Job Description
Are you ready to architect the future?
At FutureScale Technologies, we are pioneering the infrastructure for the next decade. As a Senior AI/ML Engineer, you will be at the forefront of developing next-generation artificial intelligence systems designed to solve complex global challenges. We are looking for a visionary technologist who isn't just building models for today, but is engineering the breakthroughs that will define the year 2026 and beyond.
Why join us?
- Work on cutting-edge Generative AI and Large Language Models (LLMs).
- Competitive equity and stock options in a high-growth unicorn.
- Flexible remote-first culture with quarterly in-person innovation summits.
- Access to the latest hardware and cloud infrastructure.
The Role:
We are seeking a hands-on Senior Engineer to lead our core AI research team. You will own the end-to-end lifecycle of machine learning models, from initial research and prototyping to production deployment at scale. You will define the technical roadmap for our 2026 vision, ensuring our AI systems are ethical, scalable, and transformative.
Responsibilities
- Architect and deploy scalable Machine Learning pipelines using Python, PyTorch, and TensorFlow.
- Lead the research and implementation of cutting-edge algorithms for NLP and Computer Vision applications.
- Optimize model inference latency and accuracy to support real-time, high-volume data processing.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Collaborate with cross-functional product teams to translate business requirements into technical solutions.
- Ensure compliance with AI ethics guidelines and data privacy regulations (GDPR/CCPA).
- Stay ahead of industry trends to integrate emerging technologies into our product stack.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or AI Research.
- Expert proficiency in Python and major ML frameworks (PyTorch, TensorFlow, JAX).
- Proven track record of deploying production-ready ML models serving millions of requests.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP), and MLOps.
- Experience with LLMs, RAG architectures, and prompt engineering is highly desirable.
- Excellent problem-solving skills and ability to thrive in a fast-paced, ambiguous environment.