Job Description
We are on a mission to redefine the technological landscape for the year 2026 and beyond. As a Senior AI Engineer at FutureScale AI, you will not just build models; you will architect the intelligence that powers our next-generation ecosystem. Join a team of world-class engineers and researchers passionate about pushing the boundaries of Generative AI, Large Language Models (LLMs), and autonomous systems.
In this pivotal role, you will lead the design and implementation of scalable AI solutions that drive core business value. You will work in a fast-paced, high-performance environment where your insights directly influence our product roadmap and our vision for the future.
Why Join Us?
- Impactful Work: Build AI systems that will be used by millions worldwide.
- Future-Forward: Work on cutting-edge projects for the 2026 roadmap.
- Competitive Compensation: Top-tier salary and equity package.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and deep neural networks.
- Lead the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training and productionization.
- Optimize existing models for speed, accuracy, and scalability to handle high-volume data streams.
- Collaborate with cross-functional teams (Product, Engineering, and Design) to translate complex business requirements into technical AI solutions.
- Conduct rigorous A/B testing and model evaluation to ensure product performance and reliability.
- Stay abreast of the latest advancements in AI research (e.g., Transformers, Reinforcement Learning) and integrate relevant innovations into our architecture.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related field (4+ years of relevant industry experience may substitute for a degree).
- Expert proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Proven experience designing and training Large Language Models (LLMs) or Generative AI models.
- Strong understanding of distributed computing, cloud infrastructure (AWS/GCP), and MLOps pipelines.
- Deep knowledge of statistical analysis, optimization techniques, and algorithm design.
- Excellent problem-solving skills and the ability to thrive in ambiguous, fast-paced environments.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.