At a Glance
- Tasks: Lead the design of cutting-edge ML applications and mentor others in the field.
- Company: Join Databricks, a leader in AI/ML solutions with a focus on innovation.
- Benefits: Enjoy comprehensive benefits, remote work options, and a commitment to diversity.
- Other info: Dynamic environment with opportunities for travel and professional development.
- Why this job: Make a real impact by shaping the future of ML technology and community growth.
- Qualifications: Experience in Data Science/ML and customer-facing roles is essential.
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 organization. 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.
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.
Benefits:
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
Our 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. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance:
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Specialist Solutions Engineer (AI/ML) employer: Databricks Inc.
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. Our commitment to employee growth is evident through continuous learning opportunities, mentorship, and the chance to lead impactful projects in the rapidly evolving field of AI and ML. With a strong focus on diversity and inclusion, we ensure that every team member feels valued and empowered to contribute to our mission of transforming data into actionable insights.
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, especially those at Databricks. Attend meetups or webinars related to AI/ML and don’t be shy about introducing yourself. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that align with what Databricks does. This could be anything from MVPs you’ve built to tutorials you’ve created. It’s a great way to demonstrate your expertise and passion.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss real-world examples of how you've tackled complex challenges. Practice explaining your thought process clearly, as you’ll need to communicate effectively with both technical and non-technical audiences.
✨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 the Databricks team. So, get that application in and let’s make it happen!
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 reflects the skills and experiences that align with the Senior Specialist Solutions Engineer role. Highlight your ML engineering background and any customer-facing experience you've had, as this is key for us.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI/ML and how your expertise can help Databricks customers. Be sure to mention any relevant projects or achievements that showcase your skills.
Showcase Your Technical Skills:In your application, don’t shy away from detailing your hands-on experience with ML technologies and cloud platforms. We want to see your familiarity with tools like Apache Spark, HuggingFace, and any other relevant tech that makes you stand out.
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 team!
How to prepare for a job interview at Databricks Inc.
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially those related to GenAI and LLMOps. Be ready to discuss your hands-on experience with cloud infrastructure and how you've tackled real-world ML challenges.
✨Showcase Your Customer-Facing Skills
Since this role is customer-facing, prepare examples of how you've effectively communicated complex technical concepts to non-technical audiences. Think about times when you've successfully collaborated with clients to solve their business problems.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions during the interview. Be ready to explain your approach to building MVPs and optimising ML workloads. Practise articulating your thought process clearly and confidently.
✨Demonstrate Your Passion for Learning
This role values lifelong learning, so share your enthusiasm for staying updated with the latest technologies in ML. Discuss any recent projects or tutorials you've created that showcase your commitment to community growth and knowledge sharing.