About the role 

Innovid’s  Research, Data and Analytics team, based in Edinburgh and Buenos Aires, is on a mission to ensure that every single ad delivered via any channel forms a meaningful and valuable connection between consumers and brands. We do this by designing, building and launching custom machine learning models to maximise value for publishers and advertisers.

To embark on this mission we are forming a new data engineering function within our RAD team. This function will develop and own our ML infrastructure and help us to scale our bespoke ML services to generate ever more value for publishers and advertisers. If you are a Data Engineer or a Software Development Engineer with passion for ML, then we would love to hear from you. With access to one of the largest and richest datasets in the industry this is your chance to build innovative tech to power the future of TV advertising on a global level.     

You will play an important role in the design, implementation and management of our end to end ML technology architecture. You will build data systems to gather raw data, create features, publish data for model training and inference and monitor data quality. You will also take responsibility for ML Ops. This is a challenging but exciting role in a team that supports each other to succeed. If you can bring  a growth mindset and passion for innovation then this is your opportunity to shine and make a meaningful impact. 

Based in our Edinburgh office, you’ll benefit from a hybrid work model enjoying both in-office collaboration and the flexibility of remote work. 

The Impact You’ll Make: 

• Collaborate with your colleagues in the RAD team and company stakeholders to establish new industry leading ML models and dependent data systems that run continuously in production environments.
• Work autonomously on high-impact projects from inception to deployment.
• Own and maintain ML infrastructure, including data orchestration, feature engineering, feature stores, model libraries and experimentation tools.
• Partner with Data Scientists to define data requirements, build data models, and create features using custom or third-party models.
• Manage data schemas, dictionaries, and quality while optimizing pipelines for cost and efficiency.
• Integrate models into real-time production environments and build the operational tools that we need to monitor model quality in production.
• Develop high level of low level technical designs for the technology that you and others build.  
• Deploy code to production in a continuous manner.
• Support team leads and senior colleagues to scope and stage work into well-defined milestones; make accurate timeline estimates and deliver to those estimates.
• Keep track of projects, tasks and documentation using the Atlassian suite, JIRA/Confluence. 

What You’ll Bring to Us: 

• Highly numerate and educated to degree or postgraduate (MSc) in computer science, and/or machine learning
• +2 years experience working in a ML Data Engineering, ML Ops or Software Development Engineering role and an ability to work within a dynamic technology based environment
• Proficiency in SQL and Python and experience of using data engineering tools, frameworks and storage such as Apache Spark, AWS Glue, AWS S3, AWS Redshift, Snowflake
• Working knowledge of Machine Learning would be a distinct advantage. Especially if you have first hand experience of using TensorFlow, PyTorch, Scikit-learn, NumPy
• Ability to work with terabyte scale data in an efficient manner
• Working knowledge of data structures and databases
• Advanced English with strong written and verbal communication skills 
• Strong collaboration skills and an entrepreneurial mindset

What we will offer you:

• 35 days holiday (including public holidays) 
• Pension plan 
• Employee Assistance Programme 
• Life insurance 
• Cycle to Work Scheme 
• Private medical insurance with Vitality 
• Training & Development sessions with our in-house L&D Platform
• Unlimited office snacks 
• Hybrid working model & good work-life balance 
• RSU’s (Restricted Stock Units) plan 
• Offices in major cities around the world and a cross-company collaboration unlike anywhere else.