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For Companies At a Glance
- Tasks: Develop scalable ML systems and enhance user experiences with AI-powered features.
- Company: Typeform is a leading form builder helping 150,000+ businesses collect data engagingly.
- Benefits: Enjoy a full-time role with opportunities for remote work and a diverse, inclusive culture.
- Why this job: Join a dynamic team transforming data into insights while working on cutting-edge AI technologies.
- Qualifications: 4+ years in ML model deployment; proficiency in Python, AWS, and collaboration skills required.
- Other info: Typeform values diversity and is committed to creating an inclusive workplace.
The predicted salary is between 48000 - 84000 £ per year.
Join to apply for the Sr. Machine Learning Engineer role at Typeform.
About the Company
Typeform is a unique form builder that helps over 150,000 businesses collect data through engaging forms, surveys, and quizzes. We aim to make data collection enjoyable and efficient, with 500 million responses annually, and integrations with tools like Slack, Zapier, and Hubspot.
Team and Role Overview
The Data & Insights team focuses on transforming data into actionable insights via reports, dashboards, and AI/ML models. As a Machine Learning Engineer, your goal will be to develop scalable ML systems to enhance personalized user experiences, working with cross-functional teams to implement models and build AI-powered features, including leveraging LLMs and generative AI.
Key Responsibilities
- Design, develop, and deploy scalable ML solutions using tools like Docker, Kubernetes, MLflow, Kafka, and AWS.
- Implement solutions with vector databases and Kafka for real-time data processing.
- Manage ML workflows with MLflow and automate pipelines with Airflow.
- Optimize infrastructure for reliable, scalable, and cost-effective ML pipelines on AWS.
- Develop generative AI capabilities, evaluate AI applications, and collaborate with teams to align ML initiatives with business goals.
Qualifications
- 4+ years of experience in deploying ML models in production.
- Proficiency in Python, PyTorch, LangChain, Agents.
- Experience with AWS, Kubernetes, Docker, Terraform, Jenkins, CI/CD pipelines.
- Monitoring expertise with Datadog or OpenSearch.
- Experience with FastAPI, Faust, Jupyter, AWS SageMaker, Bedrock.
- Hands-on with Kafka, vector databases, MLflow.
- Deep knowledge of LLMs and generative AI applications.
- Strong collaboration and communication skills.
- Familiarity with Enterprise RAG Systems.
Preferred Skills
- Experience in B2B SaaS environments.
- Knowledge of SQL, Spark, Snowflake, agentic decision-making frameworks.
Additional Information
Typeform values diversity and is an equal-opportunity employer. We foster a respectful, transparent, and inclusive environment, welcoming applicants from all backgrounds.
Job Details
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Job function: Engineering and IT
- Industry: Software Development
Sr. Machine Learning Engineer employer: Typeform
Contact Detail:
Typeform Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Docker, Kubernetes, and AWS. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Engage with the Typeform community on platforms like LinkedIn or GitHub. Sharing insights or contributing to discussions about machine learning and AI can help you get noticed by the hiring team and demonstrate your passion for the field.
✨Tip Number 3
Prepare to discuss your previous experiences in deploying ML models in production. Be ready to share specific examples of challenges you faced and how you overcame them, as this will showcase your problem-solving skills and practical knowledge.
✨Tip Number 4
Highlight your collaboration and communication skills during interviews. Since the role involves working with cross-functional teams, demonstrating your ability to work well with others and convey complex ideas clearly will be crucial.
We think you need these skills to ace Sr. Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with the tools and technologies mentioned in the job description, such as Python, AWS, and Docker. Use specific examples to demonstrate your expertise.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for Typeform and the role. Discuss how your background aligns with their mission of transforming data into actionable insights and mention any relevant projects you've worked on.
Showcase Your Projects: If you have worked on any notable ML projects, especially those involving generative AI or real-time data processing, be sure to include them in your application. Provide links to your GitHub or portfolio if applicable.
Highlight Collaboration Skills: Since the role involves working with cross-functional teams, emphasise your collaboration and communication skills in your application. Mention specific instances where you successfully worked with others to achieve a common goal.
How to prepare for a job interview at Typeform
✨Showcase Your Technical Skills
Be prepared to discuss your experience with the specific tools and technologies mentioned in the job description, such as Python, PyTorch, and AWS. Bring examples of projects where you've successfully deployed ML models in production.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when tackling complex ML challenges, especially those related to real-time data processing and scalable solutions.
✨Highlight Collaboration Experience
Since the role involves working with cross-functional teams, be ready to share examples of how you've collaborated with others in previous roles. Emphasise your communication skills and how you align technical initiatives with business goals.
✨Prepare for Generative AI Discussions
Given the focus on generative AI capabilities, brush up on recent advancements in this area. Be ready to discuss your understanding of LLMs and how they can enhance user experiences, as well as any relevant projects you've worked on.
