At a Glance
- Tasks: Lead the design of ML applications and provide advanced technical support to customers.
- Company: Join a leading tech company focused on Data Intelligence and ML solutions.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic role with opportunities for mentorship and community engagement.
- Why this job: Become a trusted ML expert and make a real impact in innovative projects.
- 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.
- 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 employer: Databricks
At Databricks, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. As a Senior Specialist Solutions Engineer in ML Engineering, you will have the opportunity to work with cutting-edge technologies while mentoring others and driving impactful solutions for our customers. Our commitment to employee growth is evident through continuous learning opportunities and a supportive environment that encourages thought leadership and community engagement.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Specialist Solutions Engineer (SSE), ML Engineering
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities you might not find on job boards.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects and solutions. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to ML engineering. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Senior Specialist Solutions Engineer (SSE), ML Engineering
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 customer-facing roles you've had. 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 perfect fit for our team. Don’t forget to mention any relevant projects or experiences that showcase your expertise.
Showcase Your Technical Skills:In your application, be sure to highlight your hands-on experience with ML technologies and cloud platforms. We love seeing real-world examples of how you've tackled complex challenges, so don’t hold back on those details!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our awesome team at StudySmarter!
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 solutions or provided advanced support during the sales cycle.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions. Prepare to explain your architectural design process for production-grade ML workloads and how you would approach integrating cloud-native services. Practise articulating your thought process clearly and confidently.
✨Demonstrate Your Passion for Learning
This role values lifelong learning, so be ready to discuss how you keep your skills sharp. Share any recent projects, tutorials, or hackathons you've been involved in, and express your enthusiasm for mentoring others and contributing to community growth.
