Data Engineer (Actifai)

Washington, DC /
Actifai – Engineering /
The Machine Learning team at Actifai (a Foundry portfolio company) is seeking a Data Engineer.

The Company
Actifai is an artificial intelligence company. We help clients – primarily those in the cable and telecom industry – optimize their high value, high leverage decisions. Typically this includes things like customer acquisition, customer retention, and customer development (upsells/cross-sells).  

Actifai was created in the Summer of 2020 in partnership with a major cable operator.  

Actifai is part of, a technology fund/studio that creates AI software companies in partnership with large global enterprises. Foundry’s operating companies focus relentlessly on ‘practical’ applications of AI that cut through the hype cycle and drive immediate, measurable, and recurring improvements to financial performance.  Foundry is backed by approximately $100MM in capital from leading private equity and venture capital partners. 

The Position
The Data Engineer will help design, build, and maintain the systems that process and store our data. We are a lean, agile team where you will have the ability to wear many hats, and have real input into how our platforms are built.

Data at Actifai takes many forms. Some examples include:
- Files processed each day via SFTP transfers from our customers
- Usage data generated and collected by our application
- Feature stores for Machine Learning models
- Records of model outputs

On a given day, you may do any of the following:
- Work with Machine Learning Engineers to deploy infrastructure 
- Work with Data Scientists to understand model inputs and outputs in order to create datasets that power our models
- Build containerized applications for processing data
- Set up monitoring and alerting processes for ETL pipelines

You should have expertise in the design, creation, management, and business use of large datasets. You should have excellent business and communication skills to work with business owners to understand data requirements. You should be skilled at designing, implementing, and operating stable, scalable, low-cost solutions. Above all, be passionate about working with vast data sets and someone who loves to bring datasets together to answer business questions and drive growth. You should have an interest in working with Machine Learning pipelines, though we do not require any specific knowledge of Machine Learning.

Basic Qualifications

    • Bachelor's Degree in Computer Science or a related technical field, with 1-2 years of relevant employment experience
    • Strong skills in writing and optimizing Python
    • Understanding of microservice architecture and containerization (e.g., Docker)
    • Experience with AWS and/or Google CloudExperience with data manipulation libraries such as pandas
    • Detail-oriented and takes ownership of outputs
    • A “do it the right way” mindset including commitment to proper documentation and thorough testing
    • Excellent communication skills, both as a collaborative team member and as an independent worker keeping others apprised of your projects.

Preferred Qualifications

    • Expertise in ETL optimization, designing, coding, and tuning big data processes
    • Experience with data pipelines related to Machine Learning models
    • Experience with Infrastructure as Code (Terraform, Serverless)
Finally, we highlight that excellence has no single mold, particularly in a field as rapidly evolving as AI when looking for candidates that mix business intuition with coding skills. We welcome applications from candidates with diverse backgrounds.

The Interview Process

Actifai interviews share some common features with other companies hiring Software Engineers and Data Scientists, and have some important differences. These differences are a reflection of the roles our employees play, which are focussed on the early stage development of companies where idea generation, product-market fit and partner interaction may be significant aspects of their jobs. 

All our roles have technical interviews that look for core competencies in the day-to-day tools of Machine Learning, and the ability to discuss technical work, formalize generic problems into a quantitative system, problem solve, and act as part of a team.  Many of our interviewees will recognize these as common topics for Data Scientist and Software Engineering roles, although they may find that we ask somewhat more open-ended questions, care more about collaboration, or draw on a mixed pool of skills. 

We also ask case-study type interview questions, which are less usual for technical roles.  For those who have not heard of these interviews, case studies are open-ended business problems that do not have set answers.  They typically require the interviewee to think through the provided information and the context of the problem, decide what is most important, and then build a structure to answer the most important part of the problem (asking the interviewer for further information where appropriate). We ask case studies because Actifai is solving problems that haven't been solved before, and these problems require business-orientated problem-solving and the ability to prioritize in a world of uncertain information and constrained practical actions. 

Our staff will often describe this unique mindset as not only wanting to write code to solve a problem, but also being able to define the problem that we are solving.