Job Description
Shape the Future of Intelligence
Are you a visionary engineer ready to define the next era of artificial intelligence? Apex Innovations Inc. is seeking a world-class Senior AI/ML Engineer to join our elite San Francisco team. We are not just building models; we are architecting the cognitive architecture of tomorrow. If you thrive in a fast-paced, high-impact environment and possess an insatiable curiosity for deep learning, this is your stage.
Why Join Us?
- Impact: Work on cutting-edge Large Language Models (LLMs) and generative AI systems that will redefine human-computer interaction.
- Equity: Competitive stock options and performance bonuses.
- Flexibility: Hybrid work model with a focus on results, not hours.
As we scale our infrastructure to support global operations, we need a technical leader who can bridge the gap between theoretical research and production-grade deployment. You will be mentoring junior talent and setting the technical roadmap for our AI initiatives.
Responsibilities
- Design, train, and deploy scalable machine learning models and deep neural networks to solve complex business problems.
- Lead the end-to-end ML lifecycle, from data ingestion and preprocessing to model training, evaluation, and production monitoring.
- Collaborate closely with data scientists and software engineers to integrate AI models into our core product suite.
- Optimize existing algorithms for speed, accuracy, and efficiency using distributed computing frameworks.
- Stay abreast of the latest research in NLP, Computer Vision, and Reinforcement Learning to drive innovation.
- Conduct rigorous A/B testing and model validation to ensure robustness and reliability in production environments.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience).
- 5+ years of professional experience in machine learning engineering, with a strong portfolio of deployed models.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of distributed computing (e.g., Spark, Kubernetes, AWS SageMaker, Google Cloud AI Platform).
- Experience with MLOps tools (MLflow, Kubeflow) and version control (Git).
- Strong problem-solving skills and the ability to translate complex technical concepts into actionable insights.