Job Description
We are seeking a visionary Senior Machine Learning Engineer to join our elite R&D team. As we prepare to redefine the industry landscape in 2025, you will be at the forefront of developing next-generation Generative AI models. We are looking for a builder who thrives in ambiguity and possesses the technical prowess to turn complex algorithms into scalable, production-ready solutions.
Why Join Us?
- Work on state-of-the-art Large Language Models (LLMs) and Agentic AI frameworks.
- Competitive equity package and flexible remote-first culture.
- Access to top-tier compute resources and cutting-edge research papers.
The Role:
In this pivotal role, you will own the architecture and implementation of our core AI infrastructure. You will collaborate with cross-functional teams of data scientists, engineers, and product managers to deliver products that push the boundaries of artificial intelligence.
Responsibilities
- Design, train, and fine-tune large-scale generative models using transformer architectures.
- Optimize model inference latency and throughput for real-time applications.
- Build robust MLOps pipelines to automate model training, evaluation, and deployment.
- Implement Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and reduce hallucinations.
- Conduct rigorous research to explore novel techniques in NLP and computer vision.
- Ensure data privacy, security, and ethical AI compliance across all models.
Qualifications
- PhD or MS in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience deploying models on cloud infrastructure (AWS, GCP, or Azure).
- Deep understanding of distributed systems and high-scale data processing (Spark, Kafka).
- Track record of publishing in top-tier conferences (NeurIPS, ICML, ACL) is a plus.