Job Description
The Opportunity
Nexus AI Solutions is at the forefront of the next technological revolution. As we prepare for the AI landscape of 2026, we are seeking a visionary Senior Machine Learning Engineer to lead our core research and development initiatives. You will be responsible for building scalable, robust AI systems that power our enterprise clients. This is a rare opportunity to shape the future of artificial intelligence in a dynamic, high-growth environment.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Models.
- Competitive equity package and performance bonuses.
- Flexible remote-first culture with state-of-the-art equipment.
Your Mission
We are looking for a leader who is not just proficient in current technologies but is also looking ahead to the challenges and opportunities of 2026. You will bridge the gap between theoretical research and practical application, ensuring our products remain ahead of the curve.
Responsibilities
- Architect and deploy scalable machine learning pipelines using Python, TensorFlow, and PyTorch.
- Lead the design of novel neural network architectures for natural language processing and computer vision.
- Collaborate with cross-functional teams including data scientists, engineers, and product managers to define AI roadmaps.
- Optimize models for low-latency inference in production environments.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
- Stay ahead of industry trends, specifically focusing on advancements relevant to the 2026 AI ecosystem.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Minimum of 5 years of professional experience in machine learning engineering.
- Deep expertise in deep learning frameworks (PyTorch, TensorFlow, JAX).
- Strong proficiency in SQL and distributed data processing (Spark, Hadoop).
- Proven track record of shipping production-grade ML models.
- Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.