Job Description
We are building the technological infrastructure for the year 2026. Apex Future Systems is seeking a visionary Senior AI Engineer to lead our next-generation AI research division. If you are passionate about the future of Generative AI, Large Language Models (LLMs), and autonomous agents, this is your opportunity to define the standard for artificial intelligence.
In this role, you will architect scalable AI solutions, optimize model performance, and integrate cutting-edge technologies to solve complex business problems. You will work in a high-impact environment where innovation is not just encouraged but required.
Why Join Us?
- Work on the frontier of AI technology.
- Competitive salary and equity package.
- Flexible remote-first culture with a vibrant SF office.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Architect & Deploy: Design, build, and deploy scalable Generative AI models and LLM-based applications using modern frameworks like LangChain and LlamaIndex.
- Model Optimization: Fine-tune pre-trained models and optimize inference latency for production environments.
- RAG Pipelines: Design and implement Retrieval-Augmented Generation (RAG) architectures to enhance model accuracy and reduce hallucinations.
- MLOps Implementation: Establish robust MLOps pipelines for model versioning, monitoring, and automated retraining.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to translate business requirements into technical AI solutions.
- Research & Innovation: Stay ahead of industry trends (e.g., 2026 AI roadmaps) and experiment with emerging technologies to drive product differentiation.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field (PhD preferred).
- Experience: 5+ years of experience in software engineering, with at least 2 years specializing in AI/ML and LLMs.
- Programming: Proficiency in Python, PyTorch, or TensorFlow.
- AI Expertise: Strong understanding of Natural Language Processing (NLP), Transformer architectures, and Vector Databases (Pinecone, Milvus).
- Tooling: Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Communication: Excellent verbal and written communication skills; ability to explain complex AI concepts to non-technical stakeholders.