Software Engineer - ML/Data Infrastructure

You’ll help in executing the roadmap for data infrastructure and systems to power the world’s first AI recruiter built by Moonhub.

You'll play a pivotal role in the development of tools and infrastructure that democratize data access and enable core capabilities across the organization.

You’ll architect offline and online data pipelines to performantly extract, transform, and load data to power Moonhub’s core search application.

You’ll work closely with ML, search, and product teams to build scalable cloud services that enable our customers to accelerate the candidate discovery and hiring process.

You’ll have the opportunity to design and improve the existing data and ML platform at Moonhub.

Skills & Qualifications

• You possess strong foundational knowledge of software engineering, big data, and ML platform principles.
• 5+ years of experience as a software engineer, with at least 2 years focused on building big-data backed or AI applications.
• You have worked cross-functionally to establish the right overarching data architecture for a company's needs, to build data ingestion (real-time & batch) pipelines using tooling such as Spark and Kafka to build data lakes and/or data warehouses.
• You have worked extensively building ML applications and big data pipelines at scale on cloud platforms such as AWS or GCP.
• You have worked on data or infrastructure-focused engineering teams, particularly ones that own a wide swath of software platforms (hosted or built in-house).
• You have experience with virtualization and cluster management tools, including Docker/Containers, Kubernetes.
• You have strong programming experience with at least one modern language such as Python.
• Ability to adapt to changing project requirements and dynamic customer needs.
• Effective communication skills and the ability to work collaboratively in a team.

Bonus Points

• Experience with ML platforms for LLM’s and operationalizing LLM’s such as OpenAI, Cohere, etc.
• Experience in information retrieval or semantic search using vector databases or Elasticsearch.

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