Staff Data Engineer (100% Remote, @TheMomProject)

Posted 2 years ago  •  50+ applicants
The Mom Project

Staff Data Engineer (100% Remote, @TheMomProject)

The Mom Project - Technology company

Exact compensation may vary based on skills, experience, and location.
40 hrs/wk
Permanent (w2)
Remote work yes (100%)
Travel not required
Start date
July 25, 2022
Preferred skills
Artificial Intelligence
Apache Airflow
Collaborative Filtering
PyTorch (Machine Learning Library)
Deep Learning
Data Lakes
Machine Learning
Application Programming Interface (API)
Full Stack Development
Python (Programming Language)
Docker (Software)
Data Integrity
Natural Language Processing (NLP)
Preferred industry experience
Experience level
5 - 8 years experience

All applicants applying for U.S. job openings must be legally authorized to work in the United States and are required to have U.S. residency at the time of application.

Job description

Why you?

You are a mission driven, customer obsessed, natural problem solver. You dig balanced startup life and can wrestle challenges and change with composure. You are a fearless and collaborative communicator, with the ability to make quick decisions while always in learning mode. You love big, interesting problems and bringing solutions to the masses while making sure it feels personal, authentic and connected. If this sounds like you, we'd like to talk.

Why us?

The Mom Project is a pioneering, remote-first venture-backed startup with roots in Chicago. We are backed by some of the best investors in the world and are lucky to be surrounded by an incredible team of advisors, including Serena Williams.

The Mom Project is a platform and community leading a cultural movement that matches companies with diverse talent. To date, our platform has unlocked over $300M in earning potential by connecting our 650,000+ moms, dads and allies with opportunities at world class brands like Apple, Accenture, Etsy and Nike… and we are just getting started!

Our team is growing as we push to rewrite the narrative for working women at every stage of life. We believe all women should be able to choose both a successful family life AND career aspirations without sacrificing one over the other.

The Mom Project's commitment to Diversity, Equity, and Inclusion

We move forward when we all move together.

At The Mom Project, we understand the Moms we serve are not all the same and neither are the employees that support her. We are inspired by people who come from all walks of life.

Equality and inclusion at TMP is recognizing and honoring the uniqueness of each person who works to bring our mission to life, valuing all dimensions of diversity as our greatest asset.

We are committed to being a safe, respectful, fair, and inclusive culture for all.

About the Role:

We’re looking for a Staff Data Engineer to drive the buildout of our ML/AI end-to-end data pipelines and model deployment infrastructure. This system supports training, evaluation, deployment, and monitoring of our collaborative filtering, natural language processing, and other models. In this position, you will work closely with data scientists, infrastructure engineers, and full-stack web developers. You will ensure that the data we need to drive our ML/AI systems is delivered where we need it, when we need it, in the form that we need.

Our data science team is full-stack, meaning we own the DS process end-to-end from training models to API deployment. We code in Python, and we use technologies like Docker, Redshift and PyTorch. We work in two-week sprints with daily scrums, bi-weekly planning, demos, and retros.

All applicants applying for U.S. job openings must be legally authorized to work in the United States and are required to have US residency at the time of application

What you’ll do:

  • Implement complex data pipelines using Python, AWS cloud services, SQL, Docker, Elasticsearch, Redshift, and other data engineering tools
  • Design and build a next-generation ML/AI infrastructure for training, evaluating, deploying, and monitoring machine learning, natural language processing, and heuristic ML/AI models
  • Participate in the evaluation and selection of tools and technologies to be implemented into our ML/AI infrastructure such as model training tools, model registries, model deployment capabilities, data pipelines, model monitoring, and data management tools
  • Participate in the design and buildout of our data science data lake/data warehouse

The skills and abilities you’ll need to succeed:

  • You have 7-10+ years of professional experience as a data engineer
  • You hold a bachelor’s degree in Computer Science or related discipline or equivalent technology industry experience
  • You have built complex data pipelines using Python, AWS or other cloud service, SQL, and orchestration tools
  • You have interest in or experience with modern machine learning infrastructures and MLOps
  • You are enthusiastic about learning the latest in the AI/ML space including natural language processing with large language models, deep learning techniques, and cutting-edge recommendation algorithms
  • You are familiar with a variety of data engineering tools and technologies such as MySQL, Redshift, Dagster, Airflow, Elasticsearch, Redis
  • You know how to validate and test that your data pipelines work the way they should
  • You have experience building real-time REST APIs
  • You are familiar with Agile and CI/CD practices and tools

Why you’ll love working for TMP:

Compensation & Benefits:

  • Base Compensation
  • Full medical, dental, vision
  • Short and Long Term Disability
  • Generous Paid Parental Leave
  • Family planning benefits through Progyny
  • Generous PTO (that people actually use!)
  • 401K match
  • Career Pathing
  • Flexibility/Autonomy
  • Talkspace

Let me see those Perks, Perks, Perks!

  • An incredible remote team that will support and champion your work
  • Casual Culture: because work should be a place you want to be
  • Health and Wellness stipend
  • Learning and Development stipend
  • Work From Home Stipend

We're just getting started. Join us in building the future of work.