Job Description
Join the Future of Intelligence at Apex Neural Systems
We are pioneering the next generation of generative AI and deep learning models. As a Lead AI/ML Engineer, you will not just build algorithms; you will architect the brain of our enterprise solutions, impacting millions of users globally. If you are passionate about pushing the boundaries of what’s possible with Large Language Models (LLMs) and Computer Vision, this is your stage.
Why Join Us?
- Impactful Work: Directly influence the roadmap of our flagship AI platform.
- Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits.
- Modern Tech Stack: Work with the latest in PyTorch, TensorFlow, and Kubernetes.
- Remote-First Culture: Flexible working arrangements for top talent.
The Role:
We are seeking a visionary engineer to lead our machine learning infrastructure. You will collaborate with cross-functional teams of data scientists, product managers, and researchers to deliver scalable, high-performance AI systems.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art deep learning models for natural language processing and predictive analytics.
- Infrastructure Optimization: Build scalable ML pipelines and MLOps infrastructure to support model training and deployment at scale.
- Research & Innovation: Stay ahead of industry trends in AI, experimenting with novel architectures and techniques to improve model accuracy and efficiency.
- Code Review & Mentorship: Provide technical leadership, mentor junior engineers, and ensure code quality across the team.
- Collaboration: Work closely with product teams to translate complex business requirements into robust technical solutions.
- Performance Tuning: Monitor model performance in production, identify bottlenecks, and implement optimization strategies.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or senior engineering role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed computing.
- Tools: Experience with cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and MLflow or similar MLOps tools.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.
- Problem Solving: Strong analytical skills with a proven track record of solving complex engineering challenges.