Job Description
Are you ready to architect the technology solutions that will define the future of 2026 and beyond? Apex Innovation Labs is seeking a visionary Senior AI/ML Engineer to lead our next-generation research initiatives. In this pivotal role, you will bridge the gap between theoretical research and production-grade deployment, ensuring our AI systems are scalable, ethical, and transformative.
Our mission is to pioneer artificial intelligence that solves complex global challenges. You will work alongside a team of world-class researchers and engineers, pushing the boundaries of what is possible with neural networks, generative models, and predictive analytics.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Models.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in the heart of SF.
Responsibilities
- Model Architecture & Development: Design, train, and deploy state-of-the-art machine learning models using Python, TensorFlow, and PyTorch.
- Data Strategy: Oversee the end-to-end data lifecycle, from ingestion and cleaning to feature engineering and model training.
- System Optimization: Optimize existing pipelines for latency, throughput, and cost-efficiency to support high-volume production environments.
- Research & Innovation: Stay ahead of the curve by researching emerging trends in AI, including Reinforcement Learning and Explainable AI (XAI).
- Collaboration: Partner with product managers and data scientists to translate business requirements into technical AI solutions.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related field (or equivalent practical experience).
- Experience: 5+ years of professional experience in software engineering or machine learning development.
- Technical Skills: Proficiency in Python, SQL, and deep learning frameworks (PyTorch/TensorFlow).
- AI Expertise: Strong background in NLP, Computer Vision, or Recommender Systems.
- Cloud Native: Experience deploying models on AWS, GCP, or Azure using Docker and Kubernetes.
- Communication: Excellent verbal and written communication skills for technical presentations and documentation.