Job Description
We are seeking a visionary Senior AI/ML Architect to help define the technological landscape of 2026. At Nexus Future Labs, we are building the infrastructure for the next decade of intelligent systems. You will not just build models; you will architect the future.
In this pivotal role, you will lead the research and development of cutting-edge artificial intelligence systems, focusing on Generative AI, Large Language Models (LLMs), and autonomous agents. You will work in a high-performance environment, collaborating with cross-functional teams to translate complex business requirements into scalable, ethical, and robust AI solutions.
Why Join Us?
- Work on projects that will directly impact the roadmap for 2026 and beyond.
- Competitive equity package and top-tier healthcare benefits.
- Flexible remote-first culture with access to state-of-the-art hardware.
Responsibilities
- Architect & Design: Design and implement scalable AI/ML infrastructure capable of handling petabyte-scale data and real-time inference demands.
- Research & Innovation: Lead research initiatives in Generative AI, reinforcement learning, and multimodal learning to stay ahead of industry trends.
- Model Optimization: Fine-tune and optimize pre-trained models for specific domain applications, ensuring low latency and high accuracy.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Strategic Planning: Contribute to the long-term technical roadmap, identifying emerging technologies that align with our 2026 goals.
- Deployment: Oversee the end-to-end deployment of models into production environments using CI/CD pipelines and containerization technologies.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years in a lead or architect role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Kubeflow, MLflow) and cloud platforms (AWS, GCP, or Azure) is required.
- AI Expertise: Strong understanding of Large Language Models (LLMs), fine-tuning techniques (LoRA, PEFT), and prompt engineering.
- Problem Solving: Proven track record of solving complex, unstructured problems in dynamic environments.
- Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.