AI /ML Engineer
Indexed description
The AI/ML Engineer works across GLOBO’s modern data stack (Fivetran, dbt, Snowflake) and AI infrastructure (AWS Bedrock, LLMs, agentic frameworks) to deliver reliable, well-tested solutions. This person is equally comfortable wrangling messy data and prompt-engineering an LLM, and takes pride in writing clean, tested code that other engineers can build on.
Key Responsibilities
- Data Engineering & Pipeline Development: Build and maintain ETL/ELT pipelines that move data from source systems into Snowflake via Fivetran and dbt. Clean, validate, and transform raw data into well-modeled datasets ready for analytics and ML workloads. Monitor pipeline health and troubleshoot data quality issues as they arise.
- Model Development, Testing & Evaluation: Build, fine-tune, and evaluate AI/ML models and LLM-based solutions for specific business problems (e.g., automated QA, intelligent routing, context-aware translation aids). Design and run evaluation frameworks to measure model performance, detect hallucinations and bias, and ensure outputs meet GLOBO’s reliability standards for vulnerable populations.
- Feature Development & Integration: Collaborate with Product and Engineering to ship AI-powered features into the GLOBO platform. Build and deploy LLM integrations (AWS Bedrock, Anthropic Claude) and agentic workflows (CrewAI, LangChain). Write production-quality code with proper tests, documentation, and error handling.
- Reliability & Safety: Implement guardrails, monitoring, and alerting for AI services in production. Ensure AI outputs are consistent and trustworthy. Contribute to evaluation datasets, prompt versioning, and regression testing for deployed models.
- Performance & Cost Optimization: Monitor inference latency, token usage, and compute costs across AI services (AWS Bedrock) and data infrastructure (Snowflake). Identify opportunities to improve efficiency without sacrificing quality.
- Bachelor’s Degree in Computer Science, Data Science, Information Systems, or related field.
- 2+ years of experience in data engineering, software development, or ML engineering.
- Experience with the below tech stack is required:
- Python (advanced proficiency)
- SQL (advanced proficiency)
- LLM Integration (AWS Bedrock, Anthropic Claude, or OpenAI API)
- dbt (data transformation and testing)
- Snowflake (or similar cloud data warehouse)
- AWS Lambda / Serverless architecture
- Experience with the below tech stack is preferred:
- Fivetran (or similar ELT/ingestion tooling)
- Agentic Frameworks (CrewAI, LangChain, or similar)
- Airflow (or similar workflow orchestration)
- Vector Databases (Pinecone, PGVector, or OpenSearch)
- AWS ECS/EKS
- CDK and CloudFormation for automated deployments
- Ruby on Rails (ability to read/debug core platform code)
- Redis
- PostgreSQL
- React
- Familiarity with model evaluation techniques, prompt engineering, and AI safety best practices.
- Ability to communicate clearly and effectively verbally and in writing.
- Ability to work independently in a decentralized, hybrid environment.
GLOBO Language Solutions, LLC is an equal opportunity workplace and affirmative action employer. We do not discriminate based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran, or any other characteristic protected by state, federal, or local law.
About GLOBO
GLOBO is a B2B communication platform provider, specializing in translation and interpretation technology, services, data, and insights. For the third year in a row, GLOBO has been ranked in the top-10 on the Philadelphia 100 list of fastest-growing privately held companies.
What’s it like to work here? We’re a close-knit team with big ideas and ambitions. We make the impossible happen, and make hard tasks easier. We don’t take ourselves too seriously, but we’re serious about our mission—helping people communicate when it matters most.
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