Sr. Full Stack Engineer

ABOUT THE COMPANY:

This company is building the first A.I., machine learning platform for the $900B US construction lending market. They help banks manage their large and complex construction loan portfolios using intelligent automation and integrated payments. Their software helps lenders, developers, and other stakeholders produce and process this documentation automatically, leading to fewer errors, faster payments, and more profitable loans.

This is a small company with exciting plans for growth, currently YC-backed, and are already working with several of the largest lenders in the industry. You’d be working directly with the founders in a company that values being purposeful, efficient, authentic, transparent, curious, and agile.

TECH THEY USE:

Elixir, Python, React, AWS, Docker, Kubernetes, Postgres, Redis, circleci, sklearn

REQUIREMENTS:

- 4+ years experience in full-stack web development 
- expertise in at least one server-side framework (Phoenix, Ruby on Rails, Django, etc.) 
- experience with React or similar (Angular, Elm, etc.) 
- solid understanding of git 
- experience with Postgres (or another RDBMS) 
- can build quickly without creating a horrible mess

NICE TO HAVES:

- experience with both Elixir and React 
- experience with GraphQL APIs 
- experience with machine learning 
- experience with Kubernetes


Sr. Data Engineer

HireStarter's client is a mission driven start-up looking to stop the spread of infectious disease. This is an opportunity to become a foundational member of the engineering team and design, build, & scale data pipelines, data warehouse, and machine learning infrastructure. You will be a key contributor in designing and building our data platform and delivering robust data pipelines that will ultimately have a meaningful impact for an important social mission.  This role offers a flexible work environment.


Responsibilities:

  • Designing, building, and deploying efficient data pipelines.

  • Intelligently designing and implementing our data architecture.

  • Implementing inclusive data quality checks.

  • Providing data-driven insights.

  • Ensuring scalability.

  • Meeting data privacy and data security standards.

  • Securely source external data from multiple partners

Requirements:

  • 5+ years of experience in data engineering building data warehouses and data pipelines.

  • Built large scale, data driven applications including elements like real-time streaming, batch data aggregation, data modeling, data cleaning, anomaly detection and bulk ingestion.

  • Experience designing and writing robust ETL jobs.

  • Experience with distributed data processing systems (Hive, Spark, Hadoop, etc.)

  • A passion for problem solving and providing solutions.

  • Strong software development skills at least one of the following: (Python, Java, Scala).

  • Extensive experience with SQL.

  • Experience with AWS (EC2, S3, EFS, RDS, DynamoDB, Lambda, Redshift, Kinesis)

  • Strong technical leadership skills.

Data Scientist

Full Stack Data Scientist

Our client serves tens of billions of job advertisement impressions every month. However, they are just starting to drive immense value from this data in the form of information and machine learning models. We are looking for an experienced Full Stack Data Scientist to take a leadership role in our burgeoning Data Science community. Current and future projects may include optimizing search engine yield, job seeker targeting, and personal job recommendations.  This is a high impact role.

 

Candidate Qualifications

  • Gather big data from sources like Spark, Parquet, and HDFS or S3.

  • Model using non-linear algorithms like random forests and gradient boosted trees.

  • Develop the high throughput model serving.

  • Experience with or a desire to learn and apply deep learning.

  • Investigation and development using notebooks like Jupyter or Databricks.

 

Competitive Candidate

  • Experience with deep learning in the natural language processing (NLP) field .

  • Understands the pros and cons of industry machine learning practices.

  • Development experience in a JVM language like Java or Scala.

  • Experience in search, information retrieval, advertisement technology, and/or natural language processing.

  • History of mentoring and leading junior data scientists.