About the job
Req: FEQ127R163
Location: London
Skills: Expertise in Data Science, Machine Learning, Artificial Intelligence, Large Language Models, Generative AI, and Big Data technologies like Spark
As a Specialist Solutions Architect specializing in Machine Learning Engineering, you will serve as a pivotal technical resource for Databricks customers and the Field Engineering team. Collaborating closely with Solution Architects, you will assist customers in designing and implementing production-grade machine learning applications on the Databricks platform, ensuring alignment with the evolving Databricks Data Intelligence Platform roadmap. You will continually advance your technical acumen by leveraging cutting-edge technologies in Generative AI, LLMOps, and Machine Learning, while also enhancing your influence through mentorship and establishing yourself as an authority in ML.
Your Impact:
- Design and architect production-ready ML workloads for customers on our unified platform, which includes comprehensive ML pipelines, optimization for training and inference, integration with cloud-native services, and MLOps practices.
- Deliver advanced technical support to Solution Engineers during the technical sales process, covering aspects from feature engineering and model training to tracking, serving, and monitoring, all within a single integrated platform, and participating actively in the Databricks ML Subject Matter Expert community.
- Work collaboratively with product and engineering teams to voice customer needs, set priorities, and shape the product development roadmap, facilitating the adoption of Databricks’ ML solutions.
- Enhance customer data science capabilities and apply best practices in MLOps to effectively deploy these capabilities across various domains.
- Act as a trusted technical advisor for customers developing Generative AI solutions, including Retrieval-Augmented Generation (RAG) architectures, querying structured data using natural language, content generation, and monitoring solutions.
Qualifications:
- Minimum of 5 years of experience in a customer-facing technical role, with a focus on pre-sales or post-sales support across diverse industry sectors.
- 5+ years of hands-on machine learning experience in at least one of the following roles:
- ML Engineer: Developing production-grade cloud infrastructure (AWS/Azure/GCP) to support the deployment of machine learning applications, including drift monitoring.
- Data Scientist: Proficient in modern natural language processing techniques, including vector databases, fine-tuning of large language models (LLMs), and deploying LLMs using tools such as HuggingFace, Langchain, and OpenAI.
- Graduate degree in a relevant field is preferred.
