At a Glance
- Tasks: Lead the design of cutting-edge ML applications and support customers in their AI journey.
- Company: Join a leading tech company at the forefront of AI and ML innovation.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Other info: Dynamic role with opportunities to present at conferences and lead hackathons.
- Why this job: Be a key player in shaping the future of AI while mentoring others.
- Qualifications: Experience in Data Science/ML and a passion for customer engagement.
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.
- 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 (AI/ML) in London employer: Databricks
At Databricks, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. As a Senior Specialist Solutions Engineer, you will not only enhance your technical expertise in AI and ML but also enjoy ample opportunities for professional growth through mentorship and community engagement. Our commitment to employee development, combined with the chance to work on cutting-edge technologies, 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 (AI/ML) in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to AI/ML. You never know who might be looking for someone just like you, and personal connections can often lead to job opportunities.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving ML applications. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers and set you apart from the crowd.
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and problem-solving skills. Practice common interview questions and even do mock interviews with friends or mentors to build your confidence and refine your answers.
✨Apply Through Us!
Don’t forget to check out our website for job openings. Applying directly through us not only shows your interest but also gives you a better chance of landing that dream role. We’re always on the lookout for talented individuals like you!
We think you need these skills to ace Senior Specialist Solutions Engineer (AI/ML) 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 Data Science and Machine Learning, and don’t forget to mention any hands-on projects or relevant technologies you've worked with, like GenAI or LLMs.
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 skills align with our mission at StudySmarter. Share specific examples of how you've tackled complex challenges in previous roles.
Showcase Your Technical Skills:In your application, be sure to showcase your technical expertise. Mention any experience you have with cloud platforms like AWS, Azure, or GCP, and highlight your familiarity with tools like HuggingFace or Langchain. We love seeing real-world applications!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at Databricks
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest ML technologies, especially those mentioned in the job description like GenAI and LLMOps. Brush up on your hands-on experience with tools like HuggingFace and Apache Spark, as you might be asked to discuss real-world applications during the interview.
✨Prepare Real-World Examples
Be ready to share specific examples of how you've tackled complex customer challenges using ML solutions. Think about projects where you’ve designed production-grade ML workloads or provided advanced technical support, as these will showcase your expertise and problem-solving skills.
✨Practice Explaining Technical Concepts
Since you'll need to communicate with both technical and non-technical audiences, practice explaining your past projects in simple terms. This will help demonstrate your ability to bridge the gap between complex ML concepts and practical business applications.
✨Show Your Passion for Learning
Highlight your commitment to lifelong learning and staying updated with industry trends. Discuss any recent courses, certifications, or hackathons you've participated in, as this shows you're proactive and genuinely interested in growing within the field.
