Job Description
We are seeking a visionary Senior AI Engineer to join our elite team at Apex Innovations. As we prepare to define the landscape of artificial intelligence for 2026 and beyond, we need a technical leader who can architect scalable, robust, and ethically responsible machine learning systems. If you are passionate about pushing the boundaries of Generative AI and Large Language Models (LLMs), this is your opportunity to shape the future.
At Apex Innovations, we don't just build software; we engineer intelligence. You will work alongside world-class researchers and engineers to deploy models that impact millions of users globally.
Responsibilities
- Architect & Deploy: Design, develop, and deploy end-to-end machine learning pipelines and scalable AI solutions using modern cloud infrastructure (AWS/GCP).
- Model Optimization: Optimize existing models for inference speed, accuracy, and cost-efficiency to handle high-volume production workloads.
- Research & Innovation: Stay at the forefront of AI research, evaluating new papers and methodologies (e.g., Transformers, Diffusion Models) to integrate cutting-edge techniques into our products.
- Technical Leadership: Mentor junior engineers and data scientists, conducting code reviews and establishing best practices for MLOps and data governance.
- Cross-Functional Collaboration: Partner with product managers and designers to translate complex AI capabilities into intuitive user experiences.
- Ethical AI: Ensure all AI systems adhere to ethical guidelines, addressing bias and fairness in model training and deployment.
Qualifications
- Education: Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related field (Master’s or PhD preferred).
- Experience: 5+ years of professional experience in software engineering and machine learning.
- Programming: Proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Cloud Skills: Strong experience deploying models on cloud platforms (AWS SageMaker, GCP AI Platform, or Azure ML).
- Data Engineering: Experience with data wrangling, feature engineering, and working with large-scale datasets.
- Soft Skills: Excellent communication skills, ability to explain complex technical concepts to non-technical stakeholders, and a proactive problem-solving mindset.