Job Description
Are you ready to architect the future of intelligent systems? 2026 is a next-generation technology firm dedicated to building the infrastructure for the year 2026 and beyond. We specialize in autonomous decision-making, predictive analytics for smart cities, and next-gen human-computer interfaces.
We are seeking a visionary Senior Machine Learning Engineer to join our elite R&D team in San Francisco. You will be responsible for designing scalable neural networks and deploying AI models that operate in real-time, high-stakes environments.
Why join 2026?
- Impactful Work: Your code will directly shape the operational reality of future cities.
- Top-Tier Talent: Collaborate with PhDs and industry veterans in a culture of innovation.
- Equity Package: Competitive stock options as we scale towards our 2026 launch.
- Modern Stack: Work with the latest in PyTorch, Kubernetes, and Edge Computing.
Key Responsibilities:
- Design, develop, and deploy state-of-the-art deep learning models for predictive maintenance and computer vision.
- Optimize algorithms for low-latency, high-throughput environments on edge devices and cloud infrastructure.
- Collaborate with cross-functional teams of hardware engineers and data scientists to integrate AI models into physical systems.
- Mentor junior engineers and conduct code reviews to ensure architectural integrity and scalability.
- Stay ahead of the curve in research papers and emerging AI methodologies to apply cutting-edge techniques.
Qualifications:
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in building and deploying production-level ML systems.
- Strong proficiency in Python, TensorFlow, PyTorch, and SQL.
- Experience with MLOps tools (Docker, Kubernetes, AWS SageMaker) and CI/CD pipelines.
- Deep understanding of Natural Language Processing (NLP) or Computer Vision.
- Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.
Responsibilities
- Design, develop, and deploy state-of-the-art deep learning models for predictive maintenance and computer vision.
- Optimize algorithms for low-latency, high-throughput environments on edge devices and cloud infrastructure.
- Collaborate with cross-functional teams of hardware engineers and data scientists to integrate AI models into physical systems.
- Mentor junior engineers and conduct code reviews to ensure architectural integrity and scalability.
- Stay ahead of the curve in research papers and emerging AI methodologies to apply cutting-edge techniques.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in building and deploying production-level ML systems.
- Strong proficiency in Python, TensorFlow, PyTorch, and SQL.
- Experience with MLOps tools (Docker, Kubernetes, AWS SageMaker) and CI/CD pipelines.
- Deep understanding of Natural Language Processing (NLP) or Computer Vision.
- Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.