At Optimizely, we're on a mission to help people unlock their digital potential. We do that by reinventing how marketing and product teams work to create and optimize digital experiences across all channels. With Optimizely One, our industry-first operating system for marketers, we offer teams flexibility and choice to build their stack their way with our fully SaaS, fully decoupled, and highly composable solution.
We are proud to help more than 10,000 businesses, including H&M, PayPal, Zoom, and Toyota, enrich their customer lifetime value, increase revenue and grow their brands. Our innovation and excellence have earned us numerous recognitions as a leader by industry analysts such as Gartner, Forrester, and IDC, reinforcing our role as a trailblazer in MarTech.
At our core, we believe work is about more than just numbers -- it's about the people. Our culture is dynamic and constantly evolving, shaped by every employee, their actions and their stories. With over 1500 Optimizers spread across 12 global locations, our diverse team embodies the "One Optimizely" spirit, emphasizing collaboration and continuous improvement, while fostering a culture where every voice is heard and valued.
Introduction
Our Data Science team harnesses big data, natural language processing, and machine learning to help create next generation products for Optimizely’s Experimentation, CMS, e-commerce, and data platforms.
This team emerged as a result of the acquisition of two start-ups (Peerius and Idio) that provided personalisation products for e-commerce and content. Over the past years, the consolidated company has improved the lives of customers such as Intel, HP, Fitch Ratings, Sainsbury’s and many other brands. Episerver’s acquisition of Optimizely has paved the way for interactions between data-driven experimentation and AI.
This role is within a team whose primary focus lies in the following areas: Natural Language Processing, Machine Learning, and Recommendation Systems. Our stack employs a variety of technologies, including (i) code written in Python, Scala, and TypeScript, (ii) data pipelines using Spark, Luigi, Kubernetes, and Terraform, (iii) prototyping and deploying Machine Learning solutions using Pandas, Scikit-learn, and Dask.
Job Responsibilities
As a Senior Machine Learning Engineer, you will play a pivotal role in developing and implementing advanced ML systems that drive our company's success. In this role, you will independently develop and ship medium to large features, design and implement reliable and scalable machine learning solutions, and collaborate with the Data Science team on projects related to NLP, Recommender Systems, and Predictive modeling.
1. Develop and ship medium to large features independently or with minimal support from other team members
2. Architect, design, and implement reliable, scalable machine learning systems
3. Assist the Data Science team in maintaining and extending projects related to NLP, Recommender Systems, and Predictive modelling
4. Prototype and implement production-ready approaches based on recent research
5. Provide technical mentorship to engineers and demonstrate strong expertise in your field
6. Drive the delivery of high-quality epics in a timely manner, ensuring operational excellence in your services/components
7. Proactively communicate technical decisions, work through conflicts, and partner with Technical Leads on vision and strategy
8. Break down and solve complex problems, make explicit design trade-offs, and perform complex debugging and root cause analysis
9. Actively participate in technical discussions and team meetings
10. Effectively collaborate with cross-disciplinary team members and stakeholders
11. Deliver timely feedback to peers and manager, create an inclusive environment, and play an influential role in hiring, retaining, and growing diversity in the company
12. Apply software engineering and machine learning engineering best practices
Knowledge and Experience
13. 3+ years of hands-on experience in a development team
14. Excellent Python programming skills and experience in software development
15. Strong understanding of Machine Learning, Recommender Systems, and Natural Language Processing
16. Experience designing and shipping ML models to production environments
17. Experience with cloud computing infrastructure (AWS/Azure/GCP)
18. Experience with distributed data processing (Spark or similar cloud services)
19. Experience with data querying
20. Basic understanding of Generative AI and LLMs
21. Experience with source control tools (GitHub/GitLab)
22. Great ability to convey complex concepts to a non-technical audience
23. Understanding of the ML development life cycle and/or prior experience working with teams of ML Engineers
24. Ability to work in an inclusive environment and share our values
25. Continuous learning and improvement mindset
Bonus points:
26. Experience prototyping ideas discussed in research papers into code that can be assessed and benchmarked
27. Experience with Deep Learning / Reinforcement Learning / Statistics applied to Machine Learning
28. Experience with A/B testing
29. Experience with data processing pipeline frameworks (e.g., Luigi or Airflow)
30. Experience working with teams of Data Engineers or Product Managers
31. Experience with functional programming concepts and architecture
Keywords: Machine Learning, Data Science, GenAI, Cloud, Python, Recommendation systems, NLP, Scikit-learn, Pandas, Luigi, Airflow, Docker, Git
Education
Bachelor's or Master's degree in Computer Science, Information Systems, or equivalent
Competencies
Communicating EffectivelyCritical ThinkingManaging MeetingsPrioritizing and Organizing WorkSolving Complex Problems
Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.