Job Description
We are seeking a visionary Senior AI/ML Engineer to join our elite team at Nexus Future Systems. As we prepare to launch our revolutionary products in 2026, we need a technical leader who can architect scalable machine learning solutions and drive innovation in Generative AI and Predictive Analytics.
In this role, you will bridge the gap between theoretical research and practical application, working on high-impact projects that define the future of technology. You will mentor junior engineers, collaborate with cross-functional teams, and deploy state-of-the-art models to production environments.
Why join us?
• Work on cutting-edge technology with a competitive salary and equity package.
• Flexible remote-first culture with opportunities for in-person collaboration.
• Comprehensive health benefits and professional development stipends.
• Be part of a forward-thinking company shaping the 2026 landscape.
Responsibilities
- Design, develop, and deploy advanced machine learning models and algorithms to solve complex business problems.
- Lead the full machine learning lifecycle, from data ingestion and feature engineering to model training and monitoring.
- Optimize model inference latency and scalability to ensure high performance in production environments.
- Collaborate with product managers and engineers to define technical requirements and deliver innovative features.
- Stay current with the latest research in AI/ML and evaluate new tools and frameworks to improve our tech stack.
- Mentor junior data scientists and engineers, fostering a culture of continuous learning and technical excellence.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- 5+ years of professional experience in machine learning, data science, or a related technical role.
- Strong proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Extensive experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, GCP, or Azure).
- Proven track record of deploying production-grade models and managing MLOps pipelines.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.