Job Description
Are you ready to architect the systems that will define the future? Apex Future Tech is seeking a visionary Senior AI/ML Engineer to lead our 2026 strategic initiatives. In a world rapidly evolving towards autonomous systems and generative intelligence, your work will set the standard for the next decade of technological advancement.
We are not just building software; we are engineering the reality of 2026. You will work in a dynamic, high-performance environment where innovation is not just encouraged—it is mandatory.
Why Join Us?
- Work on groundbreaking projects that shape the trajectory of AI.
- Competitive compensation package reflecting 2026 market standards.
- Unlimited PTO and flexible remote-first culture.
Responsibilities
- Architect Intelligent Systems: Design and deploy scalable Machine Learning pipelines capable of handling 2026-scale data challenges and real-time inference.
- Lead Research & Development: Spearhead research in Large Language Models (LLMs), Generative AI, and Neural Architecture Search to push the boundaries of what is possible.
- Optimize Performance: Continuously improve model accuracy, reduce latency, and optimize resource utilization for edge and cloud deployment.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineers to translate complex AI capabilities into user-centric, high-impact solutions.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Ethical AI Implementation: Ensure all deployed models adhere to strict ethical guidelines, safety protocols, and fairness standards.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related field, with a focus on AI/ML.
- Experience: 5+ years of professional experience in building and deploying production-grade Machine Learning models.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Docker, Kubernetes, MLflow) is highly preferred.
- Specialized Knowledge: Strong background in NLP, Computer Vision, or Reinforcement Learning. Familiarity with LLM fine-tuning and RAG architectures.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems with innovative technical solutions.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to diverse stakeholders.