At a Glance
- Tasks: Lead the design of cutting-edge ML applications and mentor others in the field.
- Company: Join a leading tech company at the forefront of AI and ML innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Engage in a vibrant community with chances to showcase your expertise at industry events.
- Why this job: Make a real impact by shaping the future of ML solutions for diverse clients.
- Qualifications: Experience in Data Science/ML and a passion for customer-facing roles.
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).
Senior Specialist Solutions Engineer AI ML 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 AI ML, you will not only have the opportunity to work with cutting-edge technologies but also benefit from a supportive environment that encourages professional growth through mentorship and thought leadership. Our commitment to employee development, combined with the dynamic nature of our industry, 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
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that align with the role. This could be anything from GitHub repos to blog posts explaining your thought process—let your work speak for itself!
✨Tip Number 3
Prepare for interviews by diving deep into the latest trends in AI and ML. Brush up on your technical knowledge and be ready to discuss how you've tackled real-world problems using these technologies. Confidence is key!
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Specialist Solutions Engineer AI ML
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your experience in ML and Data Science. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or technologies you've worked with!
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 you can contribute to our team. We love seeing genuine enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills:Don’t forget to include specific examples of your technical expertise, especially in areas like GenAI and MLOps. We’re looking for someone who can hit the ground running, so let us know what tools and frameworks you’re comfortable with!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves!
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 cloud platforms like AWS, Azure, or GCP, and how you've tackled real-world ML challenges.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've solved complex customer business challenges using ML solutions. Think about the architectural designs you've led and how they aligned with client needs—real-world examples will make you stand out.
✨Engage with Technical Scenarios
Expect to dive deep into technical discussions during the interview. Practice explaining your thought process for building MVPs and leading technical sessions. This is your chance to demonstrate your expertise and how you can guide customers effectively.
✨Be a Thought Leader
Highlight any experience you have in creating technical tutorials or leading hackathons. Show that you're not just a techie but also someone who can drive community growth and platform adoption through your knowledge and leadership.
