At a Glance
- Tasks: Lead the design of production-grade ML applications and support customers with advanced technical solutions.
- Company: Join a leading tech company focused on Data Intelligence and ML innovation.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to mentor and lead industry events.
- Why this job: Become a trusted ML expert and make a real impact in the tech community.
- Qualifications: Experience in Data Science/ML and strong customer-facing skills required.
The predicted salary is between 70000 - 90000 £ per year.
As a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself as an ML expert. You will be reporting to the Manager, Field Engineering (Specialist Team).
The Impact You Will Have
- Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services.
- Provide advanced technical support to the Solution Architects during the technical sales cycle by building MVPs, leading deep-dive technical sessions, and strategically aligning ML/data science solutions to complex customer business challenges using relevant real-world examples.
- Serve as the trusted technical advisor for customers developing GenAI solutions, specializing in the design and implementation of RAG architectures on enterprise knowledge bases, enabling natural language querying of structured data, and establishing content generation and monitoring frameworks.
- Drive community growth and platform adoption through thought leadership activities, including the creation of technical tutorials and training materials, as well as leading hackathons and presenting at industry conferences.
What We Look For
- Experienced, technical, customer-facing, and with a background in Data Science / Machine Learning and Data Engineering.
- Looking to learn and develop in a customer-facing technical role as a subject matter expert (SME) in a pre-sales environment.
- Pre-sales or post-sales experience working with external clients across a variety of industry markets.
Data Science/ML Skills
- Hands-on industry ML experience in at least one of the following:
- ML Engineer: Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
- Data Scientist: Experience with the latest techniques in natural language processing, including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI.
- Hands-on experience working with Distributed Spark based systems.
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
- Experience communicating and teaching technical concepts to non-technical and technical audiences alike.
- Passion for collaboration, life-long learning, and driving our values through ML.
- (Preferred) 2+ years customer-facing experience in a pre-sales or post-sales role.
- (Preferred) Experience working with Apache Spark to process large-scale distributed datasets.
- Can meet expectations for technical training and role-specific outcomes within 3 months of hire.
- Can travel up to 30% when needed.
Senior Specialist Solutions Engineer (SSE), ML Engineering in London employer: Databricks
At Databricks, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Specialist Solutions Engineer in ML Engineering, you will have access to cutting-edge technologies and the opportunity for continuous professional growth through mentorship and thought leadership initiatives. Our commitment to employee development, combined with a supportive environment that encourages creativity and knowledge sharing, makes Databricks a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Specialist Solutions Engineer (SSE), ML Engineering in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to ML and Data Engineering. The more people you know, the better your chances of landing that dream job.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving ML applications. Share your work on platforms like GitHub or even your own website. This gives potential employers a taste of what you can do!
✨Ace the Interview
Prepare for technical interviews by brushing up on key concepts in ML and Data Science. Practice explaining complex ideas in simple terms, as you'll need to communicate effectively with both technical and non-technical audiences.
✨Apply Through Us!
Don't forget to check out our website for open positions! Applying directly through us not only shows your interest but also gives you a chance to stand out in the application process.
We think you need these skills to ace Senior Specialist Solutions Engineer (SSE), ML Engineering in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Specialist Solutions Engineer role. Highlight your experience in ML engineering and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about ML and how your background makes you a great fit for our team. Don’t forget to mention any customer-facing experience you have, as that’s super important for us.
Showcase Your Technical Skills:In your application, be sure to showcase your hands-on experience with ML tools and technologies. Whether it's working with cloud infrastructure or deploying LLMs, we want to know how you've applied your skills in real-world scenarios.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Databricks
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially around MLOps and GenAI. Be ready to discuss your hands-on experience with tools like HuggingFace and Apache Spark, as well as any real-world examples of how you've tackled complex ML challenges.
✨Showcase Your Customer-Facing Skills
Since this role is customer-facing, prepare to share experiences where you've successfully communicated technical concepts to non-technical audiences. Think about specific instances where you’ve guided clients through technical sales cycles or provided advanced support.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions during the interview. Prepare to explain your architectural design process for production-grade ML workloads and how you would approach building MVPs. Practise articulating your thought process clearly and confidently.
✨Demonstrate Your Passion for Learning
This role values lifelong learning and mentorship. Be ready to discuss how you stay updated with the latest ML technologies and how you’ve contributed to community growth, whether through tutorials, hackathons, or presentations at conferences.
