At a Glance
- Tasks: Join us as an Applied AI Engineer to create impactful AI solutions for diverse customers.
- Company: Snorkel AI is revolutionising AI data development, making machine learning accessible for everyone.
- Benefits: Enjoy remote work options, comprehensive health plans, wellness stipends, and generous parental leave.
- Why this job: Be part of a pioneering team shaping the future of enterprise AI while advancing your career.
- Qualifications: 3+ years in AI/ML solutions, proficient in Python, and strong presentation skills required.
- Other info: This role offers rapid growth opportunities as part of the founding EMEA team.
The predicted salary is between 36000 - 60000 £ per year.
We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before.
As an Applied AI Engineer, you’ll research and utilize established and state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You’ll work directly with our customers to understand their business and technical needs. You will design and deliver AI solutions, either by leveraging Snorkel Flow or developing custom approaches when needed, and collaborate with product and engineering teams to help generalize and integrate these learnings back into the Snorkel Flow platform. We move fast and are constantly prototyping new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, working directly with customers, and bridging the gap between AI technology and business value.
Main Responsibilities:
- Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment.
- Develop and implement state of the art AI techniques such as retrieval-augmented generation (RAG), fine-tuning, prompt engineering, AI agents, ML model training, and optimizing model performance for real-world deployment to maximize business impact.
- Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow.
- Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.
- Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.
- Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
Preferred Qualifications:
- 3+ years of customer-facing experience in the design and implementation of AI/ML solutions.
- Proficient in Python.
- Expertise in AI frameworks and libraries, such as scikit-learn, PyTorch, Hugging Face Transformers, LangChain, and OpenAI APIs.
- Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.
- Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
- Ability to work in a fast-paced environment and balance priorities across multiple projects at once.
- B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.
Compensation depends on level of experience and country. Locations: London (UK) is strongly preferred, but we could consider UK, France, Germany or UAE for the right candidate.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment.
Applied AI Engineer - EMEA New London, UK (Remote) employer: Snorkel AI, Inc.
Contact Detail:
Snorkel AI, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Engineer - EMEA New London, UK (Remote)
✨Tip Number 1
Familiarise yourself with the latest AI and machine learning techniques, especially those mentioned in the job description like retrieval-augmented generation (RAG) and prompt engineering. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the AI field, particularly those who have experience with Snorkel Flow or similar platforms. Attend relevant meetups or webinars to connect with potential colleagues and gain insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss your customer-facing experiences in detail. Think of specific examples where you've successfully collaborated with clients to deliver AI solutions, as this is a key aspect of the role and will demonstrate your ability to bridge technical and business needs.
✨Tip Number 4
Showcase your presentation skills by preparing a mock demo or workshop on a relevant AI topic. This will not only highlight your expertise but also demonstrate your ability to educate and engage stakeholders, which is crucial for this position.
We think you need these skills to ace Applied AI Engineer - EMEA New London, UK (Remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI and machine learning. Focus on projects where you've used Python and specific frameworks mentioned in the job description, such as scikit-learn or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for democratizing AI and how your skills align with Snorkel's mission. Mention specific techniques you’ve worked with, like retrieval-augmented generation or prompt engineering, to demonstrate your expertise.
Showcase Customer-Facing Experience: Since the role involves working directly with customers, highlight any past experiences where you've led discussions or workshops. Provide examples of how you’ve successfully gathered requirements or presented solutions to stakeholders.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail. Brush up on your knowledge of AI frameworks and be prepared to explain how you've applied them in real-world scenarios. This will help you stand out during the interview process.
How to prepare for a job interview at Snorkel AI, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and AI frameworks like scikit-learn, PyTorch, and Hugging Face Transformers. Bring examples of past projects where you successfully implemented machine learning solutions, as this will demonstrate your hands-on expertise.
✨Understand the Business Value
Since the role involves bridging AI technology and business needs, make sure you can articulate how your technical skills translate into real-world business value. Research the company’s clients and think about how your solutions could impact their operations.
✨Prepare for Customer Interaction Scenarios
As this position requires customer-facing experience, be ready to discuss how you've previously gathered requirements or presented solutions to stakeholders. Practice explaining complex concepts in simple terms, as effective communication is key.
✨Demonstrate Problem-Solving Abilities
The role involves solving complex problems, so prepare to discuss specific challenges you've faced in previous roles and how you approached them. Use the STAR method (Situation, Task, Action, Result) to structure your responses effectively.