Job Description
Are you ready to architect the intelligence of tomorrow? Apex Future Systems is seeking a visionary Senior AI & Machine Learning Engineer to spearhead our next-generation R&D initiatives. In this role, you will define the technical roadmap for our upcoming 2026 product suite, pushing the boundaries of what is possible in generative AI and autonomous systems. We are looking for a builder who thrives in ambiguity and is driven by the challenge of solving complex, unsolved problems.
Responsibilities
- Architect Scalable Solutions: Design and implement robust machine learning pipelines and neural network architectures capable of processing petabytes of real-time data.
- Lead Research & Development: Spearhead the exploration of cutting-edge algorithms, focusing on Large Language Models (LLMs) and reinforcement learning to drive product innovation.
- Model Optimization: Engineer high-performance models that operate efficiently in edge environments, optimizing for speed, accuracy, and resource consumption.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering leads to translate theoretical research into production-ready features.
- MLOps Implementation: Establish and maintain CI/CD pipelines for machine learning, ensuring reproducibility and scalability across our cloud infrastructure.
- Technical Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning within the team.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering, with a strong focus on machine learning and artificial intelligence.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with distributed computing frameworks (Apache Spark, Ray) is highly preferred.
- Domain Knowledge: Proven track record of deploying state-of-the-art models in production environments.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to tackle ambiguous problems with structured, data-driven methodologies.