Job Description
Join the Architects of Tomorrow.
Nexus Future Labs is pioneering the next generation of artificial intelligence, aiming to redefine human-computer interaction by the year 2026. We are seeking a visionary Senior AI/ML Engineer to lead our core research initiatives.
In this role, you won't just build models; you will architect the foundational systems that will power the digital ecosystem of the future. You will work in a high-performance environment with a focus on scalability, ethics, and groundbreaking innovation.
Why Join Us?
- Work on cutting-edge Generative AI and Predictive Analytics.
- Competitive equity package and performance bonuses.
- Flexible remote-first policy with access to premium tech hubs.
If you are passionate about pushing the boundaries of what's possible in machine learning, we want to hear from you.
Responsibilities
- Architectural Leadership: Design and implement scalable, robust machine learning infrastructure capable of processing petabytes of data in real-time.
- Research & Development: Pioneering novel algorithms to solve complex problems in natural language processing and computer vision.
- Model Optimization: Continuously monitor, evaluate, and optimize model performance to ensure low latency and high accuracy.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and software engineers to translate business requirements into technical solutions.
- Ethical AI: Ensure all AI models adhere to strict ethical guidelines and bias mitigation standards.
- Mentorship: Guide and mentor junior engineers, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Statistics, or a related field (or equivalent industry experience).
- Experience: 7+ years of professional experience in machine learning, deep learning, or artificial intelligence.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Docker, Kubernetes, MLflow).
- Cloud Expertise: Strong experience deploying models on major cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Demonstrated ability to troubleshoot complex technical challenges and innovate under pressure.
- Communication: Excellent verbal and written communication skills for technical presentations and documentation.