Machine Learning Engineer

About Dashlane

Dashlane’s mission is to make security simple for millions of organizations and their people. We empower businesses of every size to protect company and employee data while helping everyone easily log in to the accounts they need—anytime, anywhere. Over 17 million users and 20,000 businesses in 180 countries use Dashlane for a faster, simpler, and more secure internet.

Our global team is united by a strong sense of community and passion for improving the digital experience of our users. Learn more about how we work, how we hire, and the benefits of being a Dashlaner in our Life at Dashlane page.

At Dashlane, we see data as a true and reliable asset: data drives decisions based on timely insights and all teams are empowered to use data in their daily work. We are hiring a Machine Learning Engineer to join our data & analytics team. Helping us to build & productionize impactful and actionable data models to be used in predictive and prescriptive analytics by our stakeholders and analysts teams.

You will play a pivotal role of managing data at rest and in motion along with governance controls empowering  our business & technical users with trusted, timely and actionable data . You will be responsible for bringing robust, efficient, and integrated data models to life. You are expected to roll up your sleeves and deep dive into development on need basis. You should speak the language of business teams and technical teams, able to translate data insights and analysis needs into models. 

Location:
You will be based in Lisbon, with English as your working language. We offer a hybrid work arrangement, with Tuesday being the company day, where we all collaborate in the office and have a company-sponsored meal, a department day for team bonding (will be Thursday for your department), and a third day at your choice. We offer relocation support (national and international).

About our stack:

• Programming language: Python
• Data Platform: AWS [ S3, EC2, ECS, Lambda, Kinesis, Glue & DMS],  MySQL on RDS, Redis
• ETL and ELT Tools: Airbyte and Hightouch
• Data Modeling & Orchestration : DBT and Airflow
• Release management and CI/CD: Gitlab
• BI Tools: Tableau
• Infrastructure provisioning and management: Terraform
• Logging and monitoring: ELK (ElasticSearch, Logstash, Kibana) & AWS Cloudwatch
• Documentation and collaboration tooling: Confluence, Gitlab &  Slack

At Dashlane you will:

• Work with batch and real-time operational and product usage data to build and improve ML models for Dashlane business.
• Prototype machine learning use cases and work with stakeholders to iterate on requirements.
• Develop, productionize, and operate ML models and pipelines at scale.
• Drive end-2-end algorithm development of productionized models i.e. specifications, training data generation, testing , parameter and feature tuning.
• Collaborate with cross functional partners including data engineers, analysts , product managers and business stakeholders to identify opportunities impacting business.
• Identify and articulate areas where data science can help grow company via business operations and product improvements. 
• Communicate exposition of proposed models to technical and functional stakeholders.
• Assist data science team to build  MLops workflows and models for predictive modeling & analytics.

Requirements:

• 3+ years experience in machine learning with an advanced degree in computer science or equivalent.
• Programming experience in Python / Scala / Java or equivalent.
• Working knowledge of machine learning best practices ( e.g. A/B test, feature engineering, feature/model selection), algorithms ( e.g. gradient boosted trees, deep learning / neural networks , optimization and NLP) and domains ( e.g. natural language processing, anomaly detection, personalization and recommendation).
• Experience in technologies such as TensorFlow or SageMaker. 
• Experience in building end-2-end ML infrastructure and/or building and productionizing ML models.
• Fluent in English: verbal and written.

We’re Also Looking For:

• Self-motivated and self-managing, with organizational skills
• Great communication: Regularly achieve consensus amongst technical and business teams
• Demonstrated capacity to communicate complex business activities, technical requirements, and recommendations clearly and concisely
• Ability to thrive in a distributed organization.
• Hands-on experience in data engineering technologies such as Airflow, Kafka, Spark, Kubernetes and data warehouse ( Redshift/Snowflake).
• SaaS industry experience will be a huge plus.
• PhD in Computer Science , Machine Learning, Statistics or related field.

What Dashlane offers you:

• Flex Benefits – monthly amount to be allocated to a pool of benefits of your choice
• Health insurance covered by Dashlane
• Extended time off and well-being days – add 5 days to you vacation quota, plus your birthday day off, and 4 extra days (one per quarter) to acknowledge the importance of your wellbeing
• Equal Parental leave –  regardless of gender, up to 20 weeks fully paid leave to take care of their new baby, within the first year of birth or adoption
• Mentorship program – select your mentor from our internal pool and continue your learning path!
• Flexible working hours – depending on the role, determine a schedule that fits your need, in alignment with your manager
• Donation matching program –  give back to the community and support actions that lead to positive social impact under the historically marginalized communities. Every donation will be matched by Dashlane.
• Mental health services through Spring Health for you and for you and family members
• Team buildings & seasonal social events
• Weekly lunch in the office and monthly happy hour
• and much more

Diversity, Equity, Inclusion and Belonging at Dashlane:

As a truly international company—founded in France and distributed across France, US and Portugal—Dashlane thrives off diverse perspectives. We value all aspects of diversity: gender identity, sexual orientation, ability, ethnic origin, social background, age, lifestyle, and more. We are committed to hiring a diverse community and fostering a culture where everyone is heard and belongs. See more about this here. 

Your interview experience: 

To know what to expect once you’ve sent your application, read about how we interview and hire at Dashlane. Feel free to browse our blog to find more information about our product and how we work.