Junior LLM Engineer – Entry-Level AI&NLP Developer
Build and refine large language models in Python while launching your Artificial Intelligence career. Apply your academic knowledge to real-world NLP challenges and grow alongside veteran machine-learning mentors.
About the Team
A cross-functional research and product group pushes the limits of generative AI for diverse industries—finance, healthcare, retail, media, and government. You will join data scientists, MLOps engineers, and product strategists who value peer learning, code quality, and rapid experimentation. Remote-first culture lets you work from anywhere in the United States, collaborate through daily stand-ups, and participate in twice-yearly on-site hackathons.
What You’ll Do
- Fine-tune transformer-based large language models using TensorFlow or PyTorch to meet domain-specific quality targets.
- Write clean, testable Python modules that ingest, preprocess, and augment multilingual text corpora.
- Design automated evaluation pipelines that track BLEU, ROUGE, and perplexity metrics.
- Debug inference bottlenecks, memory leaks, and GPU utilization issues—then document fixes for future reference.
- Pair with senior researchers to implement retrieval-augmented generation, prompt engineering, and reinforcement learning from human feedback.
- Maintain and version controlled datasets in Delta Lake or Parquet; ensure compliance with responsible AI guidelines.
- Contribute to sprint planning, scrum ceremonies, and architectural design reviews.
- Support CI/CD deployments on AWS SageMaker and Kubernetes, troubleshooting production incidents as part of a shared on-call rotation.
What You Bring
- Bachelor’s in Computer Science, Data Science, Computational Linguistics, or related discipline.
- 0–2 years of professional experience (internships count) designing NLP or machine-learning projects.
- Proficiency in Python 3.x plus familiarity with Jupyter, NumPy, Pandas, and Hugging Face Transformers.
- Solid grasp of probability, linear algebra, and gradient-based optimization.
- Understanding of Git workflows, unit testing, and agile development.
- Clear written and verbal communication; you explain complex ideas to both engineers and non-technical partners.
- Growth mindset—curiosity, resilience, and readiness to ask “why” until the root cause emerges.
Nice to Have
- Exposure to Rust or Go for high-performance microservices.
- Experience with vector databases such as Pinecone or FAISS.
- Knowledge of HIPAA or PCI compliance when handling sensitive text.
- Participation in Kaggle competitions or published research papers.
Why Join Us
- Immediate ownership of meaningful features that reach millions of users.
- Access to GPU clusters, custom tokenizers, and internal prompt libraries.
- Dedicated education budget for conferences, Coursera courses, and academic journals.
- Mentorship program pairs you with a principal ML scientist for your first year.
- Transparent career ladder that rewards impact, not tenure.
Application Process
Submit your résumé and concise project portfolio. You will solve a short coding exercise and discuss your approach with an engineering manager. Feedback follows within five business days.
Unlock your potential as a Junior LLM Engineer and shape the next generation of conversational AI—starting today.