Job Description
Are you ready to engineer the future? Nexus 2026 is at the forefront of next-generation artificial intelligence, developing autonomous systems that redefine human-machine interaction. We are seeking a visionary Senior AI & Machine Learning Engineer to join our elite engineering team in San Francisco.
In this role, you won't just write code; you will architect the neural pathways of tomorrow. You will work on cutting-edge projects ranging from generative adversarial networks to predictive deep learning models. We offer a competitive compensation package, equity options, and the opportunity to work in a culture that prioritizes innovation, scalability, and ethical AI.
Why join Nexus 2026?
- Work on products that will shape the trajectory of technology for the next decade.
- Collaborate with world-class researchers and engineers in a high-performance environment.
- Flexible remote-first culture with a vibrant in-office community in the heart of SF.
If you are passionate about pushing the boundaries of what is possible in AI, we want to hear from you.
Responsibilities
- Design, develop, and deploy scalable machine learning models and deep learning architectures using Python and modern frameworks.
- Collaborate with cross-functional teams of data scientists, product managers, and engineers to define AI product requirements.
- Optimize algorithms for high throughput, low latency, and high accuracy in production environments.
- Conduct rigorous A/B testing and model evaluation to ensure performance benchmarks are met.
- Stay abreast of the latest advancements in AI research and implement novel techniques into our core systems.
- Mentor junior engineers and contribute to the technical roadmap of the AI division.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of professional experience in machine learning, data science, or AI engineering.
- Strong proficiency in Python, PyTorch, TensorFlow, or Keras.
- Deep understanding of statistical modeling, natural language processing (NLP), or computer vision.
- Experience with big data technologies (Spark, Hadoop, or cloud-based data warehouses like Snowflake or BigQuery).
- Proven track record of shipping production-grade machine learning models.
- Excellent problem-solving skills and ability to thrive in a fast-paced, agile environment.