Job Description
We are looking for a visionary Senior AI & Machine Learning Engineer to lead our next-generation initiatives for the 2026 era. At Nexus Horizon Labs, we are building the foundational technologies that will define the future of intelligent systems. If you are passionate about pushing the boundaries of what's possible with Artificial Intelligence and want to be at the forefront of innovation, we want to meet you.
In this role, you will be responsible for architecting scalable AI solutions, driving research breakthroughs, and mentoring a team of top-tier engineers. You will work directly with C-level executives to define the technical roadmap for our flagship products.
Responsibilities
- Architect Scalable ML Systems: Design and implement robust, scalable machine learning pipelines capable of processing petabytes of data.
- Lead Research & Innovation: Spearhead research initiatives focused on Generative AI and Reinforcement Learning to prepare for the technological landscape of 2026.
- Model Optimization: Fine-tune and optimize deep learning models for high performance on edge devices and cloud infrastructure.
- Technical Leadership: Mentor junior engineers, conduct code reviews, and establish best practices for software engineering and data science.
- Cross-Functional Collaboration: Partner with product managers, designers, and data engineers to translate business requirements into technical solutions.
- Roadmap Definition: Define and execute the technical vision for AI integrations, ensuring alignment with company goals.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field from a top-tier university.
- Experience: 5+ years of professional experience in machine learning engineering, with a proven track record of deploying production-ready models.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and Scikit-learn. Strong understanding of Deep Learning architectures (CNNs, RNNs, Transformers).
- Tools: Experience with MLOps tools (Kubernetes, Docker, MLflow) and cloud platforms (AWS, GCP, Azure).
- Soft Skills: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Passion: A deep passion for the future of AI and a desire to solve humanity's most complex challenges.