Job Description
2026 Technologies is pioneering the next generation of intelligent systems. We are building the infrastructure that will define the digital landscape of the future. We are seeking a visionary Principal AI Engineer to lead our advanced modeling initiatives and shape the technology of tomorrow.
In this pivotal role, you will define the architectural roadmap for our flagship products, pushing the boundaries of generative AI, predictive analytics, and autonomous systems. If you are passionate about the future and want to solve complex problems that have no immediate answer, we want to hear from you.
Responsibilities
- Architect and implement scalable machine learning pipelines for high-volume data processing and real-time inference.
- Lead the research and development of novel algorithms to enhance model accuracy, efficiency, and robustness.
- Mentor a high-performing team of data scientists and engineers, fostering a culture of innovation and technical excellence.
- Collaborate closely with product management and engineering teams to translate business requirements into cutting-edge technical AI solutions.
- Ensure the ethical deployment of AI systems, rigorously adhering to industry safety standards and compliance regulations.
- Optimize model inference latency and reduce computational costs to maximize resource efficiency.
- Stay ahead of the curve by monitoring emerging trends in AI, NLP, and computer vision.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, Statistics, or a related field (PhD preferred).
- 8+ years of hands-on experience in Machine Learning, Deep Learning, or AI research.
- Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Apache Spark, Ray, or Kubernetes).
- Strong understanding of Large Language Models (LLMs), Transformer architectures, and Reinforcement Learning.
- Proven track record of deploying production-grade AI models that drive measurable business impact.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices.