Job Description
Are you ready to define the AI landscape of 2026?
Nexus Dynamics is seeking a visionary Senior Machine Learning Engineer to lead our next-generation artificial intelligence initiatives. In this role, you will be at the forefront of deploying Large Language Models (LLMs) and generative AI technologies that will shape the future of enterprise automation. If you are passionate about pushing the boundaries of what's possible in machine learning and want to work in a culture of innovation, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware and frameworks.
- Competitive compensation and equity packages.
- Flexible remote-first policy with premium office amenities.
- Opportunity to mentor the next generation of AI talent.
Responsibilities
- Architect & Deploy: Design, build, and maintain scalable machine learning infrastructure and pipelines for high-traffic applications.
- Model Optimization: Fine-tune and optimize large language models for specific industry use cases, ensuring high performance and low latency.
- Research & Innovation: Stay ahead of the curve by researching cutting-edge AI techniques and integrating them into our product suite.
- Collaboration: Partner with cross-functional teams of data scientists, product managers, and engineers to translate complex business requirements into technical solutions.
- Mentorship: Guide junior engineers and provide technical leadership within the team.
Qualifications
- Education: Master’s or PhD in Computer Science, Statistics, or a related field.
- Experience: 5+ years of professional experience in machine learning engineering, with a strong focus on Deep Learning and NLP.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex problems and deliver robust, production-ready code.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.