Job Description
Shape the Future of Intelligence. Nexus Horizon AI is pioneering the next generation of autonomous systems for 2026 and beyond. We are seeking a visionary Senior AI & Machine Learning Engineer to architect scalable models and drive the technological frontier. If you are passionate about the intersection of deep learning, generative AI, and ethical computing, we want to meet you.
As a key member of our elite engineering team, you will work on cutting-edge projects that redefine human-machine interaction. You will have the autonomy to experiment, innovate, and deploy solutions that impact millions globally.
Responsibilities
- Architect and deploy: Design and implement robust machine learning pipelines and production-grade deep learning models using Python, PyTorch, and TensorFlow.
- Model Optimization: Continuously research and apply state-of-the-art (SOTA) techniques to improve model accuracy, latency, and efficiency for real-time applications.
- Infrastructure Management: Collaborate with DevOps teams to manage cloud infrastructure (AWS/GCP) and implement MLOps best practices for continuous integration and deployment.
- Data Strategy: Lead the end-to-end data lifecycle, including data ingestion, cleaning, feature engineering, and dataset curation for training large language models.
- Cross-functional Collaboration: Partner with product managers, researchers, and designers to translate complex technical requirements into user-centric AI solutions.
- Innovation Labs: Explore emerging technologies such as Quantum AI and Edge Computing to prepare our architecture for the demands of 2026.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field with a focus on AI/ML.
- Experience: Minimum of 5+ years of professional experience in developing, training, and deploying machine learning models in a production environment.
- Technical Stack: Proficiency in Python, SQL, and experience with deep learning frameworks (PyTorch or TensorFlow).
- Big Data: Strong understanding of distributed computing, Spark, Hadoop, and experience working with large-scale datasets.
- Problem Solving: Demonstrated ability to tackle complex algorithmic problems and optimize for performance under constraints.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.