Job Description
Are you ready to define the future of technology?
2026 is a premier technology firm pioneering the next generation of intelligent systems. We are looking for a visionary Senior Machine Learning Engineer to join our elite engineering team in San Francisco. If you are passionate about pushing the boundaries of what is possible and want to work on projects that will impact millions, we want to hear from you.
Why Join 2026?
- High-Impact Work: Build and deploy scalable AI solutions that solve real-world problems.
- Competitive Compensation: Attractive base salary, performance bonuses, and equity packages.
- Modern Stack: Work with the latest tools in Python, TensorFlow, and Cloud Infrastructure.
- Inclusive Culture: A diverse team of thinkers and doers committed to innovation.
We offer a dynamic environment where your contributions are valued, and your career can soar.
Responsibilities
- Model Development: Design, train, and deploy state-of-the-art machine learning models using Python and Deep Learning frameworks (TensorFlow/PyTorch).
- Infrastructure: Build robust, scalable backend systems to support real-time data processing and high-volume inference.
- Optimization: Continuously monitor, evaluate, and optimize model performance for accuracy, speed, and resource efficiency.
- Cross-Functional Collaboration: Partner closely with Data Scientists, Product Managers, and Engineering leads to translate business requirements into technical roadmaps.
- Research & Innovation: Stay ahead of the curve by researching emerging trends in Generative AI, LLMs, and Reinforcement Learning.
- Mentorship: Guide junior engineers and contribute to a culture of technical excellence and knowledge sharing.
Qualifications
- Experience: 5+ years of professional experience in Machine Learning Engineering, Data Science, or a related technical field.
- Education: Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related field (Master’s degree is a plus).
- Technical Skills: Proficiency in Python, SQL, and cloud platforms (AWS, GCP, or Azure).
- Deployment: Strong experience with containerization (Docker) and orchestration (Kubernetes).
- Communication: Excellent verbal and written communication skills with the ability to explain complex concepts to non-technical stakeholders.