What we need:
Every week millions of documents are ingested, processed, and reviewed in Logikcull. And every week the amount of data our customers need to sift through grows faster and faster.
We have big plans to revolutionize how our customers search and review documents in Logikcull. From automatically detecting sensitive data in their documents over suggesting review actions based on previous actions to automatically detecting and culling documents that are pure noise.
If you love working with large amounts of data and extracting and presenting insights from large data sets you might be a good fit for the data engineering team at Logikcull.
Come grow your engineering skills and help build a high-impact team.
Who you’ll work with:
You will be working with a growing team of engineers and analysts. The team will be your source of information, inspiration and insights into everything that is Logikcull. This group is the core data group for the company, having eyes on not only incoming data for multiple systems but also creating value through reporting and features directly to the customers. Outside the core team, you will also be interacting with engineers from our frontend, infrastructure and processing teams to be able to bring your models to life.
What you’ll do:
You will implement and support machine learning-assisted features in our product
You will help define and develop our machine-learning architecture
You will help develop some of the models that drive our machine-learning features
You will be an active participant in our data engineering team
What we’re looking for (you!):
You have at least 3 years of experience with machine learning
You have a practical understanding of machine learning models and experience selecting the correct model for a task
You have experience evaluating the performance of machine learning models and the trade-offs involved
You have demonstrable experience using python to deploy and run machine learning processes in a production environment
You have experience building and deploying machine learning models using textual data
Experience with distributed compute (Dask, Spark or similar)
Experience with pipeline orchestration tools (Airflow, Prefect, Step Functions etc.)
Bonus – Experience with automated model training and selection
Bonus – Experience with AWS machine learning products (SageMaker, Comprehend etc.) is a plus
You’re comfortable and efficient in a Linux environment
You’re pragmatic and practical and understand that building a startup requires a constant balancing of competing priorities and weighing of risks and outcomes while setting project roadmaps
You’re willing to participate in our on-call rotation
Join for the amazingly talented and kind people. Stay for the massive customer and market impact. Read what our employees
have to say, and be sure to watch this quick explainer video
. We’re 100% remote/distributed, and staying that way! Our benefits are best in class. And our perks, including $1k/year for WFW (Work From Wherever), company off-sites (see photos
), half-day Fridays, and killer SWAG
make working @ Logikcull even better.
Logikcull is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, pregnancy, marital status, sex, age, sexual orientation, military, and veteran status, registered domestic partner status, genetic information, gender, gender identity, gender expression, or any other characteristic protected by applicable law. All employment is decided on the basis of qualifications, merit, and business need.