Job Description
We are seeking a visionary Senior AI/ML Engineer to lead our next-generation machine learning initiatives. At Apex Digital Systems, we are building the future of intelligent systems, leveraging Large Language Models (LLMs) and generative AI to transform how businesses interact with data.
In this role, you will not just write code; you will architect the neural networks that power our core product suite. If you are passionate about pushing the boundaries of what is possible in AI and possess a deep understanding of distributed systems, this is your opportunity to lead at the intersection of data science and engineering.
Why Join Us?
- Work with state-of-the-art technology stacks including PyTorch and TensorFlow.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
Responsibilities
- Design and implement state-of-the-art deep learning architectures for Natural Language Processing (NLP) and Computer Vision applications.
- Optimize existing models for inference speed and memory efficiency to ensure real-time performance on edge devices.
- Collaborate with cross-functional teams of data scientists, software engineers, and product managers to deliver high-impact AI features.
- Conduct rigorous A/B testing, model evaluation, and debugging to ensure production-grade reliability and accuracy.
- Stay abreast of the latest research in the field and implement cutting-edge techniques such as Transformers, RAG, and Fine-tuning.
- Drive the full ML lifecycle from data ingestion and preprocessing to model deployment and monitoring.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
- Minimum of 5+ years of professional experience in building, deploying, and maintaining machine learning models.
- Strong proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
- Deep understanding of NLP concepts, including tokenization, embeddings, and fine-tuning LLMs (e.g., GPT, BERT, Llama).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Excellent communication skills and the ability to translate complex technical concepts for non-technical stakeholders.