Job Description
Are you ready to architect the intelligent systems of tomorrow?
Nexus Future Systems is pioneering the technology stack for the year 2026. We are looking for a visionary AI/ML Architect to lead our research and deployment of next-generation predictive models. In this role, you won't just be maintaining existing systems; you will be defining the architectural paradigms that will drive enterprise efficiency and innovation for the next decade.
Join a team of elite engineers and researchers dedicated to pushing the boundaries of Artificial Intelligence. We offer a competitive compensation package, equity opportunities, and a remote-first culture that fosters creativity and high performance.
Why Join Us?
- Work on cutting-edge projects that define the future of tech.
- Competitive salary and equity package ($180k - $250k).
- Flexible remote-first work environment.
- Access to state-of-the-art hardware and cloud resources.
Responsibilities
- System Architecture: Design scalable, fault-tolerant machine learning infrastructure capable of processing petabytes of data in real-time.
- Pipeline Development: Lead the end-to-end development of ML pipelines, from data ingestion and processing to model training and deployment.
- Innovation Strategy: Identify and implement emerging AI technologies (e.g., Generative AI, Reinforcement Learning) to solve complex business problems.
- Model Optimization: Continuously monitor model performance, conduct A/B testing, and optimize algorithms for latency, accuracy, and cost.
- Team Leadership: Mentor junior data scientists and engineers, fostering a culture of technical excellence and continuous learning.
- Collaboration: Work closely with product managers and engineering teams to translate business requirements into technical specifications.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
- Experience: Minimum of 5+ years of professional experience in Machine Learning Engineering or Data Science.
- Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Cloud Expertise: Proven track record deploying models on AWS, GCP, or Azure using containerization tools like Docker and Kubernetes.
- Mathematical Maturity: Strong foundation in linear algebra, calculus, probability, and statistical modeling.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.