Job Description
Are you ready to architect the intelligence of tomorrow? Apex Future Labs is seeking a visionary Senior AI/ML Engineer to lead our next-generation research initiatives. As we prepare for the 2026 technological landscape, you will be at the forefront of deploying scalable, robust, and ethical AI systems that redefine user experiences.
We are looking for a self-starter who isn't just following trends but is setting them. In this role, you will bridge the gap between theoretical research and production-grade software, ensuring our AI solutions are both cutting-edge and commercially viable.
Why join us?
- Work on groundbreaking projects that will define the industry standards for 2026.
- Competitive compensation package with equity options.
- Flexible remote-first culture with state-of-the-art office amenities.
- Continuous learning budget and access to top-tier research conferences.
Responsibilities
- Design, train, and deploy advanced machine learning models, including Large Language Models (LLMs) and Computer Vision systems.
- Lead the architecture and optimization of MLOps pipelines to ensure scalability and efficiency.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business needs into technical solutions.
- Conduct rigorous testing and validation of AI models to ensure accuracy, fairness, and compliance with data privacy regulations.
- Stay ahead of industry trends in AI, advising leadership on emerging technologies and their potential impact on the business.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
Qualifications
- Master’s or PhD degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in machine learning engineering, with a focus on Python and deep learning frameworks (TensorFlow, PyTorch, JAX).
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven experience in building and optimizing production-grade AI/ML systems.
- Experience with data wrangling, feature engineering, and model interpretability.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.