ability to communicate technical concepts to both technical and non-technical audiences.
Showcase Relevant Projects: Include a section in your application that showcases relevant projects or case studies where you developed LLM solutions or optimised ML pipelines. This will help illustrate your practical experience and problem-solving skills.
Highlight Soft Skills: Don't forget to mention your soft skills, such as teamwork and mentorship. The role requires collaboration with cross-functional teams, so demonstrating your ability to work well with others is crucial.
How to prepare for a job interview at Databricks
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Generative AI applications and the tools mentioned in the job description, such as HuggingFace and Langchain. Highlight specific projects where you've built or deployed LLMs, and be ready to explain your approach and the outcomes.
✨Demonstrate Collaboration Skills
Since the role involves working cross-functionally, share examples of how you've successfully collaborated with product and engineering teams in the past. Emphasise your ability to communicate technical concepts to both technical and non-technical audiences.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving skills in data science and MLOps. Practice articulating your thought process when tackling complex data challenges, and consider discussing how you would optimise ML pipelines for customers.
✨Express Your Passion for Lifelong Learning
Convey your enthusiasm for staying updated on the latest trends in machine learning and AI. Share any recent courses, conferences, or workshops you've attended, especially those related to LLMs or MLOps, to demonstrate your commitment to continuous improvement.
