Responsibilities
- Lead applied research initiatives to solve challenging problems in translation and customer support automation
- Design, implement, evaluate, and optimize ML and NLP models for real-world machine translation use cases
- Work with large-scale, multilingual datasets to build accurate and scalable systems
- Develop, optimize, and maintain AI services and supporting infrastructure in production environments
- Contribute to the development of data pipelines and computing infrastructure that support efficient machine translation workflows
Requirements
- 2+ years of relevant industry experience
- Strong understanding of applied AI and machine learning fundamentals
- Proven ability to write clean, maintainable, and well-tested code
- Experience building and consuming APIs (REST and/or gRPC)
- Familiarity with relational and non-relational databases (e.g., PostgreSQL, MongoDB)
- Experience developing and maintaining production systems, with attention to reliability and security
- Experience working in Agile, collaborative development environments
- Professional proficiency in English (written and spoken)
Nice to Have
- Experience with Python web frameworks such as FastAPI or Flask
- Experience deploying and operating LLMs or model serving systems
- Experience owning AI services in production, including monitoring, alerting, and performance tuning
- Hands-on experience with observability tools (e.g., Prometheus, Grafana, PagerDuty)
- Exposure to cloud and DevOps practices (AWS, CI/CD, infrastructure as code such as Terraform)
- Familiarity with microservices architecture and container orchestration (e.g., Kubernetes)
- Contributions to ML/NLP projects (professional or personal) demonstrating practical AI engineering skills
Additional Information
- Professional proficiency in English (written and spoken)
