Job Description
Join the Architects of the Future
Apex Future Systems is seeking a visionary Senior AI/ML Engineer to lead our R&D division dedicated to defining the technological landscape of 2026 and beyond. We are building the infrastructure that will power the next generation of intelligent applications, moving beyond current limitations into the realm of autonomous systems and generative intelligence.
In this pivotal role, you will not just build models; you will define the architecture for scalable, ethical, and high-performance artificial intelligence systems. You will collaborate with a world-class team of data scientists, engineers, and product strategists to deliver solutions that are robust, scalable, and ready for the enterprise of tomorrow.
Why Join Us?
- Work on cutting-edge technology that is shaping the future.
- Competitive compensation package including equity.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to mentor the next generation of engineering talent.
If you are passionate about pushing the boundaries of what is possible with Machine Learning, we want to hear from you.
Responsibilities
- Design, train, and deploy state-of-the-art Machine Learning models, focusing on scalability and real-time inference for 2026 use cases.
- Lead the architecture and implementation of Generative AI pipelines, including LLM fine-tuning and RAG (Retrieval-Augmented Generation) frameworks.
- Collaborate with cross-functional teams to translate complex business requirements into robust technical solutions and algorithms.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Optimize existing models for latency, throughput, and cost efficiency on cloud infrastructure (AWS/GCP).
- Stay abreast of the latest advancements in AI research and implement best practices in code quality and MLOps.
- Ensure data privacy, security, and ethical AI compliance in all model development processes.
Qualifications
- 5+ years of professional experience in Software Engineering, with at least 3 years specifically focused on Machine Learning or Deep Learning.
- Proficiency in Python and major ML frameworks such as PyTorch, TensorFlow, or JAX.
- Strong understanding of Deep Learning architectures (CNNs, RNNs, Transformers, GANs).
- Experience with MLOps tools (Kubeflow, MLflow) and containerization technologies (Docker, Kubernetes).
- Familiarity with cloud platforms (AWS, Google Cloud Platform) and big data technologies (Spark, Hadoop).
- Excellent problem-solving skills and the ability to work in a fast-paced, agile environment.
- Master’s degree or PhD in Computer Science, Mathematics, or a related technical field is preferred.