Job Description
We are seeking a visionary Senior AI & Machine Learning Engineer to define the technical roadmap for our next-generation generative AI platform. As we approach the technological horizon of 2026, we are looking for experts who can bridge the gap between theoretical deep learning and scalable production systems. You will work with a world-class team to build autonomous agents that redefine human-computer interaction.
Why Join Us?
At Nexus Innovations, we are not just building software; we are architecting the intelligence of the future. You will have the autonomy to experiment, the resources to scale, and the impact to change the world. We offer a competitive benefits package, equity options, and a flexible work environment.
Responsibilities
- Model Architecture: Design, train, and deploy state-of-the-art Large Language Models (LLMs) and multi-modal AI systems optimized for 2026 standards.
- System Optimization: Architect high-performance computing pipelines to reduce model latency and maximize throughput in real-time environments.
- MLOps Leadership: Establish and implement best practices for MLOps, including automated CI/CD pipelines, model versioning, and monitoring.
- Research & Development: Conduct cutting-edge research into novel neural architectures and reinforcement learning techniques to stay ahead of industry trends.
- Cross-Functional Collaboration: Partner with product managers and engineers to translate complex AI capabilities into user-centric, scalable features.
- Ethical AI: Lead initiatives to ensure fairness, transparency, and safety in AI decision-making processes.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related field with a focus on Artificial Intelligence.
- Experience: 5+ years of professional experience in deep learning, machine learning engineering, or data science.
- Technical Skills: Expert proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Apache Spark, Kubernetes).
- NLP Specialization: Strong background in Natural Language Processing (NLP), Transformers, and Large Language Models (GPT, Llama, etc.).
- Problem Solving: Demonstrated ability to tackle complex mathematical problems and optimize algorithms for large-scale data.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.