Key skills
AWSAzureCloudETLGoogle Cloud PlatformJavaScriptPythonSQLAIMachine LearningMLNLPLLMAgenticELTData EngineeringSnowflakeDatabricksGCPGoogle CloudServerlessCommunication
About this role
Role Overview
- Collaborate with cross-functional teams to assist in the design and productionization of machine learning, ML ops, traditional AI, LLMs, and agentic AI solutions
- Support the implementation of application integrations to leverage newly built machine learning, ML ops, traditional AI, LLMs, and agentic AI products
- Assist in building solutions that improve the delivery speed and scalability of data and product pipelines
- Under minimal supervision, work on leveraging managed and serverless cloud offerings for application solutions and data engineering pipelines
- Support client-facing teams by preparing technical documentation and assisting in project communications
- Stay up to date with the latest advancements in data science, machine learning, and AI technologies
Requirements
- Bachelor's degree in Computer Science or a related field
- Familiarity with ETL/ELT concepts and best practices in data engineering
- Proficiency in programming languages such as Python and SQL (JavaScript a plus)
- Experience or coursework with NLP and LLM-based technologies and frameworks
- Exposure to a few major cloud or data platforms (e.g., AWS, GCP, Azure, Snowflake, or Databricks)
- Eagerness to learn and adapt quickly in a fast-paced environment
- Excellent verbal and written communication skills and a team-player attitude
- Strong problem-solving and analytical skills
- 2–4 years of foundational experience in data engineering, data science, or ML/AI roles/internships
Tech Stack
- AWS
- Azure
- Cloud
- ETL
- Google Cloud Platform
- JavaScript
- Python
- SQL
Benefits
- Fully remote
- Flexible Schedule
- Unlimited Paid Time Off (PTO)
- Paid parental/bereavement leave
- Worldwide recognized clients to build skills for an excellent resume
- Top-notch team to learn and grow with