Job Description
We are at the precipice of a technological singularity. Apex Future Systems is seeking a visionary Lead AI Engineer to architect the foundational models that will define the Year 2026 and beyond. If you are passionate about pushing the boundaries of Generative AI, Autonomous Agents, and Cognitive Computing, this is your opportunity to shape the future.
Why Join Us?
In an industry defined by rapid evolution, we are building the infrastructure for the next decade. You will work with a world-class team of researchers and engineers to deploy cutting-edge LLMs, optimize inference at scale, and build AI-native workflows that redefine productivity.
Key Responsibilities:
Responsibilities
- Architect and deploy next-generation Large Language Models (LLMs) tailored for enterprise scalability.
- Design and implement advanced Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and context awareness.
- Lead the fine-tuning process for proprietary datasets, ensuring alignment with specific business objectives and ethical guidelines.
- Optimize model inference latency and resource consumption using techniques like quantization and pruning.
- Collaborate with cross-functional teams to integrate AI agents into real-world applications, from finance to healthcare.
- Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.
- 5+ years of professional experience in AI/ML engineering, with a focus on Deep Learning frameworks.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Proven track record of deploying models to production using MLOps tools (MLflow, Kubeflow, or SageMaker).
- Strong understanding of Transformer architectures, NLP, and vector databases (Pinecone, Milvus, Weaviate).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).