Job Description
About Us: At 2026 Labs, we are not merely predicting the future; we are architecting it. We are a forward-thinking technology collective focused on developing autonomous systems and next-generation neural networks that will define the era of 2026 and beyond. We are seeking a visionary Senior Artificial Intelligence Engineer to lead our core research and deployment efforts.
The Role:
You will be at the forefront of the AI revolution, designing scalable machine learning architectures that solve complex, real-world problems. You will work closely with product leaders and data scientists to translate cutting-edge research into production-ready software. If you are passionate about pushing the boundaries of what is possible with deep learning and want to leave a legacy in the tech industry, we want to meet you.
Responsibilities
- Architect & Deploy: Design, implement, and maintain high-performance deep learning models and neural network architectures.
- Optimization: Optimize algorithms for speed, scalability, and accuracy, ensuring low latency in production environments.
- Research & Development: Stay abreast of the latest advancements in AI/ML research and integrate novel techniques into our product suite.
- Collaboration: Partner with cross-functional teams (Data Science, Engineering, Product) to define technical requirements and roadmaps.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of innovation and continuous learning within the engineering team.
- Infrastructure: Manage cloud infrastructure (AWS/Azure) and MLOps pipelines to streamline the model lifecycle.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: Minimum of 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior or lead capacity.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Tools: Experience with containerization (Docker/Kubernetes) and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Proven track record of solving complex technical challenges and delivering robust, scalable solutions.
- Communication: Excellent verbal and written communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.