Job Description
Are you ready to define the landscape of 2026?
At FutureScale Solutions, we are not just predicting the future; we are engineering it. As we approach the pivotal year of 2026, our mission is to revolutionize human-machine interaction through advanced, autonomous artificial intelligence. We are looking for a visionary Senior AI/ML Engineer to lead our next-generation generative model initiatives.
In this role, you will architect scalable machine learning systems that push the boundaries of what is possible in predictive analytics and natural language processing. You will work in a high-performance environment where innovation is the currency, and your work will directly shape the core products used by millions worldwide.
Why join us?
- Work on cutting-edge Generative AI and Autonomous Agents.
- Competitive equity package and performance bonuses.
- Top-tier health, dental, and vision insurance.
- Unlimited PTO and flexible remote-first culture.
Responsibilities
- Architect and deploy proprietary Large Language Models (LLMs) optimized for enterprise applications.
- Design and implement MLOps pipelines to ensure model scalability, reliability, and continuous learning.
- Collaborate with cross-functional teams of data scientists, product managers, and engineers to translate complex requirements into robust AI solutions.
- Research and prototype novel algorithms in the fields of reinforcement learning and neural architecture search.
- Mentor junior engineers and conduct code reviews to maintain high technical standards.
- Monitor model performance in production and optimize for latency, throughput, and cost efficiency.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, Physics, or a related field (equivalent experience considered).
- 7+ years of professional experience in machine learning, deep learning, or artificial intelligence engineering.
- Expert proficiency in Python, TensorFlow, PyTorch, or JAX.
- Strong understanding of transformer architectures and state-of-the-art generative models (e.g., GPT, LLaMA).
- Experience with cloud platforms (AWS, Google Cloud, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of deploying models that handle high-volume, low-latency data streams.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, agile environment.