We’re looking for a mission-oriented machine learning engineer to help build the recommendation engine for middle-skilled mobility
Changing jobs between industries is incredibly hard, particularly for the 80m working Americans who haven’t gone to college. However, a person’s past work may have given them many of the skills they need to succeed in a seemingly different job.
Last year, we began to investigate how machine learning can make it easier to identify latent talent in this huge segment of the workforce. Reducing the uncertainty in a job transition will have economic as well as social benefits for all stakeholders, including employers, vocational training providers, and workers themselves.
Our new venture, AdeptID, is building a comprehensive recommendation engine connecting talent, demand, and training. Our models are based on real hiring data that allow us to offer insights based on observed outcomes.
We’ve had some exciting progress in our first months since launch:
- We’ve gathered a dataset of over 150,000 observed job transitions and ingested public and commercial data from various providers
- We’ve trained models that, in some cases, are predicting hiring success over 90% of the time – purely on the basis of underlying skills.
- We’re working with a growing cohort of employer and training provider partners who are starting to incorporate these insights into their practices.
This traction is validating, but it’s also a wake-up call that we need to expand our team.
In particular, we need a creative technologist who can help us design and implement the data infrastructure that can ingest diverse and often inconsistent data from public and private sources, build and deploy predictive models, then serve insights to partners via an API. This role would evolve into a technical leadership position in the company.
Our ideal candidate is someone who is:
- Collaborative and mission-oriented self-starter
- Fluent in Python – particularly with data science libraries (NumPy, https://pandas.pydata.org/docs, SciPy, sklearn)
- Proficient in building & maintaining SQL and NoSQL databases
- Experience with Snowflake preferred but not required
- A clear written communicator
- Documentation of code and databases is essential
- Experienced in data visualization and BI tools (like Tableau)
- Experienced in building & deploying scalable machine learning models
- Experience with cloud platforms (AWS) and containerization (Docker) preferred but not required
- Experience developing scalable tools and services for handling machine learning workflows
- Experience designing software architecture and data flows for scalable machine learning development work
We are based in Boston, but there are no geographic requirements for this role. Candidates must have work authorization for the US.We are committed to building a team with diverse perspectives and experiences.
What we can offer
- An important mission
- A fascinating technical problem (i.e. an opportunity to make human capital legible)
- Chance to join an exciting venture at the ground floor
- Competitive early-stage salary and benefits (incl. medical, dental, vision, paid parental leave)
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