Job Description
Join 2026: Shape the Future of Intelligent Systems
Are you a visionary engineer ready to define the trajectory of artificial intelligence? 2026 is a next-generation technology firm focused on building the infrastructure for a smarter, autonomous world. We are looking for a Senior Machine Learning Engineer to lead the development of cutting-edge generative models and scalable AI architectures.
In this role, you won't just write code; you will architect the solutions that power the next decade of human-computer interaction. We value autonomy, technical excellence, and the boldness to experiment.
Why join us?
- Impactful Work: Deploy models that directly influence millions of users.
- Top-Tier Compensation: Competitive salary and equity packages.
- Future-Ready Tech: Work with the latest in LLMs, computer vision, and edge computing.
Responsibilities:
- Design, train, and deploy state-of-the-art machine learning models and large language models (LLMs).
- Architect scalable MLOps pipelines to ensure model reliability and real-time inference.
- Collaborate with cross-functional teams of researchers, product managers, and designers to translate business requirements into technical solutions.
- Conduct rigorous testing and validation to ensure model accuracy, fairness, and robustness.
- Stay ahead of the curve on emerging AI research and integrate novel techniques into production systems.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications:
- PhD or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- 7+ years of professional experience in machine learning, AI, or data science.
- Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Demonstrated track record of shipping production-grade machine learning applications.
- Deep understanding of NLP, Computer Vision, or Reinforcement Learning is a plus.
Responsibilities
- Design, train, and deploy state-of-the-art machine learning models and large language models (LLMs).
- Architect scalable MLOps pipelines to ensure model reliability and real-time inference.
- Collaborate with cross-functional teams of researchers, product managers, and designers to translate business requirements into technical solutions.
- Conduct rigorous testing and validation to ensure model accuracy, fairness, and robustness.
- Stay ahead of the curve on emerging AI research and integrate novel techniques into production systems.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications
- PhD or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- 7+ years of professional experience in machine learning, AI, or data science.
- Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Demonstrated track record of shipping production-grade machine learning applications.
- Deep understanding of NLP, Computer Vision, or Reinforcement Learning is a plus.