Job Description
We are 2026, a pioneering technology firm dedicated to architecting the future of artificial intelligence. We are seeking a visionary Senior Machine Learning Engineer to join our elite engineering team in San Francisco. If you are passionate about pushing the boundaries of generative models and scalable infrastructure, this is your opportunity to shape the digital landscape of tomorrow.
In this role, you will lead the development of next-generation AI systems, collaborating with world-class researchers and engineers to deploy high-impact solutions. You will own the full ML lifecycle, from experimental research to production-grade deployment, ensuring our products remain at the cutting edge of technological advancement.
Why join 2026?
- Work on groundbreaking projects that define the future of technology.
- Competitive compensation package and equity options.
- Unlimited PTO and a flexible remote-first culture.
- Access to state-of-the-art hardware and research facilities.
Responsibilities
- Design, train, and deploy complex machine learning models and algorithms at scale.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
- Mentor junior engineers and foster a culture of innovation and continuous learning within the team.
- Optimize existing models for speed, accuracy, and cost-efficiency in production environments.
- Conduct rigorous experimentation and A/B testing to validate model performance and drive product improvements.
- Stay abreast of the latest research in AI/ML and integrate cutting-edge methodologies into our engineering stack.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field (PhD preferred).
- 5+ years of professional experience in machine learning engineering, data science, or a related role.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience with big data technologies (e.g., Spark, Kafka, Hadoop) and cloud platforms (AWS, GCP, or Azure).
- Proven track record of shipping production-level machine learning applications.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.