Job Description
We are on a mission to redefine the boundaries of human-machine interaction by building the world's most advanced Generative AI platform. As a Senior Artificial Intelligence Engineer at FutureScale, you will be at the forefront of innovation, architecting the neural architectures that power our next-generation products. If you are a visionary engineer who thrives in a high-velocity, high-impact environment, we want you to help us shape the future of AI.
Why Join Us?
- Unmatched Impact: Work on products used by millions, shaping the future of enterprise automation.
- Premium Compensation: Competitive salary, equity packages, and comprehensive benefits.
- Top-Tier Team: Collaborate with PhDs, researchers, and industry veterans from leading tech giants.
- Flexible Culture: Embrace remote-first flexibility and a culture that prioritizes results over hours.
The Role:
In this pivotal role, you will design, train, and deploy cutting-edge Large Language Models (LLMs) and computer vision systems. You will bridge the gap between theoretical research and production-grade software, ensuring our models are not only accurate but also efficient and scalable.
Responsibilities
- Architect and optimize state-of-the-art Deep Learning models, specifically focusing on Transformers and Generative AI architectures.
- Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model training, fine-tuning, and deployment on cloud infrastructure.
- Collaborate closely with product managers and engineers to translate complex business requirements into robust technical solutions.
- Conduct rigorous experimentation and A/B testing to improve model accuracy, reduce bias, and enhance user engagement metrics.
- Implement MLOps best practices to ensure continuous integration and delivery of high-quality AI models.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field (or equivalent professional experience).
- Proven experience (5+ years) in designing and deploying production-level AI/ML systems in a fast-paced environment.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of NLP, LLMs (GPT, BERT, LLaMA), and prompt engineering techniques.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Strong mathematical foundation in linear algebra, calculus, and probability theory.
- Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.